In a world increasingly shaped by artificial intelligence, automation, and rapid organizational change, what does it truly mean to lead? How can business leaders stay relevant in such a dynamic landscape? What role will humans play in this technology-powered future? These questions were explored in the latest Innovantage podcast episode, hosted by Sigli’s CBDO, Max Golikov. Max invited Stijn Staes to share his expert insights.Stijn is the founder of Stappen met Stijn, a transformation coach, and the host of a podcast on leadership, diversity, and the evolving relationship between people and agentic AI.Stijn has always had a passion for helping people to grow. His career began in nursing and hospital management. He traveled around the world with such organizations as Doctors Without Borders. Back in Belgium, he served as general manager of the country’s largest private youth institution. He always stayed focused on the same mission: unlocking human potential. For the past six years, Stijn has worked as an independent executive coach, sharing his insights through coaching and his podcast.What is diversity?According to Stijn, deep down, all human beings are fundamentally the same. Today, diversity is often treated as a buzzword, which is used to assign labels based on race, culture, gender, or identity. Nevertheless, Stijn emphasized that beneath these labels lies a shared human desire: to be seen, to be heard, and to feel connected.Effective leadership should start with recognizing this common humanity, while also adapting communication styles to meet people where they are. Cultural and personal differences matter. But they should act not as boundaries but as bridges. Stijn sees diversity not only in visible identity but also in how we communicate, relate, and create space for others to belong.He explained that true diversity in an organization is not just about representation. It is about developing the awareness and emotional intelligence to engage with people as individuals, each with their own way of being heard and understood.How to communicate in the right wayFor Stijn, effective communication, especially in leadership, starts with curiosity. He believes that staying curious helps us avoid judgment, which is the most common pitfall in human interaction. Miscommunication often stems not from what is said, but from assumptions we bring into a conversation when we fail to truly listen.Curiosity is the gateway to the right communication. It keeps us engaged and open to others’ views.Key challenges for building a diverse cultureOne of the key challenges in building a truly diverse culture is our natural desire to get involved with people who think, speak, and act like us. While this may feel comfortable, it is a serious mistake.According to Stijn, effective leaders must actively look for individuals who can offer constructive criticism and challenge ideas. This will not disrupt, but deepen understanding and improve outcomes. This requires humility and openness. For many leaders, the real challenge isn’t embracing diversity on paper, but learning to welcome feedback that doesn’t align with their own thinking.How to provide feedback: Trust and intentionStijn believes that trust and intention are two essential elements of giving feedback effectively. Trust creates the psychological safety necessary for honest communication. It means knowing the other person will speak with honesty, respect, and a shared commitment to growth. Without that foundation, feedback can easily feel personal or threatening.The intention behind the feedback is equally important. Feedback should not be about proving who is right or wrong. It also shouldn’t serve the ego. Its true purpose is to improve the organization’s services and outcomes for clients. When both parties understand that feedback delivers value and supports common growth, much of the emotional tension often associated with difficult conversations will be eliminated.Stijn is strongly confident that feedback culture works not only on a small, team-based level. It can be scaled across an entire organization. In his view, feedback should not be limited to face-to-face teams or familiar colleagues. It’s a fundamental part of a healthy organizational culture, and it should reach every level, including interns and CEOs.Asking simple, respectful questions (like how someone prefers to work or whether the timing is right) opens the door to meaningful, two-way communication.Are visionary leaders bad for the corporate culture?Visionary leadership is essential but only when paired with self-awareness and a genuine understanding of what the organization needs. Leaders must recognize not only their strengths but also their limitations and remain open to diverse perspectives.Stijn cautioned against authoritarian leadership, noting that while it might deliver short-term gains for shareholders, it undermines long-term sustainability. A resilient organization requires transparency and a culture of open feedback. This doesn't mean leaders must act on every suggestion they receive, but they should always listen, consider, and respond with thoughtful reasoning.This helps build not just a business, but a strong community around it.The most effective strategies for change managementWhile talking about approaches to changes, Stijn mentioned the case from his time as a general manager. His organization needed to integrate 150 new employees into an existing workforce of 300. This required forming 30 newly blended teams and simultaneously introducing a new way of working.Instead of imposing change from the top down, Stijn and his team focused on deep listening and inclusive planning. They did their best to understand what mattered most to employees. This transparent and people-centered approach was key to the transformation. Despite the scale of change, only 2% of employees left the organization.Instead of relying on algorithms or AI tools, they conducted one-on-one conversations, online questionnaires, and team meetings to find out what mattered most to their people.Leaders from across locations came together to analyze the findings and co-create new team structures. Several proposals for the reorganization were shared with employees, who could give feedback and even request alternative roles. As a result, almost everyone ended up exactly where they wanted to be.Stijn believes successful leadership rests on three pillars:Love for people and for what you are doing;Knowing your business and having a clear insight into what works and what doesn’t;Listening to your gut and trusting your intuition to act at the right moment.Pitfalls of change managementWhen guiding an organization through intensive transformation, something will inevitably go down a little (and that is usually income).This temporary drop, however, is not a failure. It’s the cost of meaningful, people-centered change. When done with care, clarity, and the right timing, the organization stabilizes and rebounds stronger. But if the transformation is rushed or poorly managed, the downward curve continues. An organization may experience employee dissatisfaction, increased turnover, and loss of trust.For Stijn, effective change management starts with a fundamental truth: there is always a change. Sometimes it is big, sometimes it is small. But it is constant. The real challenge isn’t initiating change, but allowing people the time and space to integrate it.Quite often, companies move from one transformation to the next without pause. A new manager comes in and brings another change. However, humans need time to settle, to process, and to feel included. In Stijn’s practice, his team always made sure to involve people actively. Weekly newsletters, employee-written reflections, and open communication created a sense of shared ownership and psychological safety.Change isn’t something you tick off a list. It lives on long after the formal transformation phase ends. Sustainable change requires a long-term mindset, a culture that embraces uncertainty, and leadership that shows up fully.If you see change as a box to check, it won’t work. Because this isn’t AI. This is human. And humans need to be seen and heard.Uncontrollable changesMax shared insights about Sigli. In its early days, Sigli was a young, energetic, and even impulsive team. It was common for employees, who were mostly in their twenties, to work late, play video games, and socialize a lot. The culture embraced this youthful energy.Over time, the team matured. Those who once spent late nights gaming now had families and different priorities. Staying late at the office became less common, and personal life took precedence. However, hiring practices continued to focus on attracting younger, energetic candidates, which created a cultural disconnect. This shift wasn’t a result of deliberate organizational change but rather a natural evolution driven by time. Here comes a question: How can a company manage or anticipate these kinds of uncontrolled, organic changes that happen naturally over time rather than through planned initiatives?Stijn emphasized the importance of self-reflection for leaders navigating change. He believes every leader must regularly ask themselves if they are still the right fit for their role and the company’s future. Given that external circumstances constantly evolve beyond anyone’s control, the only thing leaders can truly change is themselves.Stijn also pointed out that as companies grow, the leadership style and team composition may need to change as well. A startup’s energy might require younger leaders, while scaling up could call for more experienced, seasoned managers. They must be aware of their role in this evolution and have the courage to step aside if necessary.Self-reflection is the key tool for recognizing when organizational change becomes a must.Do surveys really work?That’s not a rare case when corporate surveys fail. Response rates are too low, while the data quality leaves much to be desired. In a 300-person organization, it’s typical to get only about 100 responses, and even then, the reliability of the answers can be questionable.However, there is nothing wrong with this format itself. The survey’s purpose plays a major role. In Stijn’s practice, surveys always worked best when participants could see clear personal relevance. For example, when a questionnaire directly impacted employees’ next career steps, response rates were 100%, as everyone understood its importance.If there’s no immediate benefit or urgency, responses always tend to be incomplete or socially biased. Therefore, it’s crucial to evaluate whether a survey is the right tool for the information needed. Sometimes, one-on-one conversations or group meetings might be more effective.Given all this, Stijn advised against relying on surveys alone. A combination of methods tailored to the goals and the audience can ensure the best engagement and data quality.Will everything be AI?The discussion also touched on the power of AI. Stijn mentioned an article arguing that AI will inevitably replace most jobs related to data, presentations, and routine business tasks. According to it, humans will remain essential mainly for fieldwork and personal interactions, while AI handles data-driven tasks efficiently and without complaint.Stijn also believes that many technical tasks, especially those repeated in meetings and spreadsheet discussions, will be taken over by AI. However, he stressed the importance of understanding where humans fit in this evolving landscape. It’s necessary to determine the ways in which people can grow, adapt, and focus on uniquely human strengths.For example, we shouldn’t underestimate the value of robots that can assist elderly people. But human connection cannot be replaced by such assistants.Every person should stay aware of new technologies and trends. But it is not a good idea to accept things just because they are popular. It is necessary to remain curious and question the true value of all innovations. Business leaders need to analyze whether some changes genuinely serve the company, society, and the world or whether they are just a new trend that has no practical benefits.The fact that AI can create art does not diminish the value of human-made art. While technology like 3D printers can produce sculptures, they don’t carry the same meaning or connection as those crafted by human hands. The same applies to drawings and paintings. AI-generated art lacks the personal insight and emotional depth that come from human creativity.The true value lies in creations made by people. Without the human element, this value is lost.Human touch: What sets people apart from AIThe role of AI in professional life is growing. However, it has its clear limitations. Stijn explained that there are AI programs that could technically replace an interviewer or even an interviewee. Nevertheless, he admitted that he doesn’t want to do an interview with a machine. The essence of a real conversation is unpredictability, nuance, and emotional presence.Artificial intelligence can’t replicate the human dynamic of live dialogue. Human interviews are not just about answering questions. It’s about connection.AI is a powerful tool, but not a replacement for human interaction. For instance, you can practice foreign languages with AI. But you can grow only with people.Key trends shaping the future of leadershipStijn highlighted a growing polarization in leadership styles. On one end, we can see ego- and result-driven leadership. On the other hand, there is a more human-centered, empathetic approach. These two directions seem to be drifting further apart.The real challenge lies in bridging the tech world and human-focused leadership. Technology is essential. But without a human, all this won’t make sense.And that’s one of the main theses voiced by the guests of the Innovantage podcast episodes. Technologies are changing and replacing each other. But human communication is always here. And it will definitely stay.Want to know more about the world of technology and business? New episodes with new guests are coming soon.

