IBM: Where Will AI Contribute to Revenue Growth?

Business leaders are betting big on artificial intelligence as a central force for growth by 2030.

That's according to the Enterprise 2030 Study from IBM’s Institute for Business Value, which finds 77% of C-suite executives in the UK and Ireland believe AI will contribute to revenue growth by 2030 – up from 37% who say the same of today.

While confidence in AI’s potential is rising fast, clear strategies to realise its financial promise remain in short supply. Just 27% of executives say they have a clear understanding of where that future revenue will come from.

IBM identifies this disconnect as a key leadership issue, describing it as a “challenge that will define strategy for the next decade”, requiring organisations to evolve from using AI as a supporting tool to building fully AI-integrated business models.

AI investment rises but risks remain

Executives expect AI investment to grow by approximately 149% by 2030, reflecting an intention to embed intelligence not just in operations, but throughout entire product lines and services.

At present, nearly half (47%) of AI spend focuses on improving efficiency. However, by 2030, businesses expect 64% of AI budgets to go toward innovation in products, services and business models. IBM sees this as a transition from simple cost savings to broader value creation.

But the greater risk, the study says, is not failing to invest — it is investing without clear direction.

The report highlights that 73% of leaders worry that AI initiatives could fail if they are not properly integrated into core business functions. As IBM describes it, success depends on becoming an “AI-first enterprise” instead of simply layering AI tools onto existing processes.

Rahul Kalia, Managing Partner for the UK and Ireland at IBM Consulting, says: “AI is no longer just a tool for efficiency – it’s becoming a growth engine for the enterprise. With UK AI investment set to increase significantly in the next four years, success will hinge on integrating AI into core business strategies and reskilling the workforce.

"Organisations that act decisively, with the appropriate governance and controls in place for AI, will be the ones defining competitive advantage tomorrow.”

The wider economic benefits are substantial. According to the UK Government’s AI Opportunities Action Plan, AI could add £400bn (US$551bn) to the national economy by 2030 through higher productivity and increased innovation. IBM’s research aligns with this, predicting AI-led productivity growth of 44% across the UK and Ireland within the decade.

Global shifts point to deeper integration

IBM’s findings are not confined to a single region. The global study, covering 33 countries, shows that business leaders everywhere are shifting from AI trials to full integration into products, workflows and decision-making systems.

This pattern is especially strong in North America, Europe and the Asia-Pacific region, where businesses are embedding AI into strategic areas. However, the same challenge remains across all markets: a lack of clarity on where value from AI will emerge.

Emerging economies may benefit from a different angle. With fewer legacy systems in place, these markets can more easily implement AI-native frameworks, often in combination with upgrades to cloud computing and data infrastructure.

But no region is immune from workforce concerns. At least half of executives worldwide expect a major reshaping of employee skills by 2030. This positions reskilling as a global business priority, not just a regional concern.

Competitive advantage and the quantum horizon

The study reveals a widening gap between companies taking action on AI and those falling behind. In the UK, 48% of executives believe their advantage will come from the quality of their AI models, but only 29% feel they know which models to adopt by 2030.

A large majority (81%) expect to rely on a combination of large-scale and more targeted AI systems tailored to their own business logic. This reflects a shift away from one-size-fits-all tools towards multi-model ecosystems aligned with specific needs.

Quantum computing also emerges as a factor in shaping AI's future. Six in 10 executives say that quantum-enabled AI will transform their industries, yet only 37% are preparing their organisations to be ‘quantum-safe’ – referring to readiness for quantum computing’s impact on data security and algorithm performance.

IBM warns that the balance between innovation and governance must be carefully managed. It concludes that the journey from ambition to outcome depends on proper integration of AI, investment in skills and a governance structure that builds trust.