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Your banking app has already completely transformed everyday banking. The next shift’s even bigger—banking that feels like a conversation. At the end of April, just a few days before becoming CEO of Belfius, we engaged with Olivier Onclin to unpack what it truly takes to move from traditional digital channels to conversational AI, and why the "wow" factor only matters if the underlying processes are rebuilt end to end.

We get practical about how AI in banking has evolved over decades, from scripted automated decision making in credit models to compliance automation, and now to large language models that can reshape the client experience. Olivier explains why efficiency and customer experience are tightly linked, why the talent challenge is real even for well-prepared organisations, and why late starters still need to jump in quickly while treating AI as a management journey, not a plug-in tool.

Next, we explore trust in AI. Olivier breaks it down into four clear dimensions: transparency (people should know they're talking to a machine), security (including cybersecurity for consumers), a human layer (AI cannot replace basic humanity), and sovereignty. When it comes to sovereignty, we discuss European AI and why Belfius favours European providers when performance is comparable, including a partnership with Mistral, alongside the broader need for resilient infrastructure and cooperation across European players.

We also tackle the uncomfortable topic of ROI. If the best transformations can take seven to ten years to pay back, how do leaders justify AI investments in uncertain times and short reporting cycles? If you care about digital transformation, AI governance, cybersecurity, and the future of customer experience in financial services, this conversation will provide a sharp framework and real-world constraints.

If this episode has sparked new ideas on conversational banking, AI governance, and responsible AI in your organisation, subscribe, share it, and leave a review.

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Energy independence is no longer an abstract policy goal when your region imports most of its oil and gas and global tensions spike prices overnight. We sat down with Grégoire Dallemagne, CEO of Luminus, one of Belgium’s largest electricity producers and energy suppliers, to talk about the fastest path to lower emissions and stronger sovereignty—electrification. We walk through the simple physics behind electrification, from why electric vehicles use far less energy per mile than thermal cars to why heat pumps outperform gas boilers, and how shifting more of daily life to electricity can shrink total energy demand.

Then we get practical about AI. Electrification sounds straightforward until you look at what it does to the grid and to customer expectations—smart metres create real-time energy data, renewables add weather-driven variability, and people want prices and guidance that match the moment. We unpack how Luminus uses AI and machine learning for renewable energy forecasting, how smarter models help integrate wind and solar into the electricity system, and how AI-enabled tools support flexibility like smart EV charging that’s cheaper for customers and healthier for the network.

We also tackle the tough questions. AI uses electricity, so when is it worth it and how do you keep “garbage in, garbage out” from undermining results? Grégoire explains why solid processes and data governance matter, how internal AI governance supports safe adoption, and why the standard for customer experience is rising fast with large language models (LLMs). If you care about AI in energy, the Belgium energy market, grid flexibility, or the future of electrification in Europe, this conversation gives you a grounded, operator’s view. Subscribe, share with a friend in energy or tech, and leave a review with your biggest question about electrification and AI.

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AI’s finally crossing the line from demos to day-to-day work, and the hardest part isn’t the model, it’s the operating system around it. We sit down with Claudia Max, Regional CEO of Allianz Benelux, to get specific about how a major insurer approaches AI implementation across core processes like claims, underwriting, and operations while keeping trust and data protection at the core.

We talk about the shift from scattered proofs of concept to scaling real capabilities, including voice bots and enterprise knowledge assistants that help employees find accurate client and customer information faster. Claudia shares how Allianz builds a practical map of customer journeys, then identifies where AI agents can improve coverage checks, decision quality, and service speed. The big takeaway—generative AI creates the most value when it forces you to rethink the journey, not just automate a step.

Because insurance runs on trust, we also get into governance and responsible AI—group-wide frameworks, local transformation teams, AI ambassadors in each department, and the non-negotiables like human-in-the-loop decision making and transparency. We cover the messy reality of vendor selection in a fast-moving market, plus why many leaders “see AI everywhere except in the P&L” and what to measure as adoption grows.

If you’re building an AI strategy for a regulated enterprise, this conversation offers a grounded playbook for AI adoption, AI governance, workforce AI training, and customer experience improvements without losing control. Subscribe, share this with a colleague, and leave a review with the one AI challenge you want us to tackle next.

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Tired of hearing about "AI transformation" without seeing a clear path to implementation? This discussion takes a different turn. It sets the essential groundwork that makes AI truly effective in insurance. We engage with Heidi Delobelle, CEO of AG Insurance, Belgium's oldest and leading insurer, to explore how AI has been integrated into daily operations while remaining reliable, secure, and transparent.

We focus on where the real value materialises. Heidi reveals that a successful AI strategy goes beyond cost savings to enhance customer experience, streamline distribution, and bolster employee support. We explore hybrid service models in which digital channels manage routine tasks, leaving humans to handle critical interactions. We also delve into how AI and data are reshaping call centres, moving past "press 1" menus to provide agents with real customer insights, enabling quicker and higher-quality resolutions.

Next, we examine the foundations and risks of AI. Clean data, a unified customer view, a shared sandbox, and central standards prevent chaotic tech and help mitigate AI risks. Heidi highlights the importance of governance, cybersecurity, bias checks, and human oversight for significant decisions and external communications. You'll also hear about a specific use case where AI reduces SME underwriting research from days to minutes, freeing up capacity for growth, along with a five-year perspective on claims automation and prevention-focused insurance.

If this conversation has sparked new ideas on applying generative AI, data governance, and responsible AI in your organisation, subscribe, share the episode and leave a review.

