New Delhi, July 28 -- Enterprise AI is entering a new phase. The conversation is no longer about who has deployed the most copilots or built the most AI agents. Instead, boards are increasingly asking a harder question: What business value is artificial intelligence actually delivering?
A series of global studies released over the past few months points to the same conclusion. CIOs are moving from being technology enablers to business leaders responsible for proving returns on AI investments, redesigning operating models and ensuring governance keeps pace with rapid deployment.
The latest evidence comes from IT staffing solutions firm Experis' CIO Outlook 2026, which found that aligning IT strategy with business objectives has overtaken cybersecurity as the top priority for CIOs for the first time. Nearly half (48%) of technology leaders now rank business-IT alignment as the CIO's most important responsibility, up from 34% a year ago, while 54% say their AI investments are already generating positive returns.
Yet the findings also reveal growing pressure. Nearly one-third of respondents believe their organisations may be overinvesting in AI, and 61% say the CIO's role remains poorly understood by other members of the C-suite, making it harder to align technology decisions with business priorities.
That disconnect is echoed across other industry research. According to IBM's latest global study, two-thirds of CIOs and CTOs are now accountable for AI systems they do not fully control, while 77% say AI adoption is moving faster than governance frameworks can keep pace. Only 11% believe their organisations are fully prepared for the scale of AI agents expected over the next year.
Gartner, meanwhile, has found that only 28% of AI use cases in infrastructure and operations fully meet return-on-investment expectations. The analyst firm argues that successful AI initiatives are distinguished less by sophisticated models than by strong business alignment, executive sponsorship, workflow integration and governance.
In an interview earlier this month, Vijay Balakrishnan, chief digital and information officer at Godrej Enterprises Group, said enterprises are shifting away from isolated AI pilots toward building enterprise-wide data foundations and digital platforms that can support AI at scale. He argued that AI initiatives deliver value only when embedded into core business processes rather than treated as standalone innovation projects.
Similarly, Balakrishnan Narayanan, chief product and analytics officer at Fibe, said the next phase of digital lending will be defined by AI that improves underwriting, fraud detection and customer experience, rather than AI deployed simply for automation. For financial institutions, he said, the focus is increasingly on measurable business outcomes supported by alternative data and analytics.
Kaushal Kurapati, group vice-president for Oracle Fusion Applications at Oracle, described enterprise software as entering an "AI-first" era in which customers are buying business outcomes rather than applications. The shift, he argued, will fundamentally change how enterprises evaluate software investments, with success measured by productivity improvements instead of feature adoption.
Analysts say the evolution is inevitable. Sanchit Vir Gogia, founder and chief analyst at Greyhound Research, said that enterprises are moving beyond experimenting with generative AI and are now focused on operationalizing AI responsibly. "The winners will be those that combine governance, data readiness and measurable business outcomes-not just model deployment," he said.
The governance challenge is becoming increasingly important as organizations deploy autonomous AI agents across business functions. Deloitte has argued that boards must begin treating AI governance as an operating discipline rather than a compliance exercise, with clear accountability and measurable value reporting becoming central to enterprise AI strategies.
That represents a significant shift in how CIO performance is being evaluated. Historically, technology leaders were measured on uptime, cybersecurity, infrastructure modernisation and digital transformation. Increasingly, however, CEOs and boards expect CIOs to demonstrate how AI improves margins, accelerates product development, enhances customer experience or creates new revenue streams.
The challenge is compounded by persistent talent shortages and the pace of technological change. Experis found that cybersecurity remains the most sought-after technical skill, followed by AI and machine learning, while nearly half of technology leaders identified rapid technological innovation as their biggest organisational challenge.
Taken together, the findings suggest enterprise AI is entering what many executives describe as its "accountability phase." The question is no longer whether organisations have adopted AI, but whether they can govern it, scale it and demonstrate sustained business value. For CIOs, that may become the defining metric of leadership over the next few years.
Published by HT Digital Content Services with permission from TechCircle.