Getting the future exactly right isn’t nearly as important as being ready for it.
At Gartner’s IT Symposium/Xpo, Distinguished VP Analyst Daryl Plummer opened the firm’s top strategic predictions for 2027 and beyond with a joke about a man visiting a psychic. When he knocked on the door and someone inside asked, “Who is it?” he turned around and left.
Knowing exactly what comes next isn’t always possible.
But as Plummer explained, the goal is to put technology leaders on the right path early enough to act.
Gartner’s ten predictions explore what’s ahead, along with the next best actions CIOs should take and the next worst moves they should avoid.
AI Coworkers Are Coming, but Replacement Isn’t the Goal
Forget the humanoid robots of science fiction. Physical AI is already embedded in everyday life, from smartwatches to vehicles that automatically brake to avoid collisions.
By 2030, Gartner predicts 80% of frontline workers at international companies will be assisted by physical AI systems.
“Don’t think replace workers, think augment and extend.”
The right move is investing in adaptable systems that help employees work more effectively. The wrong move is assuming robots will deliver returns simply by reducing headcount.
Autonomous AI agents present another challenge. Gartner predicts more than 10 million agents will clog public services by the end of 2027.
One example involved an agent that secured a gym appointment by canceling other people’s reservations. When instructed to restore them, it couldn’t.
The recommended response is deploying guardian agents that can identify and stop unauthorized activity rather than allowing autonomous systems to operate unchecked.
AI Costs Are Becoming a Security Problem
AI spending isn’t just a budgeting issue anymore. It’s a cybersecurity concern.
By 2030, Gartner predicts 80% of organizations operating public-facing AI will experience cost-exhaustion attacks designed to drive up consumption and expenses.
During the presentation, uncontrolled AI usage was compared to giving teenagers mobile phones without understanding what happens when their free minutes run out.
Suddenly, there’s a $2,000 bill.
Organizations face similar risks with token consumption, repeated requests, and unnecessarily powerful AI models.
Gartner expects 60% of organizations to establish dedicated AI cost-to-value functions by 2029, while 60% of Fortune Global 500 companies will implement AI token operations controls by 2028.
The next best action is establishing usage limits, monitoring inference costs in real time, and connecting AI spending to business outcomes.
The mistake is focusing exclusively on cutting costs or waiting for perfect measurement systems.
“Cost reduction is the denominator. Value is the numerator.”
Both matter.
Energy and Accountability Demand New Thinking
AI’s growing appetite for energy is creating another challenge.
Gartner predicts major enterprises will increasingly become energy providers themselves by 2030, selling excess capacity to public grids and AI data centers.
To put AI’s energy demands into perspective, Plummer had everyone turn on their phone flashlights and wave them overhead. He then explained that it would take roughly 1,000 people doing that for three hours to equal the energy consumed creating just one AI-generated dancing video shown during the keynote.
That’s a lot of energy for a dancing video.
And AI’s growing energy demands are making this an issue CIOs can’t afford to overlook. The right move is investing in real-time energy optimization. The wrong one is treating energy consumption as someone else’s problem in facilities.
Governance is changing, too.
By 2030, Gartner expects 80% of Global 500 companies to designate CIOs or Chief AI Officers as custodians of evidence documenting responsible AI practices.
For Paul Mohabir, Head of Information Technology at Transervice Logistics, that prediction raises an important question about authority and accountability.
“I wouldn’t consider an organization prepared if its CIO is expected to provide that assurance without visibility into AI across the business, named business owners, and the authority to pause unsafe deployments,” Mohabir said. “Making the CIO the custodian of the evidence must not make everyone else less accountable.”
The recommended approach is evaluating digital evidence management and AI governance technologies while ensuring accountability extends beyond IT.
Competitive Advantage May Not Last Long
By 2029, Gartner predicts 25% of Global 500 companies will innovate AI-powered offerings so rapidly that traditional fast followers cannot catch up.
A single entrepreneur supported by AI agents could become a serious competitor almost overnight.
Consider Blockbuster, which focused on stores and physical inventory while Netflix changed the business model entirely.
The right move is exploring how AI can reinvent customer experiences, not simply improve internal efficiency.
And software itself may become disposable.
Gartner predicts 80% of new applications will be intentionally designed for use lasting less than one year by 2029.
Vineet Rao, Principal Advisor and Fractional CIO at AION Strategy, sees this as a fundamental change in how CIOs manage technology.
“The work moves from maintaining software to governing software that platform teams and citizen developers build, use, and retire faster than manual review can follow,” Rao said.
That makes traceability essential, particularly knowing who built an application, what data it accessed, and when it was retired.
“Most organizations aren’t ready, because many are still proving returns on their first AI rollouts and have no lifecycle plan for software meant to expire,” Rao added.
Gartner’s recommended move is focusing on the speed and cost of creating and retiring applications. The mistake is assuming long-term stability and multiyear contracts will always be advantageous.
The Wrap
Gartner’s predictions cover a lot of ground, but one thing carries through all ten: CIOs have some important decisions ahead.
Whether it’s managing AI costs, keeping autonomous agents in check, or preparing for software that may only last a year, knowing what to do next matters just as much as knowing what’s coming.
And as Plummer reminded attendees, the dates won’t always be exact. What matters is getting on the right path with enough time to do something about it.
