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It’s now or never:
Why the AI gap is widening
Global IT leaders surveyed for a new report highlight the risks—and consequences— of falling too far behind
04-08-26 | BY FAST COMPANY CUSTOM STUDIO
Most CIOs believe they’re ready for AI. But they might be wrong—and the gap between perception and reality is growing fast. That’s the sobering takeaway from 3,120 global IT leaders surveyed for the “CIO Playbook 2026: The Race for Enterprise AI.” The International Data Corporation (IDC) survey, commissioned by Lenovo, revealed that nearly all (93%) anticipate real ROI as deployments move beyond pilots, averaging $2.79 in value for every dollar spent. And with 96% planning to increase AI investment this year at an average growth rate of 13%, the hard pivot away from productivity gains toward full-blown enterprise transformation is well underway. But for firms still testing the waters or struggling to scale pilots, these numbers are less of a validation than a warning: The rest of the market isn’t waiting—they’re sprinting away.
Their lead will only widen with the imminent arrival of agentic AI—systems increasingly capable of sensing, reasoning, and acting without human supervision. Agents automating tasks in areas such as cybersecurity, customer service, and quality control will free up resources that can be reinvested elsewhere, spinning the flywheel even faster. But while CEOs are champing at the bit, only one in five firms (21%) reports significant agent usage today, and more than two-thirds (70%) of early-stage organizations—those exploring piloting or deploying agentic AI in a limited manner—report that they are at least a year away from deploying at scale. CIOs’ reach is in danger of exceeding their grasp, with little more than a quarter (27%) having governance frameworks in place, while an overwhelming majority (84%) of organizations prefer the leverage on-premises or edge deployments for AI workloads and applications as part of a hybrid deployment environment.
AI readiness isn’t just about
pilots or proofs of concept; it’s about building the right foundation.
Ken Wong
President, Solutions & Services Group, Lenovo
“This study signals a clear inflection point for enterprise AI,” says Ken Wong, president of Lenovo’s Solutions & Services Group. “Many organizations thought they were ready for AI, until they tried to scale it and realized how much they’d underestimated what ready really means. Early efforts stalled because companies optimized for experimentation instead of execution. AI readiness isn’t just about pilots or proofs of concept; it’s about building the right foundation.”
The “CIO Playbook” captures how this has played out in practice. Too many organizations optimized for experimentation while overlooking the fundamentals—i.e., data readiness, security, governance, and the operational scale required to run AI agents across the enterprise. Now, as intelligence is pushed further to the network’s edge, closer to where data lives and decisions are made, CIOs are rethinking their approach across devices, infrastructure, and services before those blind spots become permanent liabilities.
“Lenovo helps CIOs address those gaps end to end,” Wong adds. “From edge to cloud to data center, our AI portfolio brings together infrastructure and services designed to make AI deployable, manageable, and secure at enterprise scale.”
A PUSH FOR PROFITS
CIOs’ big rethink is apparent in the inversion of their priorities. A year ago, improving employee productivity topped their agenda; that’s since fallen to the bottom behind a renewed push for profits and digital transformation. AI adoption is accelerating beyond IT and moving into higher-value business functions.
The number of organizations planning to leverage AI in corporate finance is expected to double, with significant increases also seen in marketing and sales, where adoption rates are projected to rise by more than 80%.
As AI spending moves beyond IT, CIOs seek to accelerate adoption. Lenovo has built AI-ready infrastructure solutions to help teams across various functions of a business build expertise as they deploy real-use cases in their own environments. Services such as Lenovo AI Discover for strategy development and Lenovo AI Fast Start for rapid deployment help organizations shift smoothly from proof of concept to production. They’re reinforced by the Lenovo AI Library, a portfolio of customized use cases for deploying at scale across hybrid and edge environments while reducing risk and complexity.
The mismatch between ambition and readiness is driving the most significant architectural shift in enterprise computing since the advent of the cloud two decades ago. Only 16% of CIOs polled are still all-in on public clouds, while the majority (62%) favor a hybrid approach that balances cost, latency, and security.
As AI moves into production, enterprises are realizing not every workload belongs in a centralized cloud environment.
Ashley Gorakhpurwalla
President, Infrastructure Solutions Group, Lenovo
“We’re not seeing this as a permanent structural shift away from public clouds, [but rather], a rebalancing,” explains Ashley Gorakhpurwalla, president of Lenovo’s Infrastructure Solutions Group. “As AI moves from experimentation into production, enterprises are realizing not every workload belongs in a centralized cloud environment. Latency, data governance, cost predictability, and security all matter more when AI systems are embedded directly into operations.”
To better meet the need of customers regardless of size, Lenovo has positioned its portfolio around this shift with hybrid, edge-to-cloud infrastructure optimized for inference workloads, scalable edge deployments, and flexible architectures allowing enterprises to run agentic AI where it delivers the most value.
RAISING THE STAKES
This rebalancing extends to end users as well. As organizations grapple with governance gaps—a lack of responsible AI practices and poor data security are among CIOs’ top concerns—AI-powered PCs and other edge devices are becoming a critical piece of the puzzle.
“AI fails when it never reaches the people who are meant to use it,” says Luca Rossi, president of Lenovo’s Intelligent Devices Group. “Our research shows that 84% of enterprises already want AI running closer to where data lives, and nearly a third are prioritizing AI devices to make that shift real. AI PCs, smartphones, and edge systems are where intelligence becomes usable—where employees can trust it, govern it, and actually put it to work in their daily decisions.”
AI DEPLOYMENT
CIOs surveyed that . . .
93%
. . . Anticipate real
ROI as they move beyond pilots
21%
70%
. . . Are more than
one year from deploying at scale
The stakes will rise further when AI agents enter the chat. Operating autonomously in the background—monitoring systems, managing customer relationships, and executing tasks—agents will need to read, write, and act upon firms’ most sensitive data. In the near term, this places the onus on CIOs to upgrade governance procedures and security; over time, it promises to redesign workflows from scratch.
“Agentic AI introduces a new set of real-time infrastructure requirements,” Gorakhpurwalla says. “Low latency, continuous availability, and tighter integration across compute, data, and orchestration layers have all become mission-critical.”
THE PATH FORWARD FOR CIOS
With global electricity costs soaring, performance-per-watt has become more important than raw compute. The IDC predicts that by 2027, 80% of enterprises will deploy distributed edge infrastructure specifically to improve latency and responsiveness, not to mention energy efficiency. When power is the bottleneck, competitive advantage goes to firms finding ways around it with models and hardware specialized for the task at hand.
As AI becomes operational
at scale, the real question for CIOs shifts from where AI runs to how
people experience it.
Luca Rossi
President, Intelligent Devices Group, Lenovo
“As AI becomes operational at scale, the real question for CIOs shifts from where AI runs to how people experience it,” Rossi says. “We’re moving toward one personal AI that works seamlessly across devices—PCs, smartphones, tablets—carrying context and intent with the user. When intelligence follows people instead of platforms, organizations can power every employee, secure workflows by design, and put AI exactly where the work happens.”
For AI, it’s a sign of growing maturity. For CIOs, the real work lies just ahead. It’s now or never for firms to seize the moment before the future zooms out of reach.
Explore the full findings from Lenovo’s “CIO Playbook 2026: The Race for Enterprise AI.”
. . . Are using AI significantly today
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