At Rome Business School, a panel on Strategic Foresight in the Age of Artificial Intelligence during Rome Future Week 2025

Rome Business School and PMI Central Italy explore scenarios, governance, and skills to shape the future in the AI era

• Among the key topics: the urgency of moving beyond linear approaches, the need for responsibility beyond KPIs, and the design of dynamic scenarios
• Preparedness as a competitive advantage: AI enables organizations to simulate strategies and anticipate disruption
• Anticipatory governance and solid data governance as prerequisites to integrate innovation and resilience
• The project manager as an enabler of strategy and value, in ecosystems where human stakeholders and AI agents coexist

As part of Rome Future Week 2025, Rome Business School, in collaboration with the Project Management Institute Central Italy, hosted the conference Strategic Foresight in an AI World: Are You Ready?. The event, opened with institutional greetings by Massimo Scarcello (Associate Dean, Rome Business School) and moderated by Gerlie Saura (Senior Manager Corporate Education & Institutional Relations, Rome Business School), brought together experts from academia and business who shared complementary perspectives on the future of leadership in the age of artificial intelligence.

Why foresight is now urgent

The discussion began with the scale of today’s acceleration: by 2030, most project management activities will be supported by AI, yet only a minority of professionals report advanced skills with these tools. On top of that, 85% of executives consider their business models exposed to disruption within the next five years. In this context, foresight is no longer an academic exercise but an operational mindset to identify weak signals, build scenarios, and prepare decisions before shocks materialize.

AI and human responsibility: beyond KPIs

Opening the panel, Valentino Megale (Program Director, Master in Artificial Intelligence – Rome Business School) shifted the focus from “what AI can do” to “how we choose to use it.” Automating intellectual work is possible, but the real value lies in the growth paths of people and the quality of the decisions that shape technology.

“We should not stop at the next KPI: artificial intelligence will have far deeper long-term impacts. This is where the real challenge of leadership and responsibility lies.” — Valentino Megale, Rome Business School

Megale stressed that an efficiency-only approach can become a bottleneck if not paired with process reengineering and reskilling: cutting costs without redesigning workflows hinders performance; rethinking them opens new value.

Methodologies in transformation: from the speed paradox to early warning

Giuseppina Rizzolo (CA & Auditor; Master in Social Foresight – University of Trento) highlighted what she called the speed paradox: while AI advances at exponential speed, traditional foresight tools quickly become obsolete. She pointed to the need for dynamic metrics (emerging capabilities, speed of improvement, cross-sector integration), probabilistic forecasts constantly updated, and early warning systems to capture when cycles shift.

“It is not so much about predicting the future of AI, but about developing the capacity to navigate its ongoing evolution.” — Giuseppina Rizzolo, University of Trento

Rizzolo emphasized collaborative approaches that leverage global expert networks, combining technical variables with cultural, organizational, and regulatory dimensions.

Preparing before disruption: simulate, test, decide

From a business standpoint, Filippo De Vita (Director, EY.AI – EY) focused on preparedness: the difference between laggards and frontrunners is the ability to use foresight and AI to simulate strategies, test hypotheses, and act in advance.

“The real question is how we can prepare to change before disruption arrives: AI gives us scenarios and simulations, but leaders need the vision to anticipate and act.” — Filippo De Vita, Director of EY.AI

Governance and infrastructures: from compliance to learning capacity

Carla Nisio (VP Cloud4TIM & IT – Noovle; Board Member – FederAcademy) outlined a shift from reactive, compliance-driven governance to anticipatory, adaptive, and learning-oriented models. This means:

• Monitoring emerging signals and integrating them into decision-making;
• Dynamic risk management (model drift, new rules, new players);
• Distributed accountability across business units;
• Feedback loops to learn from experimentation.

On the technical side, she stressed the importance of AI-ready infrastructures: scalable, composable architectures, solid data governance, balanced edge vs cloud strategies, resilience by design, and sandbox environments for safe experimentation.

“Structures must evolve: distributed responsibility, data governance, and modular architectures are the foundation for effective foresight in the AI era.” — Carla Nisio, Noovle / TIM

Project management and ecosystems: delivering value, not just output

Closing the panel, Carmine Paragano (President – PMI Italy; Senior Director – NTT DATA) reframed foresight through the lens of the project manager and the ecosystem perspective. The PM’s role is not only to deliver outputs but to realize strategy and value, in contexts where human stakeholders and AI agents will increasingly coexist. What matters are accountability, data, and the ability to orchestrate collaborations.

“The project manager is the one who makes dreams — the company’s strategy — come true. With AI we can deliver better projects, but accountability still rests with us.” — Carmine Paragano, PMI Italy / NTT DATA

A purpose-driven closing

Wrapping up, Antonio Ragusa (Dean, Rome Business School) recalled the School’s purpose-driven mission and the centrality of humanistic management, where innovation and ethics move together.

“The real challenge is not to survive change, but to transform it into a driver for innovation, sustainability, and inclusion.” — Antonio Ragusa, Dean – Rome Business School