In 2025, enterprise technology executives faced immense pressure to help their businesses reap the rewards of sustained focus on AI. Most made inroads, honing their approach to project prioritization and dodging AI washing from vendors.
CIOs are still experiencing AI-related hiccups, however. The fragmented, shifting AI regulation landscape and macroeconomic headwinds will continue to push technology executives toward skepticism and scrutiny.
The effects of growing AI adoption are still emerging, with some CIOs expecting next year to bring changes to workforce strategy. Agentic AI, which gained enterprise traction this year, is one of the leading drivers, although success was rare in 2025.
The technology still has a ways to go before it can run loose in enterprise environments, but 2026 could bring agentic AI much closer to vendor aspirations.
Here are five predictions that technology leaders expect will shape AI strategies for 2026:
1. AI agents gain some ground, but still face implementation challenges
CIOs are anticipating agentic AI to still dominate conversations in the year ahead. Talk will turn to action in some cases, although true transformation is likely to be more distant.
“Traditional players — Salesforce, ServiceNow, Pegasystems — their systems are based on workflows, and that’s going to be an area where agentic AI really takes off,” Citizens Financial Group CIO Michael Ruttledge told CIO Dive.
More enterprises are using AI agents each quarter, but project maturity varies and widescale deployment is minimal.
Vendors still need to convince CIOs that their agentic offerings work as advertised, according to Kris Lovejoy, global practice leader of security and resiliency at Kyndryl.
“For the next six, eight months, it’s still going to be a lot of, ‘Prove to me that this can work effectively,’” Lovejoy said in a November interview.
Enterprises that move forward on initiatives will likely run into unintended consequences, Lovejoy said, and cautious organizations will need to answer questions around trust and compliance before jumping in.
“The use cases that we're going to see are not going to be large-scale transformation,” Lovejoy said. “They're going to be more business process transformation focused, which is not a bad thing.”
Bolt-on AI assistants will become enterprise table stakes as AI agents evolve.
“The era of copilot-only models fades as organizations adopt agentic systems that deliver outcomes rather than suggestions,” Andie Dovgan, chief growth officer at Creatio, said in an email.
2. AI-driven productivity gains for software engineers will open new doors
Enterprises expect to reach significant productivity gains in the year ahead as strategies and use cases mature. Some leaders predict these uplifts will open the door and fuel more in-house projects.
“There’s going to be a bit of a pivot toward homegrown solutions versus vendor solutions,” Ruttledge said. “Certainly, if we’re getting 5x productivity growth, which is what we’re predicting for next year, then you want those engineers to be your engineers, not paying a vendor for that.”
The shift is coinciding with a sharper focus on the value AI can — or cannot — bring.
“For some, AI is about being a productivity enhancer,” Skillsoft CIO Orla Daly said. Leaders have to consider if just boosting productivity is enough of a reason to pursue a use case, she added. If the answer is yes, the question then becomes what do leaders want to do with the time saved.
Industry experts have previously warned companies that a lack of clarity around AI use could lead to more busywork. CIOs will play a vital role in helping the business navigate the change as AI tools continue to deliver productivity boosts next year.
3. IT leaders will spend more time talking about trust
With generative AI tools deployed and AI agents becoming more enterprise-ready, CIOs spend more time talking about trust in the year ahead. Trust is intertwined with security and responsible AI practices as well as the reliability of tools.
“Organizations want AI they can depend on to act predictably, explain its decisions and stay accountable as it takes on more work,” Dorit Zilbershot, group VP of AI innovation at ServiceNow, said in an email. “As companies build out their AI architectures, trust will become the common language that shapes how and where agents are deployed.”
For enterprises to capture the potential of AI agents, they need to feel confident that they can use them in real operations, according to Zilbershot.
“AI agents built on a foundation of proven, deterministic workflows will ensure every action is grounded in predictable, governed and auditable logic,” Zilbershot said. “This will open the door to a new era of enterprise-grade agentic automation where organizations scale faster because they trust the agents doing the work.”
4. CIOs will deploy more scrutiny to potential AI use cases
Gone are the days of enterprises trying to pursue every potential application of AI.
“We’ve already shifted from last year where there was a lot of excitement and experimentation,” Daly said. “Now it’s about bringing value and creating impact. Next year will be a continuation of that.”
CIOs will more seriously scrutinize potential AI opportunities, triaging projects to pursue what will work. “It’s a bit of a reality check,” Daly said.
The increased scrutiny will occur alongside demand for strengthened governance practices to better shepherd projects. Forrester predicts 60% of Fortune 100 companies will appoint a head of AI governance in 2026.
Organizations that ramp up agentic exploration will especially benefit from the increased focus on governance.
“There’ll be a need for more rigor,” Ruttledge said. “Testing is going to need to be very robust.”
Vendors will have to grapple with rising enterprise expectations, too.
“Governance will be integrated into every part of the product, and not just bolted on at the end,” Ravi Krishnamurthy, VP of AI platforms at ServiceNow, said in an email. “Products that embody this principle will outpace their competitors in customer adoption and value delivered.”
The fragmented state of AI regulation is also pushing businesses to think critically about how they’re deploying AI. Gartner predicts that by 2027, enterprises will invest $5 billion in compliance efforts.
5. IT decision-makers will rework workforce strategies as AI adoption changes responsibilities
Since the start of the current wave of AI innovations, industry experts and technologists have posited a barrage of theories on how the technology will affect workforce strategies.
In the tech vendor landscape, executives have shifted staff toward supporting AI endeavors and cut support for other projects. All industries have accelerated hiring for AI skills.
But analysts and technology leaders expect next year will require CIOs to rework their workforce strategies in a much more comprehensive way. Forrester, for example, predicts enterprises dabbling in agentic capabilities will reduce their data team headcount by 25% next year.
While AI-driven workforce reductions can certainly leave a sour taste, others aren’t so sure about the breadth of disruption. Gartner predicts AI’s impact on global jobs will remain neutral through next year.
“There are certain roles, like customer support, that are more prime for displacement, but I think it’s a relatively short list,” Daly said. CIOs, however, will need to think about organizational structure regardless of whether they view AI as a replacement, she added.
Skills assessments will serve enterprises well as they navigate untraversed terrain, enabling leaders to put workers in roles best suited to their talents. These assessments can also uncover areas of potential growth or needed improvement.
CIOs will also need to consider the impacts of every employee becoming an AI manager, according to Zilbershot.
“As autonomous AI agents take on more coordination, follow-through and cross-functional execution, workers at every level will be responsible for guiding, supervising and optimizing these digital coworkers,” Zilbershot said.
