5 hard truths about implementing AI into your business

In the heart of Ghent, at Plectrum, a group of executives, strategists, and AI experts gathered for a conversation that felt different.  

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The AI Strategy Masterclass, led by Peter Hinssen and Mieke De Ketelaere, wasn’t about AI hype or abstract theories. It was about what’s happening now, and the decisions leaders need to make before it’s too late.

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AI is moving fast. Faster than most businesses can keep up with. And if there was one thing everyone in that room understood by the end of the day, it was this:

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You can’t afford to sit back and “see what happens.”

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Peter Hinssen and Mieke De Ketelaere led the discussion with a mix of hard-hitting insights and hands-on examples, showing how AI is already reshaping industries, forcing new business models, and redefining leadership itself.

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Here are the 10 biggest takeaways from the day, with all the real examples, candid discussions, and uncomfortable truths that came up in that room.

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1. AI Moves Too Fast for a “Wait-and-See” Approach

Every morning, something new happens in AI. Every week, an entire industry shifts. It’s relentless.

"I wake up, check my phone, and think—what the hell happened overnight?" - Peter Hinssen

That wasn’t an exaggeration. It was the reality we’re all living in. OpenAI, DeepMind, Anthropic, and a dozen startups you’ve never heard of are pushing AI forward at an insane speed. If your company is still “experimenting” with AI, you're already behind.

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Belfius Bank understood this early. They didn’t wait for AI to prove itself. Instead, they invested aggressively, not just in banking applications, but in AI-powered healthcare and insurance innovation.

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Between 2017 and 2022, burnout cases in Belgium rose by 43%, and 90% of employees now expect companies to play a role in workplace wellbeing.

So what did Belfius do?

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They partnered with Alan, integrating AI-driven mental health and wellbeing solutions into their corporate insurance offerings. Employees covered by Belfius now have:

• AI-powered virtual health support, including teleconsultations with doctors and psychologists.

• Personalized prevention plans that adjust based on individual health data.

• Faster reimbursements processed entirely by AI.

This is AI actively solving a workforce problem that affects business productivity, absenteeism, and retention.

That’s the mindset that wins. AI isn’t a side project. It’s a core business decision that leaders need to make now.

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2. Data-Tracking Isn’t the Same as AI-Driven Decision-Making

Most companies think they’re data-driven. They have dashboards, reports, and analytics. But tracking data isn’t the same as letting AI make decisions.

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Mechelen Media House figured this out the hard way. They used to base publishing and subscription models on historical trends and editorial judgment. That worked, until AI-powered competitors started using real-time AI insights to make decisions instantly.

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So, they adapted:

🔹 AI now determines the best time to publish for maximum audience engagement.

🔹 AI identifies which articles should be paywalled based on live user behavior.

🔹 AI flags subscribers likely to cancel and automatically triggers retention campaigns.

That’s AI making business decisions.

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"We have more information than ever before, but less time to act on it. AI changes that." - Peter Hinssen

3. AI Is Replacing Jobs (But Not How You Think)

The conversation about AI and jobs is often framed in extremes—either complete automation or minimal impact. The truth, as discussed in the Masterclass, is far more nuanced:

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AI won’t replace humans. Humans using AI will replace humans who don’t.

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Peter Hinssen emphasized this shift:

‍"Maybe only 10% of jobs will disappear, but 100% of jobs will change."

That’s not speculation, it’s already happening.

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How AI Is Reshaping High-Skill Professions

One of the most striking examples discussed was the legal industry. Every major law firm is now integrating AI-powered legal assistants like Harvey, an AI trained on legal case law, contracts, and compliance regulation.

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Before AI :

🔹 Junior lawyers spent hours reviewing contracts, searching for key clauses, risks, and compliance issues.

🔹 Document review was slow, repetitive, and costly.

🔹 High-value legal strategy took a backseat to administrative work.

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After AI :

🔹 AI scans entire contracts in seconds, flagging risks and highlighting critical terms.

🔹 AI suggests case law precedents to strengthen legal arguments.

🔹 Junior lawyers now focus on client strategy and courtroom preparation—not admin work.

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And it’s not just law.

🔹 Novo Nordisk replaced a 50-person team of clinical report writers with just 3 AI-assisted experts to streamline drug approval documents.

🔹 Microsoft’s Dragon Co-Pilot for Doctors listens to patient consultations and automatically generates medical notes, reducing admin time for physicians.

🔹Belfius is embedding AI into its insurance operations, automating claims processing and predictive risk assessments.

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If AI isn’t integrated into your long-term workforce strategy, your company isn’t future-proofing, it’s stalling.

4. AI Won’t Save You from Bad Processes, It Will Expose Them

Most businesses assume AI will fix inefficiencies, but in reality, it often highlights just how broken internal communication is.

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In Mieke De Ketelaere’s Duckworks workshop, teams were divided into different business roles—sales, project management, and developers.  

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Each group had to build a product (represented by ducks) based on information.

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🔹 Sales gathered market insights but had no way to communicate them accurately.
🔹 Project managers interpreted those insights but often misunderstood what was actually needed.
🔹 Developers built the product—but by the time it reached sales, it was misaligned with what customers wanted.

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Sound familiar?

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This exercise mirrored real-world AI adoption struggles. Companies invest in AI tools but fail to integrate them into decision-making processes.

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Mieke observed this pattern across multiple industries: ‍

"Technical teams build AI solutions, but the business side doesn’t fully understand or use them. Meanwhile, leadership expects AI-driven growth but hasn’t aligned departments on how to implement it."  

Executives often think the problem is the AI itself—but the real issue is that their organization isn’t designed for AI-driven workflows.

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5. The AI Buy vs. Build Dilemma

One of the most strategic challenges C-level executives face today is whether to build AI solutions in-house or buy off-the-shelf AI products.

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Mieke emphasized how the landscape is shifting rapidly, making this decision more complex than ever.

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"The challenge today isn’t just AI itself. It’s knowing where to invest. Every vendor is adding AI features, and every startup is offering AI solutions. So, do you build or do you buy?"  

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This isn’t a simple question. Many companies fall into two traps:

1. Buying AI solutions without understanding how they work, leading to dependency on external vendors.

2. Trying to build AI entirely in-house, only to struggle with expertise gaps and slow execution.

Mieke’s Solution: The Hybrid AI Strategy

Mieke advised executives to keep their options open and always invest in some internal AI capacity.

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Why? Because companies that at least experiment with building AI develop:
✅ Better negotiation power with AI vendors.
✅ Deeper understanding of trade-offs in AI adoption.
✅ More control over data security and compliance.

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Example: The AI Feature Boom ‍

Right now, every major software vendor is adding AI-powered features, from SAP to Salesforce.

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🔹 If you don’t understand AI’s mechanics, you’ll overpay for basic AI automation.

🔹 If you rely only on vendors, you’ll struggle to integrate AI across your systems.

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The companies that thrive will be those that balance building AI in-house while leveraging external tools strategically.

Mieke’s advice:

"You don’t have to build everything, but you do need to build enough to know what you’re buying."  

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Takeaways :

🔹 Don’t just trust AI vendor sales pitches, understand how AI models actually work.

🔹 Invest in a small internal AI team to test, validate, and challenge external AI offerings.

🔹 Balance speed with control. Some AI needs to be built internally, while other solutions can be outsourced.

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This buy vs. build challenge is now one of the most critical AI leadership decisions.

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This masterclass helped us realise that AI isn’t a future problem, it’s a leadership decision happening now.

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