This article explores how to launch successful AI projects that create measurable business value, based on Sigli's “AI Profit Toolkit” webinar for SMEs. It highlights key considerations before starting with AI, including when not to use it, how to evaluate feasibility with the AI value matrix, and the importance of aligning AI use cases with business KPIs. A real-world case study from a UK e-commerce company shows how an LLM-powered returns bot improved refund times and cut costs. The post also offers practical advice on data quality, quick-win AI pilots, and stakeholder sponsorship to ensure high ROI. Ideal for decision-makers seeking to implement AI with confidence and clarity. Artificial intelligence continues to change the way businesses operate. When applied sensibly, this technology opens up a wide range of new possibilities for efficiency, innovation, and profitability. At Sigli, we strongly believe that we should use our deep business and tech knowledge to help individuals and companies uncover the practical value of cutting-edge AI-powered tools. One of our latest initiatives in this space was a free educational webinar for SMEs titled “The AI Profit Toolkit”. The event was hosted by Sigli’s Chief Business Development Officer Max Golikov.This article includes the key takeaways from the webinar and offers actionable guidance for anyone looking to launch AI projects that deliver real value without excessive risks.What you should know about AI before you even startOne of the most important principles to understand before diving into AI is that it is not always the answer.AI is a powerful tool. But it doesn’t mean it should be applied universally. In many situations, simpler, more cost-effective technologies may yield better and faster results. The key is to find out why you want to use AI and whether a non-AI solution might accomplish the same goal with less complexity. If there are other approaches to addressing your needs, it may turn out to be much more sensible to use them instead of investing in an AI project.Nevertheless, we by no means deny the business value of AI. It’s absolutely measurable and wide-ranging. According to industry insights shared during the webinar, AI’s contributions to business value break down into several categories:57% comes from boosting productivity, primarily through automation.17% stems from automating routine daily tasks.16% is linked to enhancing customer experience.The remaining 10% covers a range of other use cases.The transformative power of AI is especially tangible when applied thoughtfully to pain points that drain time and resources.AI value matrixTo evaluate whether your future AI project is worth your time and money, we recommend you use an AI value matrix. This strategic tool helps find the right balance between the technical feasibility and business value of your ideas.According to this approach, on the technical side, you will need to assess:Data quality. The foundation of any successful AI project is high-quality data. Projects with clean, abundant data move faster and require fewer resources at every stage of development and maintenance.Technological complexity. Before committing to an AI project, you need to consider the resources needed to move from idea to impact. Low-complexity solutions (like plug-and-play SaaS and low-code components) tend to score best on the AI value matrix.Availability of talent and skills. Even if your problem seems to be solvable with AI, you also should carefully analyze whether you have experts with the required skills in-house or whether you are ready (and have the budget) to hire reliable partners. Moreover, if you choose the second path, make sure that you have a hand-off plan.On the business side, it will be necessary to focus on such aspects as:Alignment with business goals. AI should be tightly aligned with your strategic objectives or profit and loss (P&L) metrics. This ensures you are not chasing tech trends for their own sake but solving real, impactful business problems.Sponsor support. Every AI project needs a committed sponsor. In the ideal scenario, it should be someone who owns the budget and the performance metrics that the project aims to improve. For example, projects that have a C-level sponsor are likely to move much faster than those supported by people without the authority to sign cheques or make decisions independently.Measurable KPIs. Your AI use case should be built around a small set of clear, quantifiable KPIs. For instance, these metrics might include time saved, cost reduction, revenue growth, or user engagement. It makes sense to choose the KPIs that are already tracked and understood in your organization. This will help you avoid debate over measurement methods and simplify the “before vs. after” comparisons.The projects that score highest across both dimensions are those with the highest likelihood of success and return on investment.Choosing the right AI pilot: A real-world exampleDuring the webinar, Max Golikov shared a couple of powerful case studies to demonstrate what you should pay attention to while considering different ideas for your AI projects. One of the examples was Sigli’s cooperation with a mid-sized UK apparel e-commerce retailer.The company had an annual revenue of £48 million and 220K monthly orders. 12 fulfillment staff processed orders, returns, and refunds via three legacy tools (Magento, Zendesk, and homemade Excel macros).When the company turned to Sigli, they had serious issues with the time needed for different processes. The returns and exchange queue averaged 5000 orders, which caused 7-day refund delays and seriously hurt the company’s rankings on Trustpilot. Apart from that, manual triage was pretty expensive as it cost £3.40 per refund.Another problem was the fact that the customer support team had to spend 30% of time copy-pasting return merchandise authorization (RMA) info instead of applying upsell techniques and driving sales.To solve the described issues, it was offered to consider different ideas, including an LLM-powered returns-triage bot, a demand-forecast bot, and a personalized upsell recommender.As the AI value matrix shows, the first idea won.For such a solution, the company had rich training data. The team had access to 95,000 labeled Zendesk tickets, which made it easy and fast to train the AI model.From the integration perspective, there were no serious pitfalls. The solution only needed to connect with the Zendesk API and an existing RMA. It means that the implementation of this bot didn’t require a full system overhaul.Moreover, it was quite simple to detect clear success metrics. Such KPIs as cost per return and refund turnaround time were already being tracked daily. Thanks to this, it was possible to measure the immediate project impact.The project also could receive strong business sponsorship. The Fulfillment COO both owned the P&L and sponsored the pilot.All this led to a successful AI implementation and tangible outcomes:Cut cost per return to £1.90 (a 44% reduction);Reduced refund delays to 2 days (a 72% improvement);Boosted Trustpilot score by 0.3 stars.Key things to keep in mind to maximize the ROI of your AI projectLet us briefly summarize what we’ve discussed above. Based on our practical experience, we recommend focusing on the following points to ensure your AI initiatives deliver real value:Quick-win quadrant. Want to achieve quick wins? Select projects that score at least 7+ on technical feasibility and 8+ on business value on the AI value matrix.Clean and accessible data. Well-organized data always saves time and reduces rework.One clear KPI. Choose a metric that you have been already tracking for a while. Thanks to this, performance can be easily compared before and after implementation.A single, accountable sponsor. A budget-owning stakeholder accelerates decision-making and ensures follow-through.Measurable deliverables. Projects should be much more than just flashy tech demos. They should yield clear financial results.Closing thoughtsArtificial intelligence offers incredible opportunities to streamline operations, reduce costs, and deliver standout customer experiences. However, all benefits become available only when this technology is used deliberately. It means that AI should be guided by clear goals, supported by strong data, and evaluated by hard metrics.At Sigli, we can provide support for your business through every phase of the AI journey: from ideation and pilot planning to full-scale deployment. If you are ready to turn AI potential into business value, we are here to help.

Today, Sigli devotes considerable efforts to helping individuals and companies discover the value of cutting-edge technologies, including artificial intelligence, and their influence on business processes. One of the most recent educational initiatives was a free webinar for SMEs called “The AI Profit Toolkit”. The key goal of the webinar hosted by Sigli’s CBDO Max Golikov was to provide the audience with practical recommendations on how to adopt AI in a practical, budget-conscious way. In this article, we will share the key insights on how to launch AI pilots that create a measurable impact without serious risks. What business value can AI create? The impact of AI can be broken into several categories. The largest portion (57%) of AI’s business value comes from boosting productivity.AI often helps automate daily tasks, reducing manual workload. Everyday routine automation accumulates 17% of the general business value. A share of 16% represents customer experience enhancements. 10% is related to other use cases.Is AI the best technology to use today? The golden rule number one that every business owner and decision-maker should learn is that AI isn’t required everywhere. It’s a powerful technology, but you shouldn’t use it unless you really need it. Instead, you also need to consider other tools. In many cases, their implementation can help you save money and, at the same time, achieve much better efficiency. Before you apply AI, you should have a very good understanding of why you need to do it. How can I estimate the profitability of any AI project? One of the most reliable ways to do it is to apply an AI value matrix. It helps prioritize projects based on technological feasibility and business value. The group of technological factors that should be evaluated covers data quality, technological complexity, as well as the availability of skills and people. Business factors include business goal alignment, sponsor support, and measurable KPIs (like the decrease of time or resources needed for performing this or that task). The project that will get the highest score in the overall results is likely to succeed and bring the most significant impact. How to analyze technological complexity? When you are considering the implementation of a particular AI tool, you need to understand how much time and what resources will be required to achieve the level when this solution starts bringing real value. There are several core questions that you need to ask yourself: Is there a similar native feature in your current SaaS/ERP? (Today, a lot of systems offer their own AI functionality and it is possible that you won’t need to introduce your custom tool instead). Does a managed API already exist? Are there any latency or throughput constraints? Is it secure to implement this solution? Is a security review needed? Those solutions that require minimal effort from your side (like low-code components or plag-and-play SaaS) will get the highest score according to the AI value matrix. What does business goal alignment show? This parameter will help you evaluate the link between the AI use case under consideration and a strategic or P&L (profit and loss) objective. Thanks to it, you will be able to move your focus from overhyped tech trends that don’t have any relation with your existing bottlenecks to mission-critical initiatives. How can I understand that one AI pilot is better than the other one? To answer this question, let’s turn to one of the real-life cases that the Sigli team worked on. The client was a mid-sized Dutch EdTech platform that has 175K active learners on its online courses. The main problem that the company wanted to solve was the reduction of time and resources that were required for user support services. Tutors used to spend 18% of their paid hours answering FAQs, which cost the company more than €1 million per year. Our experts had different project ideas under consideration. Some of them were an LLM tutor-assist bot, a drop-out risk predictor, and an adaptive learning path recommender. As you can see from the matrix below, the first idea won. But why did it happen? To launch such a bot, the company already had a rich set of labeled data (more than 22K historical chat transcripts tagged by topic). There were no specific difficulties in integrating the solution with the company’s platform. It was possible to apply clear success metrics (response time and tutor time). And last but not least, the project received strong support from a single sponsor (it was the Head of Learner Success who owned the tutor budget and worked with retention KPIs). As a result, the successfully implemented tool helped cut the median first-time response time by 84% from 8h to 1.3h and free 0.25 FTE (full-time equivalent) per tutor. How to make sure that my AI implementation will be a successful one? To maximize the ROI of your AI project, you need to focus on the key elements: Quick-win quadrant on the AI value matrix. You should select projects that score at least 7+ on Technical Feasibility and 8+ on Business Value. These are the ideal quick wins. Clean and accessible data. High-quality, well-organized data significantly reduces preparation time and helps avoid repeated model re-training. One primary KPI. It is vital to choose a use case with a clear metric that is already tracked. This makes "before vs. after" comparisons simple, and you can eliminate the need for extra instrumentation or debate. Single budget owner as a sponsor. Having one accountable stakeholder enables fast approvals, resource access, and sustained momentum. Measurable business deliverables. You should make sure that your AI project produces tangible, financial results. The goal is to prove that AI delivers profit, not just innovation for its own sake. Final word Artificial intelligence can help you overcome a lot of existing bottlenecks and greatly boost your business growth. But all this is possible only when AI is applied deliberately, with the right expectations and a strong business case. As you can see, the most successful AI initiatives are not driven by hype or fear of missing out. They are driven by clearly defined goals and measurable outcomes. At Sigli, we are always ready to support your business at any stage of your AI journey: from strategy development and pilot selection to full-scale implementation. Don’t hesitate to contact us and learn more about how to turn the potential of AI into real business value.

