Agentic AI
,
Artificial Intelligence & Machine Learning
,
Next-Generation Technologies & Secure Development
CIOs Face Integration, Talent and ROI Hurdles Despite Rising AI Budgets
CIOs looking for quick wins from artificial intelligence may be out of luck. The real value from AI won’t come from plug-and-play tools that can be bought, but rather from the hard work of integrating AI into enterprise systems, workflows and operating models, according to new research from Cognizant.
See Also: How Unstructured Data Chaos Undermines AI Success
Successful technology leaders will be able to build bridges between emerging AI capabilities and the complex realities of their enterprise technology operations. Value will come from customization and creation, not from purchasing standalone technology solutions from vendors.
The Cognizant survey found that vendor preferences are shifting, and enterprises are increasingly turning to “AI builders” over “off-the-shelf” vendors to create more customized solutions. IT services firms have a 23% trust advantage over management consultancies when it comes to AI adoption, as CIOs prioritize hands-on implementation and operational accountability over high-level strategy.
Flexible engagement models were the top reason AI decision-makers chose an AI solution, ranking higher than pricing and time to value, Cognizant found. The IT services firm worked with research firm Avasta to survey 600 AI decision-makers and interview 38 senior executives in November 2025.
“AI success is not about deploying isolated models – it’s about engineering intelligence into the enterprise with purpose-built solutions,” said Ravi Kumar S, CEO of Cognizant.
For many enterprises, AI is a core operational expense, the survey found. Among enterprises, 84% said they now maintain formal AI budgets and 91% expect those budgets to grow. Half of respondents said they expected that growth to be in the double digits over the next two years.
These expenses can be significant, with 52% of firms reporting that they’re already investing $10 million or more annually.
While budgets are robust, the course of successful AI scaling never runs smoothly, and many are in a phase Cognizant calls the “messy middle,” caught between ambitions and actual capabilities. Nearly two-thirds of enterprises reported that there were “moderate to large capability gaps” between what they wanted to do and what they were able to do.
AI leaders identified three primary barriers to success. First, 33% report that they’re stymied by regulatory and compliance concerns as they navigate the complex legal landscape of automated decision-making. Demonstrating tangible ROI for these early-stage investments is a challenge cited by 31% of respondents, and data and talent readiness were called out as barriers by 27% of respondents as companies struggle with shortages in the specialized skills and clean data required to advance pilots into production.
Legacy systems also are creating drag, consuming up to 80% of IT budgets and creating road blocks as they can lack the agility needed for modern AI integrations.
The survey also asked how respondents are thinking about labor displacement, but the results show that most AI leaders think the future will involve significant human-AI collaboration rather than mass layoffs. Across 13 enterprise functions, sales ranked as the most likely to see full automation at 20% and finance was least at 10%. In customer service roles, respondents expect 76% of workflows to be AI-dominant, yet only 9% believe they will be fully automated.
Another recent Cognizant study found that just 10% of all job tasks are fully capable of being automated, although that showed a sharp increase from 1% three years ago.