Based on expert discussions and intelligence insights
By Benoît Grenier
Strategic Advisor — Intelligence, Risk Management & Counter-Espionage
PART II
Ten Essential Questions Every CEO Must Ask AI — and Themselves — Now
The collapse of informational certainty and the geopolitical turbulence described in the previous part inevitably raise a deeper issue: how can executives make decisions in a world where data is unstable, identities are synthetic, and markets are shaped by forces that traditional business analytics cannot detect? The answer is not to abandon AI. It is to transform the way leaders engage with it. The companies that will dominate the next decade are those that know what to ask, what to validate, and what to challenge.
AI is not an oracle. It is a powerful interrogative engine. Its value lies not in the raw answers it provides, but in the quality of the questions that executives use to interrogate it. In the intelligence world, the strongest advantage is not information itself but the ability to ask the questions that reveal risk before risk becomes visible. This is why the next decade of corporate leadership will be defined by CEOs who develop an intelligence mindset—leaders who treat AI not as a magic box but as an instrument of strategic probing.
Based on the insights with my friends and the evolving geopolitical context, the following questions represent the core of that new executive discipline. Each one exposes vulnerabilities, blind spots, or emerging opportunities that traditional dashboards, market reports, or corporate KPIs simply cannot reveal. The purpose is not to seek answers that are final, but to stimulate ongoing intelligence cycles inside the organization. These questions, when integrated into a continuous analytic process, create the foundation for what enterprises urgently need: a living risk architecture.
1. What geopolitical shifts outside my industry could alter my economic exposure within the next 18 to 36 months?
Most executives monitor risks that occur inside their sector. Few monitor the geopolitical and macroeconomic tensions happening around it. Yet the world no longer respects such boundaries. A conflict in the Red Sea affects shipping costs in Europe. A rare-earth export restriction in Asia affects manufacturing in North America. A financial sanction imposed by Washington or Brussels instantly reverberates through entire supply chains.
AI, when properly configured with validated data, can scan these global patterns at a scale no human team can match. But the key is to ask the model to identify indirect and lagging risks, not just immediate disruptions. Executives who ask this question gain early visibility on vulnerabilities that competitors will only see once the damage is already done. In an era of economic warfare, this kind of anticipatory insight becomes a competitive shield. AI does not replace geopolitical expertise, but it extends its reach and amplifies its depth.
2. Which parts of my organization are most susceptible to synthetic data manipulation, deepfake impersonation, or AI-driven fraud?
According to me, It is clear that synthetic personas, fake accounts, and AI-generated identities will soon dominate the digital ecosystem.
For organizations, the risk is not abstract. It affects HR (fake candidates), procurement (fake vendors), finance (fraudulent invoices), customer service (synthetic complaints), and cybersecurity (identity spoofing). The executive question here is not whether the organization will be targeted—it already is—but which entry points have the weakest validation mechanisms.
AI can audit these vulnerabilities by scanning for irregularities, anomalies, and patterns that deviate from historical human behaviour. But executives must recognize that this question can only be answered accurately when the data feeding the model is clean. Asking this question forces the enterprise to confront a deeper issue: does the organization possess a reliable ground-truth layer, or is it relying on publicly contaminated signals? The answer often determines the company’s actual level of exposure.
3. What competitive strategies can be inferred by analyzing weak signals and micro-patterns in global data flows?
In my recent discussion, one of my expert-friends described how major corporations are preparing to reconfigure entire market categories using AI-driven micro-personalization strategies.
These shifts rarely show up in press releases or earnings calls. They appear as subtle changes in hiring patterns, supply chain contracts, real-estate moves, niche acquisitions, or targeted investments. AI, combined with an intelligence-trained human team, can detect these faint signals long before they consolidate into visible threats.
When a CEO asks this question, they begin to see competitors not as static entities but as evolving strategic actors whose intentions can be decoded. This kind of early detection is the difference between reacting to a market disruption and shaping one.
4. What emerging behaviours or incident patterns within my operational environment are early indicators of systemic instability?
One of the most insightful remarks in my last conversation with my inner circle concerns the value of “hyper-microscopic data collection”—high-frequency, human-validated signals that reveal real conditions on the ground.
Organizations that rely exclusively on aggregated dashboards miss the subtle indicators that precede major operational disruptions: rising petty theft around retail locations, unusual traffic patterns in logistics lanes, shifts in employee sentiment, or irregular supplier behaviour.