The episodes of the Innovantage podcast hosted by Sigli’s CBDO Max Golikov cover a wide range of topics, including technology, business, and the role of digitalization. In the spotlight of the new episode are not just technologies, but also people. How can business leaders successfully implement innovations without facing resistance from their teams?Thiago de Faria, Senior Solutions Architect at AWS and a recognized Team Topologies expert, shared his perspective on this and many other important questions.Thiago has spent the past decade at the intersection of data, distributed systems, and organizational dynamics. Through years of hands-on experience, he came to understand that success isn’t just about algorithms or tools. It’s about communication and how teams work together.This insight led him to pursue leadership roles, including such positions as CTO, director, and team lead. He later joined AWS, where he led startup solutions architect teams, working closely with early-stage startups. After a period of freelancing, Thiago returned to AWS. Now, he focuses on enterprise modernization. His goal is to help organizations realize that technology is rarely the real challenge in their transition. They need to pay more attention to everything else around it. “It is about people, and it has always been.”For Thiago, building sustainable businesses goes far beyond technology. It is about people and communication. Success depends on understanding human behavior, managing egos, and being kind.He doesn’t believe in the top-down leadership model and the "do it because I'm the boss" mindset in the modern world. Today’s teams are motivated by more than just money or fear. The traditional stick-and-carrot approach no longer works. Instead, leaders must tap into what truly drives people and apply that insight to how technology and organizations evolve.Team Topologies as a framework for structuring teamsThiago mentioned Team Topologies as a powerful framework for structuring teams and improving how they collaborate. It was developed and described by Matthew Skelton and Manuel Pais. The framework is based on the ideas of DevOps, Agile, Lean, Deming’s principles, and the Theory of Constraints. Its core goal is to enable fast flow from idea to production, while still meeting security, compliance, and feedback needs.Overplanning or overcommunicating can also be dangerous for team efficiency. Team Topologies introduces a shared language to design team interactions intentionally. Without this structure, teams often drown in context, which can result in cognitive overload and a loss of focus.In Team Topologies, the team is treated as the smallest meaningful unit. And the key idea behind that is the fact that sustainable outcomes come from well-structured, collaborative teams rather than separate heroes. Team Topologies isn’t a rigid framework or a call for company-wide reorganization. Instead, it starts with identifying value streams and understanding how work actually flows through the organization.How to implement significant cultural changes within teamsThiago emphasized that meaningful cultural change within teams is neither strictly top-down nor bottom-up. It requires a combined approach. Such changes take time. It can be quarters or sometimes even years. The key is to create sufficient awareness of the broader context, the processes in place, and the value stream itself. By determining bottlenecks and reducing handovers, organizations can begin shifting toward a more collaborative and efficient culture.This cultural shift is deeply tied to technical practices rooted in DevOps: continuous integration, continuous deployment, fast feedback loops, trunk-based development, and robust testing. But it’s not just about better tooling. It’s about bridging the gap between business and technology.One of the biggest mindset shifts is moving away from a factory-style model where tech teams wait for perfect requirements before building. Instead, developers must become more curious about the business and more engaged with customer needs. Collaboration shouldn't be sporadic, and it shouldn’t be handed off via tickets or rigid requirements. It should be ongoing. The core challenge lies in bridging the gap between existing infrastructure and organizational culture. It can’t be imposed top-down through mandates or principles alone.The real test of culture comes during crises like missed deadlines, outages, or security issues. In such situations, nobody wants to take responsibility for that because responsibility can be really painful.Often, it is not about people avoiding responsibility, but about misalignments and overloaded teams that make real ownership nearly impossible.That’s where the principle of fast flow becomes crucial. To avoid such situations, it is necessary to reduce cognitive load, streamline knowledge requirements, and minimize distractions. This will allow teams to focus on real ownership and deliver value more effectively.Psychological safety is a must for cultural changesAccording to Thiago, there is no one-size-fits-all model for implementing cultural changes. One of the biggest challenges is building psychological safety, which is a prerequisite for any meaningful transformation. If even one person on a team doesn’t feel safe, the team as a whole isn’t truly safe.Psychological safety starts with trust among teammates, across roles, and with leadership. Trust isn’t built through blind agreement. It’s built through transparency.For Thiago, a practical way to foster trust is to surface assumptions and clearly explain decisions. People don’t have to agree with every call, but they should understand the rationale behind it. Disagreement is fine when it is followed by commitment and free of blame if things go wrong.Platform groupsOne of the most impactful ideas to emerge from Team Topologies is the concept of platform groups. They are responsible for building and maintaining internal platforms, tools, services, and building blocks that reduce the cognitive load for product-focused teams.Thiago explained that teams that are directly delivering customer value are often overwhelmed. They are expected to handle everything: databases, deployment pipelines, infrastructure, testing frameworks, compliance, programming patterns, and business context. That’s an unrealistic cognitive burden, and it’s often why these teams default to focusing only on the technical layer.Platform groups solve this by offering clear, reusable paths, or prebuilt ways to deploy services, manage infrastructure, or handle CI/CD. Their main goal is to streamline delivery by eliminating unnecessary friction.However, many companies misapply this concept. They form a single overloaded “platform team” tasked with managing everything, from CI/CD and data infrastructure to Git workflows. As a result, such teams become a bottleneck themselves. That’s why the shift to true platform groups is important. Here, it is essential to keep in mind that they should be purpose-driven, focused units with clear boundaries, allowing for scale without burnout.Thiago also highlighted another team pattern from Team Topologies. It is enabling teams. They unite cross-functional experts, such as architects or systems specialists, who embed temporarily with other teams to unblock problems, offer guidance, and enable better practices before moving on. Companies should think of them as internal consultants focused on capability-building, not control.Transformative impact of cloud computingCloud computing introduced a profound shift in the technology landscape.The first big transformation it enabled was accessibility. Cloud computing removed the barrier to entry. It turned infrastructure into a utility that is available on demand based on the pay-as-you-go principle. It enabled startups and solo entrepreneurs to bring ideas to life without the need to secure bank loans just to spin up their first server.But the second wave of transformation came with serverless technologies (or, as Thiago calls it, “serviceful” computing). Instead of managing servers or configuring infrastructure, teams can now focus almost entirely on solving business problems. These new patterns allowed developers to work faster, experiment more freely, and scale effortlessly. This approach closely aligns with the principles behind Team Topologies.Thiago admitted that this shift was the biggest he had seen in his career before the AI transformation that we can observe today.However, he emphasized that not everything belongs in the cloud. There are workloads that make a lot of sense to keep on-prem. This is especially relevant for companies with decades of investment, expertise, and operational maturity around legacy systems.The real challenge of cloud transformation isn’t just technical, it’s human. Telling someone their years of expertise with data centers or custom infrastructure are no longer needed can trigger fear and resistance. That’s why change management becomes essential.Cloud-first approach: Is it always a good idea?Many companies today embrace a “cloud-first” approach. But, as Thiago noted, it’s often cloud-first only until compliance or cost gets in the way. The problems typically begin when companies attempt a “big bang” migration and try to rebuild or replatform everything at once. Thiago recollected cases where highly competent teams are tasked with rebuilding existing systems from scratch on the cloud, but team members didn’t have enough experience in cloud-native patterns.What comes next is often a “lift and shift” migration. It means that applications are moved to the cloud using the same designs and operational assumptions that worked on-premise. As you can understand, this method can result in multiple issues.Sometimes a lift and shift makes sense (for example, when delaying migration would incur hardware costs or lease renewals). But that should be the exception, not the rule. Instead, Thiago advised a more incremental, wave-based approach that includes team enablement and intentional architectural planning.The key to successful cloud-first transitions again lies in psychological safety. Companies should help people understand why the transition is happening and show how their existing knowledge can evolve in a cloud context.From the cloud back to on-premise solutionsToday, there are a lot of talks about cloud repatriation, which presupposes moving workloads back to on-prem. However, Thiago clarified that, in practice, he rarely sees this happening at scale. More frequently, he can observe companies that have never completed their cloud transition in the first place. These organizations may have adopted a “cloud-first” mindset years ago, only to realize later that some workloads were better left on-prem, or that not all systems needed to move.According to him, it’s vital to understand that not everything needs to be in the cloud.But today, cloud providers are prepared even for scenarios that require local infrastructure. Quite often, they offer hybrid options. For instance, Outposts by AWS bring AWS-managed infrastructure into the customer’s data center, still connected to the broader AWS ecosystem. It means that businesses can maintain full control locally, but the rest of their systems can still run in the cloud.At the same time, he also highlighted that it’s a myth that running LLMs on-prem is automatically more secure. If you are calling a third-party AI endpoint with no guarantees, that’s one thing. But platforms like AWS Bedrock give you private, VPC-based endpoints where no one else can access your data.Development of cloud computingAccording to Thiago, the 80/20 rule is a good one to describe what is happening in the modern IT infrastructure. 