IBM’s CEO Report on AI for 2025 confirms what many of us in the innovation space already feel in our bones: the AI era is entering a new chapter – one defined not by possibility, but by performance.
While the report is framed around five critical mindshifts required to realise AI’s full potential, we’ve honed in on four telling observations that map closely to the challenges and conversations we’re seeing with our partners across government, enterprise, and growth-stage businesses.
Business Model Innovation Drops – but It’s Not Going Anywhere
Business model innovation has slipped from the top priority in 2024 to the number three priority for 2025. At first glance, that might suggest a declining appetite for transformation, but viewed in context, it signals something more pragmatic – innovation efforts are maturing.
With economic uncertainty and budget pressures persisting, boards are shifting focus from “what’s next?” to “what works?” That doesn’t mean the bold ideas are off the table – it just means the appetite now demands ROI and traction, not just exploration.
For many of our enterprise clients, this aligns with a movement from lab-based experimentation to grounded, scalable solutions – supported by internal capability, not just external pilots.
Talent Leaps Up the List—But It’s About Fit, Not Just More
Perhaps most telling is the leap of talent strategy from priority #10 to #2. While headlines often point to a war for AI talent (and talent in general), we’re seeing a more complex reality unfold.
It’s not just about hiring data scientists and software engineers, it’s about right-sizing, re-skilling, and redesigning roles for the AI-enabled future. It’s about embedding capabilities across the business, not in silos.
Organisations don’t just need new people. They need new behaviours, incentives, and pathways that align with AI-enabled workflows. Our AI Capability Uplift programs are designed specifically for this reason – to move beyond tool training and prompt engineering into culture-shifting readiness.
In short: it’s not just who you hire, but how your existing teams learn, adapt, and lead that will determine AI success.
AI ROI Remains Elusive – CEOs Need Better Change Playbooks
IBM’s report states that just 25% of AI initiatives are delivering ROI, and only 16% are scaling enterprise-wide. That’s a brutal statistic – and a familiar one. Anyone who has worked in digital transformation over the last 20 years knows that innovation change management is key to success.
We’ve seen first hand that the gap isn’t usually in the tech. It’s in the translation – aligning AI with core business priorities, embedding the right change frameworks, and building confidence in the why – not just the how.
This is why our AI Discovery Sprints are built to start with problem-worth-solving frameworks, not shiny object syndrome. It’s why we insist on co-designing with the teams who’ll use these tools – not just building for them. And it’s why benefits realisation is not an afterthought, but baked into the roadmap from day one.
The Next Three Years Are About Skills – and Structures
CEOs are preparing for a wave of new capabilities over the next three years. But as the IBM report highlights, this isn’t just a matter of learning – it’s a matter of design.
The AI-enabled enterprise will look different. It will be structured differently. Roles will blur, incentive systems will need rewiring, and governance frameworks will need to keep up with ethical, strategic, and operational shifts.
For organisations navigating these shifts, the mandate is clear: learning and development programs must go hand-in-hand with organisational design. That’s why we work at both levels – building capability and advising on the structures that let those capabilities stick.
