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Strategy

From Waiting Too Long to Moving Ahead: Why Cbw and AI Governance Need One Clear Plan

From Waiting Too Long to Moving Ahead: Why Cbw and AI Governance Need One Clear Plan

In the Netherlands, waiting until the very last moment to deal with new rules is very common. For a long time, the standard approach to IT security was simple: "They won't check us yet," or "Let's wait and see what others do." With the European NIS2 directive and the new Dutch cybersecurity law — the Cyberbeveiligingswet (Cbw) — that time is over. The laws are active, supervision is starting, and the final responsibility now sits directly with company directors and executive management. Viewing the Cbw as just a burden or a boring checklist is a mistake. At the same time, the EU AI Act and frameworks like ISO 42001 are coming at us fast. Treating these as completely separate projects will waste budget and burn out your team. The smartest move is to stop waiting and combine IT security and AI governance into one clear strategy. The Cyberbeveiligingswet (Cbw): Why Waiting Is No Longer an Option The goal of NIS2 and the Cbw is simple: raise the basic level of digital security across Europe. The old rules mostly applied to traditional vital sectors like energy and water. The new Cbw applies to many more organizations. Medium and large companies in logistics, food, chemistry, digital services, and IT providers (MSPs and MSSPs) now fall under the law. Because of this, supply chain security becomes a shared legal responsibility. Two core parts of the Cbw change how companies must operate:Duty of Care & Fast Reporting: Companies must prove they take the right technical and organizational security steps. If a major incident happens, strict rules apply: a first warning must be sent to regulators within 24 hours. Personal Board Responsibility & Mandatory Training: Directors can now be held personally responsible if they ignore basic security rules. On top of that, executives are legally required to take regular training to understand cyber risks. Leaving IT security completely to the IT department without director oversight is no longer allowed by law.BIO2 Becomes Law: Your Foundation Is Already There For Dutch government bodies and their IT suppliers, an important change is happening. The Baseline Informatiebeveiliging Overheid (BIO2) is moving from a voluntary framework to a binding law under the Cyberbeveiligingsbesluit. While many organizations worry about this, the truth is that BIO2 gives you a solid foundation you might already own. It builds on well-known global standards:ISO/IEC 27001: The process foundation for security management (ISMS). It sets up risk checks, policies, and continuous improvement. CIS Controls: The practical, technical checklist. Where ISO tells you what goals to reach, CIS Controls give you a concrete list of actions (device management, multi-factor authentication, logging, and endpoint protection).If your organization already works with ISO 27001 or BIO2, you already cover most of the technical requirements of the Cbw. The AI Side: Don't Build Another Separate Project At the same time, company boards are hearing about the EU AI Act and ISO 42001 (the standard for Artificial Intelligence management). The usual reaction is to push AI away: "Let's finish the Cbw project first. We will worry about AI in a few years." This is a missed opportunity. If you compare BIO2 and ISO 27001 with ISO 42001, you see something interesting: a company running a good ISO 27001 or BIO2 setup already covers 70% to 80% of what ISO 42001 requires. That is because AI management uses the exact same basics as normal IT security: risk checks, data rules, access management, supplier controls, and incident handling. You do not need to build a whole new management system. The Specific "AI Gap" The remaining 20% to 30% gap is very specific:AI Ethics & Fairness: Making sure algorithms work fairly without discrimination. Explanation & Human Control: Understanding how an AI tool reaches a decision and keeping a human in control (human-in-the-loop). Impact on People: Checking how the AI tool affects employees, customers, and privacy. AI Lifecycle Management: Checking data quality and monitoring if the AI model changes over time (data drift). AI Incident Handling: Preparing for new threats like prompt injection or accidental data leaks through AI tools.These extra steps are not a new system; they are just a direct addition to your current IT security setup. One Integrated Plan: Build It Once The AI Act timeline moves forward regardless of your Cbw deadlines. Companies that treat these things as three separate projects — one for Cbw, one for ISO 27001, and one for AI — will pay three times as much for the same result. The practical order to follow is: BIO2 / ISO 27001 Foundation ➡️ CIS Controls (Technical Setup) ➡️ ISO 42001 (AI Extension) Practical Steps to TakeCombine Risk Checks: Add AI tools and algorithms directly to your existing risk lists in your security management system. Use Clear Technical Rules: Use CIS Controls to secure your cloud environments (like Microsoft Azure) to meet the requirements for both Cbw and ISO standards. Extend Your Security Policies: Add the specific ISO 42001 points for AI ethics and control directly into your daily processes. Train the Board: Combine the required Cbw training for directors with a practical update on AI risks and opportunities.Closing Thoughts Putting off rules and regulations until the last minute no longer works. The Cyberbeveiligingswet, mandatory BIO2 rules, and the EU AI Act mean that IT security and AI are now direct topics for company leadership. Instead of running separate compliance projects, combining these standards into one clear plan turns a legal obligation into a practical advantage. You protect directors from liability, remain a trustworthy partner in your supply chain, and build a safe foundation to use AI effectively in your business.

