Enterprises are forecasting a substantial rise in AI-enabled workflows, with expectations for more than an eight-fold increase from 3% currently to 25% by year-end, according to a new study by IBM. The “AI Projects to Profits” study, conducted by the IBM Institute for Business Value, surveyed 2,900 global executives and highlights a shift from experimental AI use to essential business operations.
The research, conducted with Oxford Economics, involved two surveys, the “AI at the Core” survey and the “Agentic AI Pulse” survey. Findings indicate that AI investment accounted for about 12% of IT expenditure in 2024, with expectations for this figure to rise to 20% by 2026. Notably, 64% of AI budgets are now focused on core business functions, marking a strategic shift from experimentation to integration within key operations.
AI agents are anticipated to enhance efficiency and adaptability significantly. By 2026, 83% of respondents expect improvements in process efficiency and output, while 71% believe these agents will adjust autonomously to changing workflows. Key benefits driving adoption include improved decision-making, cited by 69%, cost reduction through automation at 67%, and competitive advantage at 47%. Enhanced employee experience and talent retention are also significant factors, noted by 44% and 42% of executives, respectively.
Despite these advantages, challenges remain in adopting agentic AI systems. Data concerns are highlighted by 49% of survey participants, while trust issues are a barrier for 46% and skills shortages a concern for 42%. However, confidence in AI-driven transformations is rising; reliance on an ad hoc approach has plummeted from 19% last year to just 6%.
“We see more clients looking at agentic AI as the key to help them move past incremental productivity gains and actually gain business value from AI, especially when applied in their core processes like supply chain and HR,” said IBM consulting vice president and AI integration services senior partner Francesco Brenna. “This isn’t about plugging an agent into an existing process and hoping for the best. It means re-architecting how the process is executed, redesigning the user experience, orchestrating agents end-to-end, and integrating the right data to provide context, memory, and intelligence throughout.”
High returns possible as organisations shift towards core functions
The study found that one-quarter of surveyed companies have adopted an “AI-first” strategy, attributing over half of their revenue growth and operating margin improvements to AI initiatives from the past year. While initial returns from generative AI pilots were high, averaging around 31%, they have now stabilised at about 7%, falling short of typical capex hurdle rates. Only a quarter of AI initiatives have met expected ROI over three years; however, top-performing companies report returns around 18%, surpassing cost-of-capital benchmarks.
The IBM study found that organisations are redirecting investments towards core functions that now command the majority of AI budgets. This shift away from scattered pilots indicates a trend towards strategic implementation across various business domains. Despite progress, fewer than one-quarter reimagine workflows with AI as a central growth engine or redefine business models.
Read more: 88% of US firms to increase AI budgets amid agentic AI adoption, finds survey
