For most of the past three decades, the Chief Information Officer's mandate was easy to describe: keep IT solutions running, manage vendor relationships, control costs and maintain enterprise cybersecurity perimeters. Once a largely operational job dressed in a strategic title, it frequently sat one step removed from the big-picture planning and business decisions that actually moved markets. If IT was the plumbing behind a firm's technology infrastructure, it was the CIO's job to make sure it did not leak.
That is no longer the case, Rob Enderle, principal analyst at the Enderle Group, told The Forecast.
"The days of the CIO just keeping the lights on and managing servers are basically over," Enderle said. "We're moving from a cost-center focused mindset to focusing entirely on turning enterprise data into actual, predictive business value."
The rise of analytics, automation and agentic AI has upended the scope of the job and the work being performed, he said.
"It's no longer about just maintaining infrastructure; it's about driving the business strategy," Enderle said.
Like the experts behind Nutanix's recent masterclass for C-level leaders, "The Impact of AI on the CIO Role," also underscore, AI is no longer a back-office efficiency tool. It is a strategic business enabler, meaning CIOs must rebrand their work and operate more like business architects who align AI capabilities, strategies and initiatives with big-picture enterprise goals.
The organizations pulling ahead today are not simply deploying better IT solutions and large language models. They are building what might be called enterprise intelligence: a web of integrated, intelligent solutions capable of ingesting, parsing and interpreting data holistically across the business, acting on it through automation and continuously improving through feedback. The executive responsible for all of this, the person who has to design it, govern it, explain it to the board and evolve it faster than competitors, is increasingly the CIO.
"Today's CIOs must be as dynamic and adaptable as the technologies they champion, navigating through an era of remarkable change within the digital landscape," said Rami Mazid, former CIO and senior vice president of Nutanix.
What Does the Work of Tomorrow's CIO Actually Entail?
The short answer is intelligence. A better term for today's CIO role might be Chief Intelligence Officer. Enderle describes the distinction plainly: "The job is less about moving information across a network and way more about generating actionable intelligence and automation. The conventional CIO focused on the information itself, storing it, securing it and so on, while the new role focuses on the intelligence: What AI can actually do with that data to make the company smarter and faster?"
Whether the actual job title changes is almost beside the point. The scope and scale of the work, and the base nature of the job function, already have, whether enterprises realize it or not.
Ask a CIO what their job is today and the answer would likely sound significantly different than it might have just five years ago. Data governance. AI strategy oversight. Automation architecture. Risk modeling. These responsibilities were once the province of specialized teams such as data scientists, compliance officers and enterprise architects operating in functional silos with limited executive visibility. Now they are front and center on any given CIO's agenda, because they are a keystone of how the enterprise actually competes.
"It's a perfect storm," Enderle said of the forces converging behind this shift. "You have a massive push for operational automation; the sudden accessibility of GenAI; an absolute explosion of unstructured data; and intense pressure from the board to actually monetize that data instead of just sitting on it."
Strategically, AI now serves a dual role inside the enterprise: both as a driver that transforms customer relationships and business models, and as a supporter that enhances internal processes. CIOs who see their day-to-day work only through the second lens are likely to miss the implications of the first entirely.
This is not to say CIOs have simply been handed more responsibilities. The underlying nature of the responsibilities they now need to manage has changed. Managing IT infrastructures and apps is an operational problem that revolves around relatively objective success criteria such as uptime, latency and cost per transaction. Stewarding enterprise intelligence, let alone at scale, is a strategic problem that entails significant ambiguity and consequential trade-offs.
It requires C-level leaders to ask themselves questions like: What data should the organization collect and retain? Which decisions should be delegated to automated AI tools and which require humans to step in and apply personal judgment? How should AI outputs be audited when the reasoning behind the decisions they make is so often opaque? And who should be held accountable when an autonomous agent or solution makes a consequential mistake?
These are not always purely IT-related questions. They are leadership questions that require technical fluency to answer, which is precisely why these concerns have landed on the CIO's desk.
Why Is Data the Foundation of Everything?
Clean, well-structured data is the raw material that enterprises use to build intelligence and identify opportunities for action. If there is one common thread running through every successful AI transformation effort, it is this: the organizations that benefit most from AI are not those that use the most cutting-edge solutions or the most sophisticated models. They are the most data-literate enterprises and have the most coherent data at their fingertips. The CIO is now the primary steward of that material, turning it into an actionable strategy.
"Clean up your data,” Enderle said bluntly in his advice to CIOs addressing this transition. “AI is useless if it's a mess, so get unstructured information organized and secure."
The Nutanix masterclass reinforces the same point from a structural perspective, highlighting the exponential growth of data flowing through modern organizations and the way that explosion, paired with falling compute costs, has made the need for AI governance, oversight, and adoption both more feasible and more urgent than ever.
The CIO's relationship with data has to change. Under historical business operating models, data was a byproduct of sorts, something generated by business processes and stored for later research or reporting. Under an intelligent enterprise operating model, data becomes a strategic asset that must be actively curated, governed and cultivated at every turn. Which data exists and where; what quality level information possesses and how that quality is maintained; who can access what details, under which conditions and regulatory frameworks. These are questions a CIO must answer, along with thinking about ways to architect IT systems so that information cleanly flows between departments and tools, and how to create the feedback loops that empower processes to improve over time.
Enderle observes that leading organizations have already recognized where accountability for such responsibilities must sit.
"Leading companies are pulling AI and data governance tasks out of siloed departments and consolidating them under the CIO, often teaming them up directly with a Chief Data Officer," he said.