The executive prompt playbook: Mastering context, techniques, and multi-agent AI

The executive prompt playbook: Mastering context, techniques, and multi-agent AI

Many business leaders still view prompt engineering as a technical trick reserved for IT departments or junior analysts. They open a chat interface, type a vague question like "Draft a strategy for market expansion," and end up disappointed by a generic, middle-of-the-road answer. They assume the technology is overhyped, close the tab, and go back to traditional ways of working. This misses the fundamental nature of modern artificial intelligence. Prompting an AI model is not like typing a query into a search engine; it is an exercise in strategic delegation. If you give a brilliant human executive assistant a vague instruction without background information, you will receive a superficial result. But if you give that same assistant a clear strategic context, defined boundaries, and explicit expectations, you receive executive-grade work. The same principle applies to AI. For a modern board member or director, learning how to frame prompts, apply proven cognitive techniques, and structure multi-agent workflows is becoming a core leadership capability. The architecture of an executive prompt: Context and framing The single biggest mistake executives make with AI is omitting context. Large language models are designed to predict plausible text based on probabilities. Without specific framing, the model defaults to the average corporate jargon found across the open internet. To get sharp, actionable insights, you must anchor the AI inside your specific business reality. A high-performing executive prompt consists of five essential structural blocks: Role, Context, Task, Constraints, and Output Format. First, you establish the Role by telling the AI who it is supposed to be. Second, you provide the Context, explaining the background, market situation, or internal pressures surrounding the issue. Third, you define the Task with absolute clarity. Fourth, you set strict Constraints, specifying what the AI must avoid, what assumptions it must challenge, or what regulatory rules it must respect. Finally, you specify the Output Format, such as a structured memo or a risk matrix. [ROLE] Act as a conservative M&A advisor specializing in European industrial manufacturing.[CONTEXT] Our company is a mid-sized Dutch manufacturer ($150M revenue) considering acquiring a German competitor with strong software capabilities ($30M revenue). Our board is risk-averse, highly protective of existing cash flow, and concerned about cultural integration and hidden software maintenance debt.[TASK] Review the attached summary financial report and technical audit. Identify the top three strategic and operational risks associated with this acquisition.[CONSTRAINTS] Do not summarize the general benefits of M&A. Focus strictly on potential failure points. Assume interest rates will remain elevated over the next 36 months.[OUTPUT FORMAT] Provide a 1-page executive memo organized into three sections: Key Risk, Operational Impact, and Recommended Mitigation.Essential prompt techniques for executive decision-making Beyond basic prompt structure, executives can draw on specific prompt techniques to unlock far deeper strategic reasoning from AI systems. 1. Role-Based Prompting (Persona Framing) Instead of asking for general advice, you force the AI to look at a problem through a specific expert lens. By asking the system to evaluate a proposal as a skeptical activist investor, a strict compliance officer, or a disruptive tech founder, you quickly surface blind spots that a single perspective would miss. Act as a skeptical activist investor who has just taken a 5% stake in our company. Read our proposed three-year digital transformation roadmap attached below. Identify three initiatives in this roadmap that appear over-budgeted, unnecessary, or unlikely to deliver clear ROI within 18 months. Challenge our leadership assumptions aggressively, using concise, direct executive language.2. Chain-of-Thought (CoT) Prompting AI models perform significantly better when forced to explain their reasoning step-by-step before delivering a final answer. If you ask a complex strategic question directly, the model might rush to an oversimplified conclusion. By instructing the model to work through the logic systematically, you force higher decision quality. We are considering shifting our enterprise software pricing from a traditional fixed seat-based model to a usage-based consumption model. Before giving me your final recommendation, work through this decision step-by-step: 1. Analyze the immediate cash flow risks during the transition phase. 2. Evaluate how our sales compensation structure needs to adapt. 3. Assess customer retention risks among our largest conservative enterprise accounts. 4. Weigh the long-term upside against these operational hurdles.Show your reasoning for each step clearly before providing a final executive summary recommendation.3. Few-Shot Prompting (Learning by Example) If you want the AI to draft a strategic document, do not just describe the format—provide one or two examples of actual memos that reflect your preferred executive style. By showing the model what excellent work looks like in your company, the AI immediately matches the desired tone, structure, and depth. I need you to write a brief strategic update for our advisory board regarding our AI adoption policy. Below are two examples of previous memos I wrote that the board praised for their clarity, direct tone, and bulleted risk focus.