80% of workloads can be handled by broadly available, standardized solutions, while 20% will always require specialized, often bespoke approaches.He explained that platforms like AWS have matured to a point where the majority of business needs can be met using higher-level, off-the-shelf services. The extensive partner ecosystem has enabled businesses to build powerful platforms on top of AWS, without having to reinvent the wheel.Most businesses no longer need to create their own data platforms from scratch. There are already high-level solutions that help them avoid most of the complexity.However, many large enterprises still run highly customized legacy systems, often built on mainframes, and in some cases written in outdated languages with hundreds of thousands of lines of code. These systems are not easy to modernize. But they may be too critical to simply discard.Thiago explained that the middle layer, which is the part between front-end experiences and the legacy back ends, has already been undergoing modernization for years. What is left now is the hardest part: modernizing the base layer. It can be a real challenge, especially when companies face a knowledge drain after original developers retire.That’s where AI and ML come into play.AWS, for instance, provides tools like AWS Q Transform for mainframe apps. It leverages AI to analyze and explain complex legacy codebases, making them easier to understand and refactor. Integration of AI and ML into existing systemsThe explosion of interest in generative AI and large language models has captured global attention. Nevertheless, Thiago cautioned against abandoning the foundations of traditional ML, which continue to deliver significant value across industries.In the conversation with Max, Thiago urged organizations not to overlook the decades of progress in statistical learning, which have become overshadowed in the post-ChatGPT era. Since the launch of ChatGPT that happened in November 2022, much of the industry’s focus has shifted disproportionately toward LLMs and generative models, often at the expense of simpler and more efficient ML solutions.Thiago compared today’s LLMs with a battalion of interns. Modern LLMs are capable of generating content, conducting research, and providing ideas, but they are inherently biased and often lacking in precision or authority.“They speak with confidence, like white Reddit males who think they’re always right,” Thiago joked.Hallucinations, inconsistency, and lack of source traceability are among the main issues related to the mass use of large language models. Thiago views this as a call to action for better guardrails, source attribution, and AI literacy.Tip for business leadersMax also asked Thiago to share advice for leaders who want to implement AI solutions and build resilient technical infrastructures.“Be empathetic and be kind. That is the most important thing that I can tell people. Everything else will follow from it,” Thiago said.With all the changes that they can bring, technologies are just tools, people are the drivers of transformation. Leaders must resist the urge to chase innovation for innovation’s sake. Instead, they should focus on enabling teams, simplifying processes, and creating environments where individuals feel safe, valued, and heard. This is the main conclusion that can be made from this insightful conversation.Want to learn more about the world of business and technology? New Innovantage episodes will be available soon.‍

In the episodes of the Innovantage podcast, its host and Sigli’s CBDO, Max Golikov, usually invites guests to talk about technology and its impact on business. But the topic of the latest episode will resonate with a much broader audience. This time, the focus is on the art and the mastery of pitching to investors. Let’s be honest, when teenagers want to go out late for a Friday evening, they also need to make some kind of a pitch in front of their parents.To dive into this and entrepreneurship in and of itself, Max joined the podcast Robin De Cock, Professor of Entrepreneurship at Antwerp Management School.Robin has spent nearly 20 years helping students and business owners develop their ideas. Over time, he noticed that even strong ideas often fail during investor pitches due to poor presentation, which can be frustrating after months of work. This encouraged him to start teaching people how to effectively pitch and sell their ideas. Based on this desire and inspired by the growing body of academic research on pitching, he decided to write his book “Mastering the Pitch”.Evolving perception of entrepreneurshipFor a long time, entrepreneurs were seen as visionaries who could almost predict the future. However, over the past 10 to 15 years, this perception has shifted, especially with the rise of methods like the lean startup.Today’s entrepreneurs focus more on testing hypotheses, experimenting, and validating ideas with the market in iterative cycles to reduce risk. While vision and risk-taking are still important, there is now a stronger emphasis on evidence-based approaches.What is Robin’s book about?Robin’s book “Mastering the Pitch” is aimed at helping people improve the way they present their ideas. His main goal behind writing this book was to ensure that strong, impactful ideas don’t go unnoticed simply because they were poorly presented. He wanted to support entrepreneurs with insights that are not only practical but also grounded in scientific research. Unlike many other books on pitching, which are often based on the author’s personal experience, Robin’s approach brings together data from different sources. The book is built on two key pillars. First, Robin translated complex findings from academic research on pitching into clear insights for a broader audience.Second, he conducted interviews with entrepreneurs and investors across Europe and the US to understand how academic insights align with real-world practice. In his book, Robin also addressed several myths about pitching, starting with the idea that there is a magical formula for success. He compared pitching to dating: what works with one investor might not resonate with somebody else. Another common misconception is the overemphasis on slides. While a visual component is important, Robin explained that successful pitching involves much more. It should also be powered by passion, energy, tone of voice, body language, and team dynamics. Nonverbal elements often play a larger role than words alone in convincing others. Surprising insights from pitching to investors researchOne of the most surprising findings Robin discovered in his research is just how quickly people form impressions. Studies show that within just 150 milliseconds, an audience begins to form an opinion of a speaker. After 30 minutes, people will have a lasting impression of you. This highlights the importance of being yourself from the very start.Robin emphasized that when you are trying to impress investors, pretending to be someone else is not the best way to do it. Perhaps you will be working with these people for years, therefore, honesty and consistency from the very early stages are essential. According to one study, people tend to fall into certain “boxes” or behavior patterns during a pitch. One box is called the pushover. It means that people often agree to change even core aspects of their idea to please investors. Nevertheless, standing firm on your core vision while staying open to constructive feedback is crucial for building long-term trust and credibility.The impact of cultural background on pitching to investorsCultural background plays a significant role in how pitches are delivered and evaluated. Much of the research was conducted in the US. In this country, pitching tends to be bold, direct, and focused on world-changing ideas. In contrast, European investors often look for detailed explanations, early evidence, and proof of concept.In Asia, the approach is more indirect and relationship-based. Trust must be established before business discussions can move forward, and the process is usually more hierarchical. Decisions often take longer as pitches need to pass through multiple levels of approval. Storytelling in pitchesAccording to Robin, the role of storytelling in effective pitching can’t be underestimated. Research shows that stories are 22 times more memorable than facts. Stories capture attention, make messages stick, and help audiences connect emotionally with the idea.Instead of simply listing key elements like the problem, solution, and business model, Robin encourages entrepreneurs to weave these into a narrative. For example, sharing a personal experience