Reuters Momentum Highlights: Leading Through the Acceleration of AI

I had the opportunity to moderate a panel at the Reuters Momentum AI event in London this week, where the pace and scale of technological transformation were unmistakable. What became clear during the panel was that the conversation has moved decisively beyond experimentation, with AI now firmly established as a core driver of operational efficiency, risk management, and customer experience.

Yet with opportunity comes complexity, as the definition of what’s considered tablestakes continues to evolve. With that in mind, businesses face two major challenges. First, distinguishing genuine innovation from hype — which means understanding what’s viable today versus what remains aspirational.

Second, managing the relentless pace of change. Organisations are being asked to adapt faster than ever, often reshaping strategy in real time to keep pace with evolving technologies, market dynamics, and customer expectations.

When it comes to adapting to change, three core ideas stood out from the panel discussion that businesses can lean on.

1. Real-Time Insight
To thrive in an AI-driven world, businesses must move beyond static dashboards and embrace dynamic, actionable intelligence. Timely data will empower leaders to make fast, informed decisions and pivot with precision. But speed alone isn’t enough — data quality, governance, and lineage are now board-level priorities. AI is only as effective as the data that powers it, and businesses are investing heavily to ensure their data foundations are robust, trustworthy, and scalable.

2. Flexible Operating Models
Rigid structures will hinder progress. Forward thinking businesses are embedding flexibility into their processes and embracing open ecosystems — collaborating across platforms, partners, and industries to accelerate innovation and reduce silos. Cloud-native platforms, API-first architectures, and AI-specific tools are also becoming standard as they allow for faster integration, scalability, and responsiveness.

3. Talent and Mindset
Talent remains the ultimate differentiator. As demand grows for AI-literate roles, businesses are upskilling teams and forming cross-functional groups that blend technical depth with domain expertise. Crucially, they’re fostering a mindset shift — encouraging curiosity, continuous learning, and the confidence to test, iterate, and pivot when needed.

The future of AI is full of possibility, from autonomous agentic systems to hyper-personalised experiences and scalable assurance frameworks. But the real impact will come from building strong foundations, staying agile, and making deliberate, informed choices.

Businesses must remember that the ability to say “this isn’t working” is just as important as the drive to push forward. In a landscape defined by constant change, clarity and adaptability will separate those who lead from those who follow.