Many organisations find themselves stuck in a loop of isolated AI pilots. Individual experiments show promise, but the results rarely scale, and leaders are left wondering how to turn interesting use cases into a coherent, value-creating strategy for the whole enterprise. Our upcoming programme ‘AI Strategy for Enterprises’ is designed to help senior leaders move from scattered silo initiatives to an organisation-wide approach to achieving enterprise Value from AI.
At the heart of the programme is that AI is much more than a technology project, it is a strategic change initiative which needs to be implemented for effective transformation. As Professor Michael Barrett explains, “AI only creates lasting value when it is woven into the fabric of how an organisation competes, its operating and business model. Pilots are the starting point, not the destination.” Across this three day programme, participants explore what it takes to build that capability through a process of aligning AI strategy with their business strategy. Rather than treating AI as an experimental add-on, leaders learn how to connect use cases directly to a portfolio of problems and opportunities such as growth, productivity, customer experience, risk reduction, or societal impact, so that every AI innovation has a clear strategic purpose.
Another key focus is on data foundations. Scalable AI depends on high-quality, accessible, and well-governed data. Without this, even the most sophisticated models remain stuck in pilot mode. During the programme, leaders examine the state of their own data landscape such as where critical data sits, how it is governed, and which gaps are holding back their ambitions. In Professor Barrett’s words, “If strategy is the compass for AI, data is the terrain. You cannot chart a meaningful AI strategy without understanding the data and models that are grounding initiatives.”
AI as a strategic enabler at scale requires shared platforms, clear governance structures, and cross-functional ownership that cuts across business units. Participants discuss how to move away from fragmented experiments towards coordinated portfolios of AI initiatives. As Professor Barrett notes, “The organisations that succeed with AI are those that treat it as a long-term engagement involving a careful understanding of AI risks and opportunities, emerging business models and ways of organising that recognise AI-human collaboration, people and skills needed for effective strategic change.”
Participants consider how to upskill their workforce, engage colleagues in experimentation, and redesign workflows to enable effective human–AI collaboration. They reflect on how to build a culture where curiosity, responsible innovation, and continuous learning are encouraged, while also addressing legitimate concerns about job redesign and accountability. Professor Barrett captures this balance succinctly: “Responsible AI is not only about rules and safeguards, it is also about equipping people to work confidently and critically with intelligent tools in redesigning workflows through an enabling culture .”
Leaders examine how to establish clear accountability, risk management, and ethical oversight for AI, alongside robust metrics to track impact. They are encouraged to evaluate AI initiatives through three lenses: strategic value, data readiness, values, and ethical responsibility for risk. The more successful organisations align business goals, data capabilities, and responsible AI principles from the outset, ensuring AI creates sustainable value while maintaining trust and managing risk.
A distinctive feature of the programme is its challenge to leaders to think more fundamentally about how AI could reshape their business model, customer value proposition, operating model, and role within wider ecosystems. The programme provides an understanding of business model innovation in imagining AI use for creating new opportunities for the organisation and the challenges of maintaining business model coherence along the way. This framing balances risk with opportunities for growth, innovation, and competitive advantage. The question becomes: “How would we compete if AI fundamentally changed the rules of our industry?”
By the final day, participants begin to translate insights into action through a tailored AI roadmap for their organisation using practical frameworks to identify high-value opportunities, assess data readiness, evaluate risks, and prioritise use cases based on business impact and feasibility. Participants are encouraged to develop an outline plan and strategy to take back to their organisations and implement.
Reflecting on the programme, Professor Barrett emphasises the importance of this practical orientation: “Leaders do not need more AI hype, they need grounded conversations and knowledge that connect technology to strategy, business model, implementation and people. Our aim is that participants leave not only inspired, but equipped with a concrete roadmap and a clearer sense of how to lead AI responsibly at scale”.
Our upcoming AI Strategy for Enterprises programme highlights the shift leaders must make from fragmented experimentation to a coordinated, value-driven approach to AI. Under the academic direction of Professor Michael Barrett, it shows how lasting impact comes not from isolated pilots, but from aligning AI with business strategy, strengthening data foundations, and building the capabilities needed to scale responsibly.
Develop the strategic insight, innovative frameworks, and practical AI roadmap to move beyond experimentation, reimagine your enterprise, and lead AI transformation that creates real-world impact. Join our upcoming cohort, 22–24 July in Cambridge. Learn more >