---EXAMPLE 1--- [Insert past memo text here] ---END EXAMPLE 1------EXAMPLE 2--- [Insert past memo text here] ---END EXAMPLE 2---Draft a new memo regarding our proposed internal policy on employee use of generative AI tools. Mirror the exact tone, paragraph length, and bullet-point structure of the examples above.4. Meta-Prompting (Socratic Alignment) When facing a complex scenario where you are not even sure what questions to ask, you can instruct the AI to interview you first. This turns the AI into a thought partner that helps you clarify your own thinking before generating a single line of strategy. I need to draft a comprehensive AI governance framework for our healthcare organization, but the parameters are complex and I want to ensure we do not miss key operational details. Do not generate the framework yet. Instead, act as an expert risk management consultant and ask me 5 targeted questions, one at a time, about our current infrastructure, data privacy controls, and risk tolerance. Wait for my answer after each question before asking the next one. Once we finish all 5 questions, synthesize my answers into the final governance draft.Advanced techniques for complex strategic scenarios As executives deal with higher levels of business complexity, more advanced prompt techniques become necessary. 5. Generated Knowledge Prompting Before asking the AI to make a strategic judgment, you instruct the system to articulate and list key domain facts, regulatory constraints, and market truths first. This ensures the AI grounds its final recommendation on accurate underlying knowledge rather than high-level speculation. First, list the top five regulatory requirements under the European Union AI Act that specifically apply to automated risk-assessment software in financial services. Second, based strictly on those regulatory facts you just generated, evaluate our proposed AI credit-scoring workflow attached below and highlight where we are non-compliant.6. Tree of Thoughts (Scenario Branching) When evaluating major strategic crossroads, you can instruct the AI to explore multiple decision paths simultaneously, evaluate the failure points of each branch, and compare the outcomes before selecting the strongest path forward. Our logistics company is facing a 25% rise in fuel and operational costs. I want you to evaluate three distinct strategic responses: - Option A: Pass 100% of the cost increases directly to customers through a fuel surcharge. - Option B: Absorb the costs short-term while aggressively automating route planning to reduce total mileage by 15%. - Option C: Restructure customer contracts around longer delivery windows in exchange for fixed pricing.For each option, generate two potential downstream consequences (one positive, one negative). Then, evaluate which path offers the best balance of customer retention and margin protection over a 24-month horizon.7. Directional Stimulus Prompting This technique involves giving the AI explicit strategic anchors, keywords, or core themes to guide its analytical focus. It prevents the model from wandering into irrelevant topics and keeps the analysis tied directly to leadership priorities. Analyze our quarterly operational performance report. In your analysis, focus strictly through the following strategic anchors: [Cost Efficiency], [Supply Chain Volatility], and [Key Person Dependency]. Ignore general marketing or sales metrics. Provide a brief assessment explaining how our current performance impacts each of these three strategic anchors.Beyond single prompts: Orchestrating a multi-agent council While individual prompt techniques are powerful, the ultimate revolution in executive decision-making lies in multi-agent architecture. Instead of relying on one AI model to perform every task, you design a digital council of specialized AI agents, where each agent has a distinct role, personality, and set of responsibilities. In a multi-agent setup, the human executive moves from being the writer or analyst to becoming the chairman of the digital board. You set the agenda, monitor the debate between specialized agents, intervene when the discussion strays off course, and make the ultimate human decision based on synthesized insights. Act as the Chairman of an AI Advisory Board evaluating our entry into the US healthcare market. You will simulate a debate between three specialized board members before providing a final synthesis.Step 1: Have [Agent A: Chief Strategy Officer] present a 2-paragraph expansion argument focused on market size and revenue growth. Step 2: Have [Agent B: Chief Risk Officer] challenge Agent A's plan, pointing out three critical regulatory and legal hurdles in the US healthcare landscape. Step 3: Have [Agent C: CFO] analyze the financial trade-offs between both perspectives, focusing on cash burn and payback timelines. Step 4: As Chairman, summarize the core points of debate, resolve the conflicts between the agents, and present a final executive decision brief for the CEO.The executive mindset shift Mastering these techniques requires a fundamental mindset shift. You must stop viewing AI as an automated search box and start treating it as a team of highly capable, hyper-fast advisers who know nothing about your company until you brief them properly. The quality of the output you receive from AI is a direct reflection of the clarity of your own leadership. If your instructions are confused, your context is weak, and your boundaries are vague, the AI will return confusing, weak, and vague results. But when you master the art of framing, provide rich context, and orchestrate specialized agents, AI becomes an incredible lever for executive productivity and decision speed. Closing thought Technology will not replace strategic leadership, but leaders who know how to direct AI will rapidly replace those who do not. The goal of prompt engineering for executives is not to turn managers into programmers. It is about learning how to communicate intent, set clear boundaries, and demand rigorous thinking from digital systems. Stop asking AI for quick answers. Start giving it the strategic context it needs to deliver real executive value.