that led to discovering a broader market problem can make a pitch far more engaging. But crafting the story is only 50% of the challenge. The other half is delivering it in a compelling and captivating way. Use of humor: Is it a good idea?Humor can be a powerful tool in a pitch. In settings where multiple pitches happen in one day, a well-placed joke can help you stand out. Self-deprecating humor, in particular, can enhance authenticity and build trust.However, there’s a balance to strike. A little humor can enhance your message, but too much can shift focus away from your idea and make the pitch feel unprofessional. The key is to keep humor spontaneous and natural. It could be perfect to use it at the beginning to break the ice.The effectiveness of humor also depends on your personality and the audience. If humor fits your style and aligns with the general tone, it can work well. However, forced, inappropriate, and excessive jokes can damage credibility. Common pitching pitfallsOne of the most common causes of pitch failure is technical glitches, especially with live demos. Robin mentioned the infamous Surface tablet pitch where Microsoft executives struggled with a malfunctioning device. Given this, Robin recommended always testing tech thoroughly and having a plan B.Another example of failures is Steve Ballmer’s overly enthusiastic pitch, which became more entertaining than convincing. This situation is one more proof that balance is a must.Cornerstones of investor relationship buildingA common misconception is that a 10-minute pitch will immediately secure funding. In reality, a pitch is just the starting point of a longer relationship-building process with investors. The goal isn’t just to impress them during your short speech, but to open a conversation that leads to follow-up discussions and eventual trust. Ideally, you will be able to reach a stage where investors approach you because your pitch, press coverage, or buzz around your idea makes them curious.Tailoring your pitch format to the context is crucial. At networking events, a clear and compelling one-minute or even two-sentence pitch can spark meaningful conversations. If you struggle to summarize your startup in a few lines, it may indicate you haven’t yet clarified your core idea. Meanwhile, a full 10-minute pitch should still leave room for dialogue and relationship-building, not just persuasion.Trust and honesty are essential. Trying to hide flaws or challenges can backfire. Investors are experienced and will uncover the truth eventually. Finally, doing your homework on investors is key. Each investor has a specific focus, budget range, and strategic interests. When you understand this, you can tailor your pitch to align with their goals. Moreover, some successful founders also keep investors in the loop with regular updates. This ongoing communication builds familiarity and trust, increasing the likelihood of future investment when the timing is right.The myth of the perfect first pitchOne of the most persistent myths about pitching is the belief that you only get one shot and that it has to be perfect. In reality, very few successful entrepreneurs deliver a flawless pitch the first time. Pitching, like any skill, improves with practice, iteration, and feedback.Take The Beatles, for example: they played over 1,200 live shows before landing their first record deal. Similarly, Jeff Bezos held around 60 investor meetings before raising Amazon’s first million dollars.Pitches evolve. The more you present your idea, the more you learn. With time, you can better realize where people lose interest, which questions come up repeatedly, and what truly resonates. That feedback loop is vital. If multiple investors point to the same weakness, it’s a signal to adapt your message or your business model.Failure is just a part of the process. You can’t succeed without failing along the way.Robin explained that entrepreneurship is rarely a smooth ride. It is more like a roller coaster filled with highs and lows. The way you interpret those ups and downs can make all the difference.If the goal is purely to make money as quickly as possible, the pressure can become overwhelming. Every setback feels like a crisis. However, if the journey is seen as a learning process or a chance to grow, experiment, and improve, then failures become valuable lessons rather than crushing defeats.This perspective applies equally to pitching. Viewing a pitch as a “make-or-break” moment only increases the pressure and anxiety. But if pitching is approached as an opportunity to learn, get feedback, and refine your message, it becomes part of a growth process. The stakes are still high, but the mindset is healthier and more sustainable.How to manage stressManaging stress before and during a pitch is also crucial. Science shows that how we perceive stress plays a major role in how it affects us. If you view stress as a sign that your body is preparing to perform, it can actually enhance your performance. But if you see stress as a threat or a sign of impending failure, it can quickly become debilitating.There are many personal strategies to manage stress, including physical activity, breathing techniques, or even small rituals.Besides that, preparation remains the most powerful antidote to stress. The more prepared you are, the more confident you will feel. But preparation alone isn’t enough. Practicing on stage, in front of an audience, is essential to becoming a great pitcher.AI in pitching to investors: Assistant, not replacementThe current AI hype has certainly influenced pitching, but it can’t replace the human element. As long as humans are making investment decisions, connection remains highly valuable. Pitching through avatars or fully AI-generated videos may deliver a polished message, but it lacks personal connection, which is critical. Investors want to evaluate you, your passion, your credibility, and your commitment. You can’t just sell an idea. You need to show who they will be working with.AI is best used as a co-pilot. It can:Help craft compelling slides;Speed up research;Improve storytelling structure;Offer suggestions on clarity or tone;Simulate investor feedback or likely Q&A questions.For instance, AI can critique your pitch from an investor’s perspective, helping spot missing elements or test how your story holds up under scrutiny. While not all feedback will be useful, it can highlight blind spots or spark new thinking.AI can also help founders prepare for the Q&A session by generating possible questions. Pitching and Q&A: Key tipsAfter the adrenaline rush of a pitch, many entrepreneurs make the common mistake of answering questions before fully hearing them. It’s important to listen carefully to the entire question before responding.During Q&A, avoid getting defensive or attacking the questioner. Investors always want to see that you are open to feedback and able to handle criticism professionally.A useful strategy is to prepare backup slides and “go-to” messages. They should include key points you want to reinforce throughout the Q&A.Structure of a pitchA pitch should have a clear beginning and end, and both are crucial. It’s best to start by connecting with the audience. You can share a personal story, a striking use case, or a key number that highlights the problem. You shouldn’t jump straight to the solution. Instead, it is recommended to focus on why the problem matters.The problem-solution fit must be clear and simple. If the audience doesn’t understand this early on, the rest of the pitch won’t land. This is the backbone of your presentation.To succeed, you need to close with a strong summary of your company, the problem you are solving, and your solution, or finish with your mission. A memorable opening and closing make your pitch much more powerful.Pitch mantra: Keep it short and powerfulInstead of long mission statements, every startup should have a mantra. It is a short, sharp phrase (even just three words) that captures the essence of the business. It helps founders distill their core purpose. It clarifies your thinking and gives others a clear, memorable takeaway.You can use it to open or close your pitch for a strong impression.Talking too much vs. too little in a pitchBoth extremes can hurt a pitch. But in practice, founders are more often guilty of talking too much. It’s rare to see a pitch where too little is said. More commonly, there’s information overload.But humans have a limited capacity to process information quickly. A pitch should be clear, focused, and paced. The perfect pitch in one wordMax asked Robin to describe the perfect pitch in just one word. And teh answer was: passion.Passion shows the founder’s drive and commitment. These are crucial qualities for surviving the highs and lows of entrepreneurship. But passion alone isn’t enough.Equally important is evidence. It is proof that the idea works and that the business case makes sense. A perfect pitch combines both passion and proof.Examples of great pitchesAccording to Robin, there are many strong examples today, especially from female entrepreneurs. One standout was Jasmine Tagesson, founder of Hormona, who delivered a compelling pitch at Slush 2021. Within the first 10-20 seconds, she clearly articulated the problem and created an immediate connection with the audience. It was concise, impactful, and emotionally resonant.A more iconic example is Steve Jobs during the launch of the iPod. His pitch had excellent pacing. He sped up to build excitement and slowed down to emphasize key points. He also delivered a strong competitive analysis, clearly showing the shortcomings of existing products and positioning the iPod as the superior solution. What entrepreneurs should know before a pitchAt the end of their discussion, Robin provided some advice for those who are preparing to make a pitch:Show energy, drive, and genuine belief in your idea.Be well-prepared, know your numbers, and demonstrate that you’re serious and committed.Build a match with investors. Be collaborative and easy to work with. Listen to feedback.In addition, Robin shared a useful framework. It is the four Ps of pitching:Profile. You need to explain who you are and why you are pitching this.Plan. It includes the structure, flow, and logic of your pitch.Proof. You should share evidence, market validation, and data to support your claims.Performance. How you deliver your pitch also matters. Pitching isn’t just a startup ritual. It’s a universal skill that applies to anyone trying to convince others of an idea, a project, or a vision. Whether you are pitching to investors, partners, or even your parents, the same principles will work. You need to be honest, open, and well-prepared.Want to get more actionable insights from business experts and tech leaders? New episodes of the Innovantage podcast will be available soon. Don’t miss them!