AI is effective at detecting such anomalies, but only if leaders ask the right questions and build the right intelligence infrastructure. When executives inquire about early indicators, AI becomes a risk radar rather than a retrospective reporting tool. This fundamentally changes the role of data: it becomes predictive, not descriptive.
5. How likely is my sector to undergo consolidation, disruption, or collapse due to macroeconomic shifts or technological advances?
My expert exchange provided a detailed example of how entire industries could be absorbed by larger players through AI-enabled market strategies. The prediction that some consumer ecosystems may be swallowed by global consumer giants is not an isolated case; it is a template for what will occur across sectors.
When executives ask AI to model their vulnerability to strategic consolidation, they confront a reality few leadership teams are prepared to face: sometimes the greatest risk is not operational failure but competitive irrelevance. AI can compare historical analogues, analyze capability gaps, and assess whether the company’s current trajectory makes it an acquirer, a target, or a casualty.
This question forces leaders to evaluate their own competitiveness with ruthless clarity.
6. What critical information is missing from our decision-making process, and how would our strategy change if we had it?
In the intelligence world, the most dangerous risk is often the data you do not know you are missing. Missing information creates blind spots, and blind spots become operational or strategic vulnerabilities. AI is particularly powerful in addressing this dimension because it can map gaps, inconsistencies, and areas where the organization lacks visibility.
This question pushes executives to confront the unknown unknowns—the risks that cannot be seen without deliberate interrogation. It pulls leadership away from confirmation bias and forces a deeper kind of strategic introspection. The answer is rarely comfortable, but always essential.
7. “Which of our current decisions rely more on intuition or habit than on validated intelligence?”
Every organization claims to be data-driven, but beneath the surface, countless decisions are guided by tradition, personal conviction, or internal politics. AI can help expose these patterns by evaluating the basis of each decision: what data supports it, what assumptions it rests upon, and what alternatives were dismissed. This is not about replacing human judgment; it is about evaluating whether that judgment is informed or inherited.
Asking this question reveals where the organization is operating on autopilot. It shows where AI should be an advisory partner and where human oversight must be strengthened. It is a question that brings discipline to decision-making.
8. What changes in global consumer behaviour suggest imminent market shifts that are not yet visible in traditional analytics?
Market disruptions rarely arrive as sudden shocks. They emerge slowly, through behavioural drifts, micro-trends, or geographic prototypes that later become global. AI is uniquely suited to detect these faint behavioural movements—especially those invisible to conventional data segmentation. When a CEO asks this question, they signal an intention to anticipate customer evolution rather than react to it. This is the difference between innovation and adaptation.
9. What are the most plausible high-impact scenarios that could reshape our operations, finances, reputation, or supply chain in the next three to five years?
Black swan events cannot be predicted, but scenario families can be mapped with clarity. AI can generate hundreds of simulations that combine political instability, technological disruption, cyber events, regulatory changes, and economic volatility. Leaders who ask this question begin to see their environment through an intelligence lens, where resilience is built through preparation rather than optimism.
Such scenarios are not science fiction. They include maritime disruptions, industrial cyberattacks, cascading supply chain failures, AI-driven fraud, or sudden shifts in public sentiment triggered by synthetic influence campaigns. Asking the question forces the organization to imagine—and prepare for—what it prefers not to contemplate.
10. Which alliances, partnerships, or ecosystem positions would dramatically increase our resilience or competitive advantage?
No company survives the next decade alone. Geopolitical complexity and AI-driven competition require ecosystems, not isolated firms. AI can analyze complementary capabilities, shared threats, and mutual dependencies across the market to identify unconventional alliances. This question reframes strategy from “How do we win?” to “Who must we win with?” It is a shift from isolation to strategic interdependence, a hallmark of the intelligence-informed enterprise.
The Deeper Meaning Behind These Questions
What unites these ten questions is not their analytical sophistication but their strategic posture. They are designed to force executives to think like intelligence officers rather than administrators or operators. They demand curiosity instead of complacency, anticipation instead of reaction, and verification instead of assumption.
They also redefine the role of AI in the enterprise. AI becomes not a generator of answers but a catalyst for insight—a mechanism that reveals blind spots, tests assumptions, and elevates decision-making beyond what intuition or experience alone can achieve. These questions, asked continuously and systematically, build a form of organizational cognition that integrates technology, intelligence, and human judgment.
In the next section, we will explore how companies can operationalize this intelligence-driven decision architecture, how to build the data foundations required to support it, and how to structure an internal intelligence unit capable of producing actionable insight in a world where information is both abundant and contaminated.
Stay Tune!