Strategy is for decision-making. Marketing is for storytelling.

Strategy is for decision-making. Marketing is for storytelling.

Organizations spend an extraordinary amount of time defining their vision, mission, purpose and values. Workshops are organized. Consultants are hired. Leadership teams debate every word. Marketing departments create beautiful presentations. Posters appear on office walls. And then, on Monday morning, nothing changes. Not because the strategy was poorly communicated. But because it was never designed to help people make decisions in the first place. Too often, organizations treat strategy as a communication tool. I believe it should be treated as a governance tool. The day I realized we were solving the wrong problem Not long ago, I was part of a leadership team redefining the identity of a growing IT services company. The ambition was clear. We wanted to define who we were, what we stood for, and where we wanted to go. Something people could genuinely recognize themselves in. Something that would unite the organization as it continued to grow. At least, that was my expectation. Instead, the conversation quickly became familiar. Customer intimacy. Innovation. Competitive pricing. Quality. The kinds of phrases every organization seems to use because nobody can reasonably disagree with them. None of them were wrong. But I kept asking myself a simple question. What will we do differently on Monday because of this? Nobody seemed able to answer. And that was the moment I realized we weren't creating a strategy. We were creating marketing. A strategy should answer questions before they're asked As organizations grow, decisions become increasingly decentralized.Recruiters hire people they've never worked with. Sales teams negotiate deals without involving the board. Architects design solutions independently. Product managers decide what gets built next. Marketing teams position the company every single day.The larger the organization becomes, the less practical it is for leadership to approve every decision. That is precisely why strategy exists. Not to inspire people. Not to impress customers. Not to look good on a website. But to ensure that hundreds of people make decisions that move in the same direction. A good strategy reduces uncertainty. It doesn't create it. Every strategic principle should have consequences Words like innovation, quality and customer intimacy sound impressive. But they only become meaningful when they influence behavior. Imagine a customer asks for a highly customized solution. Do we build it? The answer shouldn't depend on who happens to be leading the meeting. It should already be implied by the strategic framework. A recruiter finds an exceptional engineer. Technically brilliant. But unlikely to thrive within the organization's culture. Do we hire them? Again, the answer shouldn't require executive intervention. Marketing wants to launch a new campaign. Should we position ourselves as the cheapest provider? The premium specialist? The safest choice? The most innovative? If your strategy doesn't make that decision easier, what exactly is it for? Every strategic principle should eliminate options. If it doesn't help people decide what not to do, it isn't providing direction. Growth demands autonomy When organizations have fifty or a hundred employees, many decisions still happen organically. People know each other. Leadership is accessible. Context spreads through conversation. But as organizations scale, that changes. Information becomes fragmented. Teams specialize. Decision-making becomes distributed. You cannot build a thousand-person organization where every important decision depends on a handful of executives. Nor should you want to. Growth requires autonomy. But autonomy without direction creates inconsistency. That's where strategy becomes essential. Not because larger organizations need more slogans. But because they need better decision-making frameworks. Strategy should reduce debate, not create it One of the simplest ways to test whether a strategic framework works is to observe what happens during disagreement. Imagine a discussion about building custom software for an important customer. If the room immediately splits into opposing opinions, and the only way to resolve the discussion is by asking senior leadership... ...your strategy has already failed. A strong strategic framework should settle many of those discussions before they even begin. Not because it provides answers to every situation. But because it establishes principles that people trust when making difficult trade-offs. The best strategies don't eliminate judgment. They improve it. Storytelling still matters None of this means communication is unimportant. Quite the opposite. Organizations absolutely need stories. Stories create identity. They build culture. They attract customers. They help people feel connected to something larger than themselves. But stories should explain strategy. They should never replace it. Marketing tells people what the organization believes. Strategy determines what the organization actually does. Confusing those two is where many organizations lose their way. The real test The effectiveness of a strategy isn't measured during an annual kick-off. It isn't measured by how many employees can recite the mission statement. And it certainly isn't measured by how attractive it looks on a slide. It's measured in ordinary moments.A salesperson deciding whether to accept a customer. An architect deciding whether to build custom functionality. A recruiter choosing between two candidates. A product team deciding what not to build.Those are the moments where strategy either exists... ...or it doesn't. Closing thought I've seen organizations spend months debating the difference between a vision, a mission, a purpose and a set of values. Ironically, none of those discussions improved a single decision. Because the names don't matter. Whether you call it a strategy, a vision, a purpose or a strategic framework is largely irrelevant. The only question that matters is this: Does it help people make better decisions without asking for permission? If the answer is yes, you've built something that can genuinely guide an organization. If the answer is no... ...you've probably written excellent marketing copy.