Discussies over de vooruitgang die vandaag in de AI-wereld wordt geboekt, gaan vaak gepaard met de veronderstelling dat het binnenkort haalbaarder wordt om AI in te zetten in plaats van echte mensen. Op het eerste gezicht lijken zulke zorgen goed onderbouwd. Maar is dat ook zo? Om hierover te praten en de echte mogelijkheden van AI agents te verkennen, nodigde Max Golikov, host van de Innovantage-podcast en CBDO van Sigli, Frank Sondors uit in de studio.‍Frank begon zijn carrière in big tech bij Google. Dit stelde hem in staat om van dichtbij te zien hoe krachtig machine learning is – niet alleen in advertenties, maar ook als hulpmiddel om bedrijfsgroei te stimuleren.‍Later werkte hij bij verschillende bedrijven met een focus op big data en AI. Toen hij bij een bedrijf genaamd Whatagraph kwam, begon hij traditionele benaderingen van het opschalen van verkoopteams in twijfel te trekken. In die tijd heerste het idee van “groei tegen elke prijs”. Dit werd vaak gerealiseerd door meer verkopers aan te nemen.‍Maar Frank zag dat als een gebrekkige aanpak. De meeste verkoopteams kampen met een hoog verloop, en slechts een klein percentage van de specialisten levert echt betekenisvolle resultaten. Volgens zijn ervaring is van elke tien mensen die je aanneemt er maar één een geboren verkoper. Twee of drie kunnen worden opgeleid, terwijl de rest de motivatie mist of simpelweg niet geschikt is voor de rol.‍Dit inzicht leidde ertoe dat hij medeoprichter werd van Salesforge, een platform dat bedrijven helpt om een verkoop-pijplijn op te bouwen met een minimaal personeelsbestand. Het bedrijf gebruikt big data en AI om repetitieve verkooptaken te automatiseren. Door agent-gebaseerde functies in de software in te bouwen, stelt Salesforge bedrijven in staat om minder afhankelijk te zijn van middelmatige verkopers en hun topspelers in staat te stellen aanzienlijk betere resultaten te boeken.AI agents: Een eenvoudige uitlegVeel bedrijven willen tegenwoordig zogenaamde “autonome mensen” in dienst nemen. Dat zijn individuen die zelfstandig verantwoordelijk kunnen zijn voor een deel van het bedrijf, zonder voortdurende controle. Verkopers worden bijvoorbeeld geacht hun pijplijn te beheren, deals te sluiten en zelfstandig problemen op te lossen. In zo’n situatie biedt het leiderschap begeleiding in plaats van toezicht.Dit concept is vergelijkbaar met hoe AI agents functioneren. Net als autonome werknemers krijgen AI agents een specifiek doel en de context om dat te bereiken. In een verkoopsituatie kan een AI-agent de taak krijgen om te reageren op een potentiële klant op basis van informatie zoals een sales playbook, prijzen of veelgestelde vragen. Het doel is om het gesprek vooruit te helpen richting een micro-conversie, zoals het boeken van een afspraak.In tegenstelling tot traditionele chatbots, die vertrouwen op vooraf gedefinieerde scripts, kunnen AI agents redeneren over inkomende berichten en de beschikbare context gebruiken om intelligent en dynamisch te reageren. Dit vergroot de kans op het gewenste resultaat.AI agents voor salesteamsVolgens Frank is er bij de integratie van AI agents in salesteams geen one-size-fits-all-oplossing. De ideale opzet hangt altijd af van de structuur van het bedrijf en de salesstrategie.In grote organisaties met 50 of meer verkopers richten menselijke vertegenwoordigers zich meestal op hoogwaardige enterprise-accounts, waarbij de waarde van de deal en de lengte van het salestraject de investering rechtvaardigen. Maar bij kleinere accounts – bijvoorbeeld in het MKB-segment – is dit vaak niet kosteneffectief vanwege het lage rendement per deal.Daar blinken AI agents uit. Ze kunnen worden ingezet om outreach via verschillende kanalen te verzorgen, waaronder e-mail of LinkedIn. Ze kunnen MKB-klanten benaderen met gerichte berichten om afspraken te boeken, een productpagina te bezoeken, zich op een platform aan te melden, enzovoort.Door AI agents toe te wijzen aan minder prioritaire of juist volumineuze segmenten, kunnen bedrijven hun efficiëntie maximaliseren. Zo kunnen menselijke verkopers zich concentreren op strategische deals.Frank noemde ook een andere belangrijke toepassing voor AI agents . Veel beginnende startups met minder dan tien medewerkers hebben moeite met het vinden van potentiële klanten. Vaak komt dit doordat de oprichters overbelast zijn met productontwikkeling en klantbeheer.Volgens Frank draait het voortbestaan van een startup om twee dingen: een goed product bouwen en dat effectief verkopen. Als het opbouwen van een sales-pijplijn erbij inschiet, lopen ze grote groeirisico’s.Oprichters hebben dan een paar opties:Ze kunnen zelf klanten gaanzoeken (als ze daar de tijd en vaardigheden voor hebben).Ze kunnen een bureau inhuren (dit is vaak duur).Ze kunnen AI agents inzetten (ze hoeven dan alleen een AI-agent in hun salessoftware te configureren, die autonoom de outreach verzorgt).Hebben AI agents beperkingen?Ondanks de inspirerende voorbeelden die het potentieel van AI agents tonen, zijn er een aantal nadelen waar bedrijven zich bewust van moeten zijn.Een van de grootste valkuilen is niet de technologie zelf, maar de context waarin die wordt gebruikt. Veel kleinere bedrijven benaderen Salesforge met het idee om hun outreach op te schalen. Maar vaak hebben ze op dat moment nog geen product-market fit bereikt. In die gevallen maakt het niet uit of de outreach door mensen, bureaus of AI wordt gedaan – alle inspanningen zullen mislukken.Ten tweede: zelfs met product-market fit kan het zijn dat bedrijven geen channel fit hebben. Niet elke klant reageert positief op een koude e-mail of LinkedIn-bericht. Als een bedrijf verkeerde acquisitiekanalen kiest, kan AI dat probleem niet zomaar oplossen.Frank vergelijkt AI agents met Google Ads: je investeert om conversies te genereren. Maar als dat niet lukt, haak je af. Bij Salesforge leert het team actief waar AI agents het best tot hun recht komen. Ze houden rekening met industrieën, dealgroottes en andere variabelen om het volledige plaatje te begrijpen.Frank noemde ook andere uitdagingen met AI agents. Bijvoorbeeld, wanneer AI e-mails moet schrijven, lukt het vaak niet om berichten te creëren die echt menselijk aanvoelen. Afhankelijk van hoe de agent is opgebouwd en aangestuurd, kan de output er overduidelijk AI-gegenereerd uitzien. Voor veel klanten is dat vandaag de dag een rode vlag.E-mails genereren met AI die aanvoelen alsof ze door een mens zijn geschreven, vereist veel inspanning. Het vraagt om doordachte prompts, rijke contextuele data en slimme technische aansturing achter de schermen. Tools zoals n8n of Make.com kunnen helpen bij het automatiseren van workflows, maar als het eindresultaat robotachtig overkomt, verkleint dat de kans op een reactie.Vier pijlers van succes in salesVolgens Frank hangt succes in moderne verkoop af van wat hij de vier kernpijlers noemt.Pijler 1. E-mail deliverabilityDe eerste en meest over het hoofd geziene factor is of je e-mails überhaupt in inboxen terechtkomen. Deliverability – dus ervoor zorgen dat berichten in de primaire inbox en niet in de spammap terechtkomen – is essentieel. Goede sales outreach begint met software die dit consequent waarborgt. Het maakt niet uit hoe sterk je targeting of boodschap is als niemand je e-mails ziet.Pijler 2. E-mailinfrastructuurDe tweede pijler is de e-mailinfrastructuur, inclusief software- en hardwarecomponenten die invloed hebben op deliverability en verzendreputatie. Frank benadrukt dat een goed geconfigureerde infrastructuur het algehele e-mailsucces verhoogt.Pijler 3. De boodschap zelfDe derde pijler is waar AI agents momenteel de meeste impact maken: e-mailteksten.Een gepersonaliseerde, kwalitatieve e-mail voorbereiden kost een mens al snel 15 minuten. Het vereist onderzoek naar de prospect op LinkedIn, het bekijken van de bedrijfswebsite en het vinden van relevante invalshoeken voor personalisatie. Ondanks die moeite blijft 90% van de e-mails onbeantwoord. Vaak omdat het moment verkeerd is of de ontvanger simpelweg geen interesse heeft.Daarom zijn AI agents zo krachtig. Ze kunnen twee essentiële datasets combineren:Verkoperdata (wat je bedrijf doet, welk probleem het oplost, waardepropositie, prijsstelling en de kosten van niets doen);Koperdata (publiek beschikbare informatie over de prospect, zoals functie, branche, gedrag of bedrijfscontext).Door die te combineren kan AI e-mails genereren die sterk gepersonaliseerd zijn. Zulke e-mails kunnen in de moedertaal van de ontvanger worden opgesteld, wat de respons aanzienlijk kan verhogen. Een e-mail in het Frans versturen naar prospects in Frankrijk kan bijvoorbeeld de respons verdubbelen. Maar er is een addertje onder het gras: wanneer mensen reageren, verwachten ze meestal dat het gesprek in het Frans doorgaat. Je moet dus een Franstalige verkoper klaar hebben staan, anders verlies je het vertrouwen.Pijler 4. TargetingHoe goed je e-mails ook zijn en hoe goed ze worden afgeleverd – als je de verkeerde mensen benadert, verspil je tijd en geld.Historisch gezien werkten SDR’s of marketeers met grote lijsten uit databases en kwalificeerden ze leads handmatig. Dat is extreem tijdrovend en foutgevoelig. Nu beginnen AI agents deze taak effectiever over te nemen.Frank stelt dat AI beter is dan mensen in het kwalificeren van lijsten om één simpele reden: lagere foutenmarges. AI kan duizenden leads verwerken met consistente logica, en markeren welke contacten wel en niet binnen je ICP passen.Waar AI agents in uitblinkenDe effectiviteit van AI agents hangt sterk af van de dealgrootte en de lengte