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Welcome to a special episode of AI Unscripted, recorded during our recent strategy session in Antwerp. This conversation brings together leading voices to explore the urgency, risks, and opportunities of the AI revolution—and what it means for your business, your teams, and the future of work.

Panelists Xavier Verhaeghe, Rik Vera, Joris Van Der Gucht and Prof. Dr. Ann Nowé draw compelling parallels between the current AI wave and the early days of the internet, noting that AI is an active, rapidly evolving tool that demands swift action from organisations. Unlike previous technological shifts, AI’s accessibility allows even small teams to build impactful products quickly, reducing barriers to innovation and enabling a new generation of creators.

The discussion highlights the importance of responsible AI adoption, focusing on transparency, explainability, and the need for interdisciplinary collaboration. Social scientists and technologists are working together to address bias and make sure AI aligns with human values. Human input remains essential, guiding AI systems and validating their outcomes, especially as large language models become more prevalent in business and daily life.

Real-world examples showcase how AI’s reshaping industries, from gaming—where AI enhances user engagement—to professional services—where clients increasingly seek validation of AI-generated advice. The panel acknowledged the unpredictable pace of AI’s evolution, urging leaders to foster a growth mindset and embrace experimentation.

Ultimately, the session underscores the critical role of leadership in navigating AI-driven change. Storytelling, vision, and engagement are key to overcoming resistance and making sure organisations thrive ethically and responsibly in the age of AI.

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What does it take to reinvent a bank for the AI era? In this episode, we sit down with Johan Thijs, CEO of KBC Group, who shares how his background in applied mathematics and actuarial science shaped a bold, data-driven strategy for one of Europe’s leading financial institutions.

Johan explains how KBC’s virtual assistant, Kate, was designed to proactively solve customer problems, not just answer questions. The goal: zero hassle, zero friction, and instant solutions—like blocking a lost credit card and issuing a new one in minutes, all without human intervention. He demystifies the investment behind Kate, clarifying that the real cost lies in the infrastructure, not the AI itself, and shares how initial skepticism from staff gave way to widespread adoption as the benefits became clear.

We challenge the common view that AI is just for back-office efficiency. Johan argues that starting with customer-facing solutions delivers the biggest impact, and that KBC’s approach—using AI first to drive sales and value—helped secure buy-in and measurable returns. He warns that Europe risks falling behind global tech giants unless it gets smarter about data sharing and regulation and stresses the importance of trust: KBC never sells customer data, using it only to personalize and anticipate needs.

Johan also shares his optimism for the future, urging everyone to keep learning as AI reshapes cognitive work. He highlights KBC’s internal AI-powered training platform, Stipple, which helps staff match their skills to future roles. The episode closes with practical advice: focus on customer needs, adapt as technology evolves, and embrace the blend of human and machine intelligence. If you want to see how AI can transform not just processes but the entire customer experience, this conversation is essential for listening.

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What if the quickest route to AI success isn't about building new systems. We sit down with Thierry Geerts, CEO of Beci, Brussels Chamber of Commerce and former Google Belgium director, to explore why small businesses in Brussels might be better placed than large corporations to harness AI's potential right now. Thierry argues convincingly for practical use over invention, suggesting that the region's high wages and pragmatic talent make ready-made AI tools a strategic advantage.

We challenge the myths surrounding AI-driven job loss and examine the Brussels labour market with fresh data. Thierry reveals how his team used AI to uncover around 100,000 open positions—showing that the job gap is more about discovery and matching than scarcity. From automated translation that prepares businesses for export to AI copilots enhancing customer relationships, he explains how leaders should view AI as an opportunity first, then a tool for efficiency. The key is adoption: empower your team, redesign workflows, and measure the gains so that time saved translates into value created.

Thierry also introduces Homo Digitalis, a mindset recognising that employees already engage with AI in their personal lives. Companies that restrict tools at work create a cultural mismatch and lose momentum. We discuss what Belgium needs next — not another hype cycle, but a clear AI master plan connecting universities, policy, and businesses for long-term value. Looking five years ahead, AI should feel as familiar as your smartphone—some teams will lead because they started small, learned quickly, and expanded what worked. If you're seeking a plan that's grounded, measurable, and human-centred, this conversation is your guide.

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While skepticism often grabs attention, data may reveal a different narrative. A select group of companies is already harnessing AI to create tangible business value. We delve into new survey insights with Xavier Verhaeghe to explore why these companies are leading, how they organise their initiatives, and what it takes to transition from isolated trials to significant results. The key is clear: view AI as a transformative force, not just a tool.

We outline the strategies successful leaders employ. It begins with a compelling "why" linked to enhancing customer experience and boosting revenue, rather than merely cutting costs. Next is targeted execution: choose a few high-impact processes, redesign them comprehensively, and safeguard resources with a dedicated transformation office.

Looking forward, agentic AI is already in use for specific applications, moving from "human in the loop" to human oversight, with agents monitoring agents for quality. This shift challenges leaders to rethink governance, monitoring, and risk management. It also transforms talent. Generalists, armed with AI, can now provide value previously reserved for experts. Boards that move past headlines to genuine urgency invest in reskilling, redefine roles, and align AI with strategic goals.

Looking to refine your plan—focus deeply on fewer initiatives, measure outcomes that matter to customers, and align business and AI leadership? This discussion offers a clear starting point and practical guidance. Subscribe, share with a colleague responsible for a key process, and leave a review with the one process you'd transform first.

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