The findings, drawn from discussions with 1,800 global executives, highlight a widening gap between the desire to deploy artificial intelligence and the internal capacity to sustain it. Although 40% of organizations claim to have an enterprise-wide AI strategy, only 20% have successfully extended that strategy across their broader operational ecosystems. Furthermore, barely half of the surveyed leaders are currently quantifying the specific results of their AI investments.

Legacy infrastructure remains a primary hurdle, with 45% of executives identifying outdated systems as a significant barrier to data-driven AI success. This technical debt is compounded by a persistent human capital crisis; nearly 70% of firms report difficulty in recruiting specialized IT talent, a shortfall that 52% of leaders say is materially delaying their digital transformation projects.

To counter these pressures, executives are increasingly pivoting toward managed services models. By consolidating their vendor landscapes, firms are seeking partners capable of bridging the divide between high-level consulting and the practical reengineering of data foundations. As CGI President and CEO Tim Hurlebaus noted, the focus is shifting from simple experimentation to building the modernized environments necessary to scale AI. Without fixing these underlying operational models, the report warns, organizations risk increasing complexity rather than achieving sustainable competitive advantage.