van het salestraject. Bij grote, langdurige enterprise-deals is het realistischer om AI-co-piloten te gebruiken die mensen ondersteunen, in plaats van volledige automatisering. Enterprise sales zijn nog steeds sterk relationeel, en het risico op een AI-fout blijft een knelpunt. Hoe groter de inzet, hoe minder bereid bedrijven zijn om taken volledig aan AI over te laten.Maar bij low-ticket deals met korte salescycli blinken AI agents uit. Hier zijn autonomie en snelheid cruciaal. Bedrijven kunnen AI agents inzetten om grootschalige outreach te verzorgen.Ondanks de huidige beperkingen leveren AI agents al indrukwekkende prestaties bij outreach naar kleine accounts. Frank ziet responspercentages van 2–2,5%, waarvan 10–20% positief is. Zelfs met hoge verwerkingskosten is het rendement hoog genoeg om de inzet op te schalen.Over de toekomst gesproken, noemde Frank het belang van “agentic swarms” (geen op zichzelf staande agents, maar onderling verbonden teams van AI agents, elk verantwoordelijk voor een ander deel van het salesproces). Bedrijven moeten zulke swarms zien als digitale SDR-teams. De ene agent bouwt lijsten, de volgende verzorgt de outreach, een ander beheert follow-ups en weer een ander plant afspraken in.Toekomst van AI agents en mensen in het bedrijfslevenAI agents veranderen nu al hoe bedrijven mensen aannemen, processen opzetten en operaties optimaliseren. Dat roept een grote vraag op: zullen mensen in de toekomst nog een rol blijven spelen in het bedrijfsleven?Elk bedrijf heeft repetitieve taken, en slimme bedrijven proberen die taken te automatiseren met behulp van AI agents. Zoals Frank aangaf, zijn ze bij Salesforge daar een paar maanden geleden actief mee begonnen via n8n, een geavanceerde tool voor workflowautomatisering. Daarmee kunnen ze complexe flows bouwen, AI agents aansturen, code genereren en operaties beheren zonder extra personeel aan te nemen.Dat is het doel: meer output genereren zonder het team uit te breiden. Salesforge wil tegen eind 2025 zo’n 1.000 n8n-flows creëren, wat neerkomt op 10–20 nieuwe flows per week. Iedereen bij Salesforge draagt daaraan bij door repetitieve taken te signaleren die ze willen automatiseren.Deze automatiseringsgerichte mentaliteit beïnvloedt ook hun aanpak van werving. Frank legde uit dat ze bij een bedrijfsprobleem steeds de volgende vragen stellen.Kunnen we dit oplossen met een standaard AI-agent?Zo niet, kunnen we een aangepaste automatisering bouwen in n8n?Als dat niet lukt, kunnen we een bureau of consultant inschakelen?Pas als al die opties falen, overwegen ze een nieuwe werknemer aan te nemen.Ze hebben voor deze aanpak gekozen omdat werving tegenwoordig traag, duur en competitief is – vooral in tech.De rol van een “Amerikaanse mentaliteit”Frank noemde ook het belang van wat hij de Amerikaanse mentaliteit noemt. Die is gebaseerd op het behouden van voorsprong op de concurrentie door efficiënter te werken, overbodig personeel te schrappen en operaties voortdurend te optimaliseren. In zijn ogen worden bedrijven die niet innoveren of stroomlijnen eenvoudig ingehaald door anderen.Sommige sectoren zijn al 20 tot 30 jaar nauwelijks veranderd, en Frank vindt dat zorgwekkend. Ondertussen evolueren landen als de VS en China razendsnel. Als Europese bedrijven niet dezelfde urgentie tonen, zullen buitenlandse spelers de markt betreden en laten zien hoe het eigenlijk had gemoeten.Experimenteren in het bedrijfslevenVolgens Frank is experimentatie een belangrijke reden waarom veel bedrijven extreem succesvol zijn. In zijn woorden worden geweldige bedrijven gebouwd op het principe van elke dag 1% verbetering. Maar zulke consistente vooruitgang gebeurt niet toevallig. Het komt voort uit bewust testen en leren.Hij benadrukte dat bedrijven zonder experimentatie (dat kan A/B-testen zijn, het uitproberen van nieuwe functies of het optimaliseren van interne processen) niet kunnen groeien.Een goed voorbeeld hiervan is Google. Hoewel de startpagina er misschien statisch uitziet, voert het bedrijf voortdurend duizenden experimenten uit, waarbij zelfs een knop met één pixel wordt verplaatst om te zien of dit betere resultaten oplevert. Deze micro-optimalisaties, aangedreven door enorm veel verkeer en snelle testcycli, zijn een van de redenen waarom Google voorop blijft lopen.Continue optimalisatie voor aandacht en waardeIn het overvolle digitale landschap van vandaag is aandacht domineren geen kwestie van toeval. Het is het resultaat van voortdurende optimalisatie. Of een bedrijf nu B2B of B2C is, Frank gelooft dat het zich moet richten op het kruispunt tussen hun potentiële klanten en waar zij hun tijd doorbrengen. Voor de meeste professionele doelgroepen betekent dat LinkedIn.Maar welke content is het waardevolst voor hen? Dat verschilt per doelgroep. Daarom is experimenteren essentieel. Frank test zelf regelmatig verschillende soorten content om betrokkenheid te meten en zijn aanpak te verfijnen.Optimalisatie draait niet alleen om de content zelf, maar om het leren wat aanspreekt. Dat vereist dagelijks posten, idealiter één of zelfs twee keer per dag, van maandag tot vrijdag. Hoewel dit veel middelen vergt, is het gerechtvaardigd gezien het organische bereik en de merkautoriteit die het kan opleveren. Op dit moment ziet Frank AI agents nog niet in staat om de nuance of authenticiteit te leveren die nodig is voor dit soort contentstrategieën. Maar dat zou in de toekomst kunnen veranderen.Hij wees ook op de opkomst van AI-gegenereerde avatars, nep maar zeer realistische videopersona’s die al in sommige marketingcampagnes worden gebruikt. Nu AI zich verplaatst van tekst naar stem en video, ziet Frank 2025 als een keerpunt in de “videofase”. Dit jaar zullen we steeds vaker synthetische content tegenkomen die er behoorlijk realistisch uitziet. Daarom moeten bedrijven nog doordachter en strategischer zijn in hoe ze aandacht trekken en vertrouwen opbouwen.Hoewel het meeste van dit werk nog steeds afhankelijk is van wat Frank de “menselijke puf” noemt, ziet hij een groeiende rol voor AI agents in de nabije toekomst. Het hoofd van YouTube bij zijn bedrijf heeft een tool ontwikkeld die video-assets analyseert en helpt deze opnieuw te verpakken voor LinkedIn op een manier die is ontworpen om betrokkenheid te vergroten. De tool beveelt berichtformaten aan, hashtags, welke bedrijven of personen te taggen, en andere elementen die de zichtbaarheid en prestaties maximaliseren.Deze hybride aanpak, aangedreven door menselijke creativiteit en AI-gestuurde optimalisatie, kan worden gezien als de toekomst van contentstrategie. AI agents zijn nog niet klaar om mensen te vervangen bij storytelling, maar ze worden steeds vaker gebruikt om te sturen welke soorten content waarschijnlijk succesvol zullen zijn.Op basis van wat we hebben gehoord van de experts die eerder de Innovantage-podcaststudio bezochten, is deze hybride formule vandaag al goed toepasbaar op veel domeinen. AI wordt steeds volwassener en geavanceerder, maar een menselijke toets blijft essentieel.Wil je meer leren over de kracht van technologie in de zakenwereld? Mis dan de volgende afleveringen van de podcast niet.

In today's digital-first world, trust isn’t an afterthought — it’s a critical requirement. Data breaches, project failures, and inconsistent delivery have made businesses more cautious than ever about who they work with. At Sigli, we believe that trust should be built into the very core of our operations — not just our technology stack, but our team.That’s why, as of March 3rd, 2025, every new hire at Sigli will undergo a mandatory background check, powered by our new partnership with Certn.Why background checks matter in techIn many software and AI development companies, background verification is either sporadic or absent altogether. But as a partner entrusted with sensitive data, mission-critical systems, and long-term strategic initiatives, we believe clients deserve full confidence — not just in our code, but in the people behind it.Why Sigli chose CertnCertn is a globally recognized leader in background screening solutions, designed for speed, compliance, and scalability. Unlike traditional providers that rely on fragmented databases and slow turnaround times, Certn leverages AI and direct integrations with thousands of global data sources to deliver background checks that are:Fast – Most reports are completed within minutes, not days.Global – Certn covers 200+ countries and territories, enabling seamless checks for distributed and remote-first teams.Compliant – Built to comply with international standards like GDPR, SOC 2, and FCRA.Candidate-friendly – Designed to respect privacy and provide transparency during the process.By integrating Certn into our hiring flow, we ensure that our growth doesn’t compromise our standards — and that every team member is vetted with the same care, no matter where they’re located.What this means for our clientsFor our clients, this partnership represents more than a new policy. It’s a message: when you work with Sigli, you’re working with a team you can count on — not just for technical excellence, but for integrity.Sigli's clients trust us with more than just code. They trust us with business continuity, innovation pipelines, customer data, and strategic outcomes. Knowing that each Sigli team member has passed a robust, standardized verification process adds another layer of assurance — one that matters more than ever in today’s landscape.Raising the industry standardIn many ways, background checks have been overlooked in the tech sector — seen as a corporate necessity only for certain roles or industries. At Sigli, we believe that’s due for a change. High-trust partnerships require high-trust teams. And high-trust teams begin with verified people.This isn’t just a checkbox for Sigli — it’s a conscious choice to lead by example. We hope it sets a new benchmark for what clients expect, and for how companies approach growth responsibly.The bottom lineSigli is not just building AI products. Sigli is building a company where trust is engineered into every detail — from the way we code, to the way we hire.Thanks to our partnership with Certn, we’re confident we can scale that trust as we grow. Line by line. Hire by hire.