What Kind of Governance Do AI Solutions Require?
AI capabilities, especially AI agents, require rigorous governance policies. One of the most consequential shifts under the CIO's expanded role is the move from governing software to governing AI solutions, and recognizing that the two are not the same challenge.
Software typically behaves deterministically. Given the same inputs, it produces the same outputs. You can test it, certify it, and largely trust that it will behave in production the way it behaved in the lab. AI solutions are different. They are probabilistic, context-sensitive and, in the case of large language models, capable of generating novel outputs that no one explicitly programmed. Agentic AI systems go one step further, acting autonomously across multi-step workflows, making decisions and triggering downstream actions without human review at each step.
Managing these solutions is not always easy. Enderle points out that even getting a basic handle on every IT tool that impacts the organization is one of the biggest concerns of the governance challenge.
"The biggest headache for CIOs right now is shadow AI, and having to worry about employees using unvetted, consumer-grade tools for company work," Enderle said. "Leaders need to prioritize locking down data privacy, preventing IP leakage, ensuring models aren't hallucinating or biased, and setting up strict compliance guardrails so the company doesn't end up in a lawsuit."
His recommended approach balances these risks against the need for speed, innovation and experimentation.
"The best play here is building a walled garden," Enderle said. "Give employees a secure, internal sandbox where they can experiment with GenAI safely on internal data, but put strict governance gates in place before anything gets pushed to production or touches real customer data."
The CIO who can build and maintain such governance frameworks, one who can explain them to regulators, defend them to the board and update them as demands evolve, is not just managing risk. Such leaders are also building organizational trust in AI systems, which is itself a competitive asset in industries where customers and partners are closely watching how AI is being used.
How Does Automation Strategy Become Business Strategy?
Automation now flows through every department, not just IT. Alongside data and AI governance, the CIO's third emerging responsibility is automation strategy, which flows most directly into the business's operating model. Automation is no longer limited to IT workflows. Agentic AI tools and generative solutions now impact virtually every department from finance to HR, legal, supply chain, customer service and sales.
Each of these functions is discovering that large categories of its work, document review, scheduling, forecasting, and compliance checking, can be handled faster and at lower cost by intelligent systems.
What that looks like at scale is visible in the work Ursula Soritsch-Renier has led as group chief digital and information officer at Saint-Gobain. The company's AI transformation efforts have produced a range of concrete results. Machine learning reduced gas consumption across multiple gypsum plants. Digital twins delivered energy savings. A forecasting system improved accuracy by double digits. GenAI legal and HR chatbots cut document review time by 7x and saved around 50 emails per month per user. Soritsch-Renier attributes GenAI's value to three distinct drivers: individual productivity gains, collective productivity improvements and the potential to invent entirely new business models.
The biggest mistake a modern CIO could make, she warns, is treating the whole endeavor as a technology deployment rather than a systems-thinking project.
"You can't treat AI like a standard software rollout," Soritsch-Renier said. "If you just plug an LLM into a broken, messy process, all you get are bad results generated much faster."
The CIO is the natural owner of enterprise automation efforts, not because automation is a technology problem, but because only the CIO has the cross-functional visibility and technical depth to see the whole system strategically and govern it coherently. Leading executives here are not waiting for business units to automate and then working retroactively to clean up the resulting complexity. They are proactively building the enterprise-wide automation architecture and IT process map that allows an overarching business operating framework to hold together.
What Kind of Leader Does the CIO Role Now Demand?
The CIO role benefits from someone who is outward-facing and strategic. All of this demands that C-suites embrace a different kind of leader. The historical CIO operating model was largely inward-facing: optimizing the stack, managing vendors, maintaining uptime and maximizing the budget. The emerging operating model for tomorrow's leaders is more outward-facing and strategic, crafting how the enterprise uses intelligence and the data it produces to better compete, grow and serve its customers.
Enderle describes the new C-suite dynamic that has emerged around this repositioning.
"The CIO is basically the C-suite's new co-pilot," Enderle said. "They're working right alongside the CEO on new business models, partnering with the CFO to figure out the actual ROI and productivity gains of these tools, and teaming up with the CHRO to upskill teams and calm everyone's automation anxiety."
The human elements of change management are as vital to the CIO's mandate as any technical capability.
"They need serious business acumen and change management skills now, not just technical chops," said Enderle.
Tomorrow's leaders need both the capability to map tools directly to business outcomes and the capacity to manage the cultural transformation challenges that so often accompany automation.
Tomorrow's Chief Intelligence Officer will not be judged on how quickly and cost-effectively they deploy AI. They will be gauged on whether they deployed it wisely, building enterprise intelligence that was not just fast and capable, but trustworthy, governable and durable.
Enderle is clear about what to expect from future leaders in the space. "The most successful CIOs will be defined by how well they monetize data, deploy automation and drive corporate strategy," he said. "The traditional stuff like on-premise infrastructure, hardware maintenance and routine software patching will become totally commoditized or outsourced."
For executives who once hung their hat on their technical chops, that is a far harder job than keeping the proverbial ship running. It is also one of the most strategically consequential roles tomorrow's management leaders could hold, and one that any technology leader who loves a good challenge is sure to relish.
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Scott Steinberg is a business strategist, award-winning professional speaker, trend expert and futurist. He's the bestselling author of Think Like a Futurist; Make Change Work for You: 10 Ways to Future-Proof Yourself, Fearlessly Innovate, and Succeed Despite Uncertainty; and Fast >> Forward: How to Turbo-Charge Business, Sales, and Career Growth. Find him at www.FuturistsSpeakers.com and LinkedIn.
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