Every day, executives make decisions that shape the fate of their organisations. They navigate volatile markets, manage competing stakeholder demands, and set long-term strategic direction, often under intense time pressure and with incomplete information. Now, a new partner is entering boardroom: artificial intelligence. And contrary to the headlines, it is not here to replace executives. It is here to augment them.
The Limits of Human Judgment and Machine Logic
Research from ESCP Business School, based on 15 interviews with executives and AI experts, reveals a striking picture of complementary strengths. Human executives bring intuition, ethical reasoning, emotional intelligence, and accountability to the table, qualities forged through years of experience that no algorithm can yet fully replicate. AI, on the other hand, can process vast datasets, detect hidden patterns, generate forecasts, and surface insights at a speed and scale that overwhelms human cognition.
But both have meaningful blind spots. Executives, operating in what strategists call VUCA environments (Volatile, Uncertain, Complex, and Ambiguous, can fall victim to cognitive biases, information overload, and other limitations of bounded rationality. AI systems, meanwhile, can inherit biases from their training data, lack contextual awareness, and produce outputs through processes so opaque they are sometimes referred to as a “black box.” The conclusion the research reaches is clear: neither should act alone.
Three Levels of AI Collaboration
The ESCP researchers adapt a Gartner framework to map three distinct modes of human-AI collaboration in executive decision-making. At the first level, Decision Support, AI functions as an analytical assistant. It generates board reports, financial forecasts, and sales projections quickly and without human error. In situations of limited or ambiguous information, executives remain firmly in control, using AI outputs to sharpen their intuition rather than replace it. One executive interviewed described using a large language model as a knowledge base when developing a new business strategy, not to delegate the thinking, but to broaden it.
The second level, Decision Augmentation, is where AI becomes a genuine strategic partner. With richer data, AI can offer concrete recommendations on hiring targets, market entry strategies, or investments, while executives retain control over the final decision. Some organisations are already experimenting with “digital twins,” AI-powered simulations of entire companies that allow leaders to stress-test strategies before committing. The main challenge here is trust: executives must learn when to follow AI’s suggestions and when their own judgment should override them.
The third level, Decision Automation, currently dominates operational rather than strategic contexts. Routine tasks like automated payments, contract renewals, capacity planning, and calendar management are increasingly handed off to AI systems. This frees executive attention for the decisions that genuinely require human judgment. Full automation of strategic decisions, the researchers conclude, remains distant, given the irreplaceable roles of “real” creativity, ethics, and accountability.
Making It Work: A Three-Step Approach
Despite the promise, the research surfaces persistent obstacles: many organisations lack the data infrastructure and digital readiness to deploy AI effectively. Executives report feeling pressure to adopt AI out of fear of missing out, while others resist it out of fear of being replaced and loss of control. Both reactions, the authors argue, are counterproductive.
The recommended path forward is deliberate and structured. Executives should first identify where AI can genuinely add value to their decision process. They should then prepare their organisation for change, investing in data infrastructure, developing prompting and digital skills, and cultivating a culture of experimentation. Finally, they should actively scout for AI tools relevant to their use-cases, engage with external experts, and stay curious and informed about emerging capabilities.
The Executive’s New Competitive Edge
The implications of this research are significant. As AI handles more analytical and operational work, the executive role will evolve towards designing creative strategies, overseeing AI agents, anticipating technological risks, and managing human relationships. As data and algorithms are increasingly available, executives who effectively augment their decision-making with AI will become their company’s ultimate differentiator.
Augmented executives are not threatened by AI. They are empowered by it. Those who learn to collaborate effectively with these systems will make faster, better-informed, and more foresighted decisions. In an era of relentless complexity, that is precisely the competitive edge organisations need.
Based on research by David Reinecke and Maximilian Weis, ESCP Business School
Source: Reinecke, D. & Weis, M. (2025). “The Augmented Executive: Enhancing Executive Decisions with Human-AI Collaboration.” ESCP Impact Paper No. 2025-22-EN.