Small and mid-sized businesses often see the value of AI but struggle with knowing where to start. That’s why Sigli is hosting a free online webinar — designed specifically to help SMEs adopt AI in a practical, budget-conscious way.What You’ll Learn“The AI Profit Toolkit: Benchmarks, Playbooks, Quick Wins” is a 60-minute session packed with real-world insights, including:Realistic benchmarks from recent UK/EU use casesA six-pillar AI readiness checklistFive quick-win AI pilot ideas you can launch nowA playbook to scale from pilot to real business resultsAccess to a downloadable toolkit + full session recordingWhether you're a company owner, director, or operations lead, this session will help you take your first AI steps confidently — and profitably.“We see many businesses sitting on the AI sidelines because they’re unsure where to start,” says Max Golikov, Chief Business Development Officer at Sigli and featured webinar speaker. “This session is about showing them how to move forward with confidence and business logic.”Event Details🗓️ Date: June 4, 2025🕑 Time: 14:00 CEST / 13:00 BST📍 Location: Online (link provided upon registration)🎟️ Cost: Free👉 Reserve your spot now

Artificial intelligence is gradually transforming customer experiences and often replaces human agents in different industries. eCommerce is one of the brightest examples. But does it really mean that interaction will be fully digitalized one day? Or is there still space for human communication? These are some of the questions that the Innovantage podcast host and Sigli’s CBDO Max Golikov prepared for his new guest. In the latest podcast episode, Max had an insightful conversation with Tomer Azenkot. After starting his career in tech and product management about 20 years ago and then moving into sales leadership in enterprise software, Tomer joined Vee24 as its CEO in 2022. Vee24 is a SaaS platform that helps businesses elevate customer experience on their websites by incorporating video chat and other chat tools as part of the customer journey. Currently, the company is mostly focused on eCommerce businesses.AI chatbots and human interaction in digital commerceOver the past two years, the rise of AI chatbots and especially widely known tools like ChatGPT has significantly impacted the digital commerce landscape. A key topic of discussion today is how these tools influence the customer journey and whether they compromise the human element of the online experience.AI brings efficiency. But it can’t always replace the value of human interaction. As Tomer explained, at Vee24, they always try to identify moments within the customer journey where a personal touch is still essential. In these cases, relying solely on bots can lead to frustration. Many users still prefer to reach a real person when AI falls short.To support his words, Tomer provided a couple of real-life examples.AI is highly effective for straightforward customer needs. For instance, it is exceptionally good at checking an order status. In such cases, customers appreciate quick, automated responses. Human assistance is not needed.However, complex or emotionally driven tasks, such as choosing jewelry for your wife, require human connection. In such situations, it is still worth speaking with a knowledgeable salesperson who can offer personalized advice and even showcase products over high-definition video. This is where Vee24 entered the game by bringing the in-store experience online through real-time, human-led video interactions.According to Tomer, 90-95% of customer journeys can be handled efficiently by AI. However, the remaining scenarios, where trust, emotion, and nuanced guidance matter, still demand a human touch. Many retailers have heavily relied on AI by applying it in the wrong contexts. As a result, this has led to poor customer experiences and lost business. The key is striking the right balance between automation and human engagement.The right AI-human balanceA good example of effective AI-human integration comes from Jordan’s Furniture, a regional furniture chain in the northeastern US. They have structured their website to direct interactions based on the nature and value of the customer journey.AI chatbots handle the majority of routine, transactional tasks, like checking order status or initiating returns. They do it very efficiently. However, there is also an option to transfer the conversation to a human agent if needed. This keeps operational costs low while ensuring customer needs are met quickly.When people are looking for high-value pieces of furniture, the site connects them with a live salesperson in-store. These experts guide customers through the showroom via live video, offer personalized advice, and often successfully upsell related items, replicating the in-store experience online.Why video isn’t widely used in digital commerce todayThe limited adoption of video in online retail highlights a significant opportunity, and Vee24 is actively addressing it at the current moment. While video shopping experiences are more common in markets like the UK, where several furniture retailers already offer live video consultations, the US market has been slower in adopting this approach.One key reason is cost. Many US retailers have prioritized AI solutions to cut operational costs, often at the expense of customer experience. Hiring human agents, especially for video, is believed to be pretty expensive compared to implementing automated bots.However, data from Vee24’s customers shows that the investment pays off. Live video consultations significantly boost conversion rates and increase average order value by two to four times. For high-consideration purchases, especially in sectors like furniture, the return on investment justifies the added human involvement. Tomer shared that one of the questions that he has for Vee24’s prospective clients is “What happens when a customer walks into your physical store?”. In most cases, staff are available to guide, advise, and enhance the shopping experience. But online, many retailers expect customers to navigate complex purchases fully on their own.This disconnect is especially striking in sectors like furniture, where high-touch sales are the norm in-store. Despite the fact that eCommerce often generates a significant share of sales, retailers frequently underinvest in online human support.Tech shift in businessA decade ago, business communication relied almost entirely on audio conference bridges. Long meetings involved dialing in, entering codes, and trying to figure out who had just joined. Now, that feels outdated. Video calls have become the norm, especially following the shift driven by the COVID-19 pandemic. The same evolution is beginning to unfold in e-commerce. While text-based chat remains the default on most websites in 2025, it may soon feel just as outdated as those old phone bridges. Video is no longer a cutting-edge technology. This technology is already mature and widely accessible.What’s innovative today is not the video itself, but how platforms can integrate it into intelligent, human-centric customer journeys. That’s where the value is created.Is AI really needed for enhancing customer experiences?Tomer believes that AI adoption is far more than just hype. AI can be integrated in many practical value-driven ways. For example, AI-powered chatbots and tools can be used for sentiment analysis that helps improve customer interactions by learning from past conversations. He also mentioned that Vee24’s engineering team relies on AI to write code more efficiently, debug faster, and optimize development workflows.As it is said, in the short term, the impact of technologies is often overvalued. But in the long term, it is undervalued. Therefore, the key is using AI intentionally, not just to follow trends, but to solve real problems.The best way to introduce new technology is through structured experimentation. For example, this can be A/B testing on a website or piloting a new internal tool. By setting clear metrics and measuring outcomes, businesses can make a well-informed conclusion on whether it will be feasible to invest in the scaling of these initiatives. AI adoption: Failures and successesTomer shared that in some early chatbot deployments, results didn’t meet their initial requirements. However, the team made the required adjustments and achieved the desired improvements. The balance between AI and human agents is another area where ongoing tuning based on real-world data is essential. A recent internal success story illustrates this well. While preparing to launch its new website, Vee24 tested a generative AI website builder. For just $20 a month, the tool, driven by natural language prompts, produced an 80-90% complete site within hours. The ease of making edits, like resizing a logo with a single prompt, and the speed of iteration were eye-opening. Though not suited for complex or highly regulated sites, the solution exceeded expectations and showcased AI’s value for the right use case.Practical AI in retail: No silver bullets, just smart integrationQuick fixes through AI are largely a myth, especially in traditional retail. Many of the companies Vee24 works with are over a century old and are naturally cautious about change. These organizations often value human interaction deeply and are not quick to adopt new technology.Some businesses may initially see AI as a “silver bullet” and be ready to apply it everywhere. However, for Vee24, the real challenge is typically the opposite. The company needs to overcome resistance to change and encourage retailers to shift their mindsets. Unlike tech companies that may chase innovation aggressively, retail businesses move more slowly. They require thoughtful, well-integrated solutions rather than instant transformations.Why is it so?Tomer provided a couple of examples from his practice. Watches of Switzerland, a major retailer of luxury watches, has modernized its customer service approach over the past five years. Initially relying solely on phone and email support, the company now has dedicated video agents in both London and the US to offer live consultations online.These video interactions mirror the boutique experience by delivering personalized, high-touch service to digital shoppers. Given the high value of their products, which can exceed $100,000, the company prioritizes human interaction over automation.This approach contrasts sharply with mass-market retailers like Amazon, where AI-driven, efficiency-first models dominate.Another example that Tomer mentioned was a women’s bra company. The company was struggling with a return rate exceeding 50% and was exploring the use of live human support to complement its existing AI solution. Despite having an advanced sizing app that helps customers find the right fit using their phones, the business still faced significant returns often due to user error during the sizing process.Recognizing the limitations of AI, the company wanted to add expert human guidance to the online shopping experience. The goal wasn’t just to improve customer experience or achieve higher sales. The most important task was to reduce costly returns that threatened business sustainability.A common issue in implementing AI is the misconception that it’s a quick fix or a magical solution that will solve all problems without human input. Many businesses mistakenly assume that once AI is introduced, it will instantly deliver perfect results without the need for fine-tuning or oversight.In reality, AI may handle the first 80% of a task quickly and successfully. For example, it can generate a website in hours. However, refining that last 20% to meet specific needs often requires significant additional work.Value of human connection in salesSuccess in AI projects and modern sales is driven by a mix of clear expectations, smart implementation, strong processes, the right people, and reliable partners. AI should be seen as a tool to support (not replace) the human touch.At the heart of business success lies customer experience. People don’t just buy products. They buy from people they trust and like. A great experience builds loyalty. Quite often, it becomes even more significant than price or speed.AI plays an increasingly large role in customer journeys. However, according to Tomer, truly memorable experiences are still mainly human. No one says: “The AI experience was so great, I’m definitely coming back because of it.” Brands that prioritize meaningful human connection will always stand out.Rise of one-person unicornsWhile discussing the power of AI in the modern business world, Max also asked Tomer whether he really believes that it is possible to build a successful project valued at $1 billion without having a full-time team.Tomer explained that if the idea is compelling enough, such a scenario can become a reality. At Vee24, they have significantly reduced full-time staff and leaned into outsourcing across various functions like sales and support. Despite being external, these team members feel like part of the company.Vee24 has shut down physical offices and the entire team operates almost entirely remotely. This flexibility has helped the company cut costs and scale seamlessly. While it’s not literally a one-person business, even with outsourced talent, the structure allows it to set ambitious revenue goals.Today, there can be different approaches to building a successful company. You can hire a big team of more than 300 employees, or you can rely on international outsourcing and automation. They both have their advantages and limitations, which every funder should carefully consider.Future of customer interactionTomer predicts that businesses will become significantly smarter in their use of AI, will start deploying it more effectively, and will understand when not to use it at all. Today, many negative AI interactions stem from misuse or poor implementation. In the future, companies are expected to adopt a more strategic approach.AI is projected to become a standard component of digital customer experiences, particularly in backend operations. This includes data analysis, reporting, and customer behavior evaluation. Namely, in these areas, AI demonstrates its outstanding performance.Another growing tech trend, according to Tomer, is the use of video. He anticipates an increase in video consultations and interactions over the next five years.Tomer mentioned that one of the most overlooked technologies in today’s retail space is appointment scheduling. While it is a cornerstone of productivity in the tech and business world, its potential in commerce hasn’t been fully realized yet. In business settings, nearly everything runs through a calendar. But when it comes to our personal lives, especially how we interact with retailers, scheduling is rarely part of the process.This case reveals a significant opportunity. For example, buying a diamond isn’t something most people do impulsively. It’s a considered purchase. Scheduling a consultation and seeing it seamlessly added to your calendar, just like any important meeting, brings a sense of clarity and professionalism to the experience.Though the retail world continues to digitize, the most successful businesses will be those that blend the speed and efficiency of AI with personalized human interaction. AI has proven its power in handling routine tasks and streamlining operations. But when it comes to building trust, guiding emotional purchases, or offering expert advice, human connection remains irreplaceable.Technology is advancing fast, but the heart of great commerce is still human. That’s the main insight that Tomer shared with Max and with the entire audience of the Innovantage podcast. Want to get more insights from business experts and tech leaders? New podcast episodes will be available soon.