CIOs bring AI transformation home to IT workflows

Mike Anderson gave his IT workers an unusual task: Create a Gemini Gems digital twin of your role, feeding the AI details such as technical documentation to learn about the role’s tasks and knowledge needs.

Anderson wants these AI creations to assist the human workers in doing their jobs by helping them access the right information in near real-time with just a query.

“We created these Gems that act as experts our team can lean on, and my goal is for each worker to get some time back,” says Anderson, chief digital and information officer at security tech company Netskope.

It’s just one of many ways Anderson is trying to transform workflows and processes inside his department to boost its efficiency and productivity. And he’s seeing wins.

For example, development teams are using AI to generate code. Workers use vibe coding to quickly develop “something to iterate on,” slicing months of work off a typical product development schedule, Anderson says. As part of the transformation, Anderson’s team is creating primitives to ensure certain elements, particularly security controls, will always be part of the AI-generated code, another workflow transformation to save IT workers time.

Although Anderson hasn’t calculated a detailed ROI for such efficiency gains, he says it’s clear he can do more with less as a result. “I’m able to maintain a flat budget and deliver more things and more capabilities than I could before,” he says.

‘Do more with the team we have’

CIOs have long felt the pressure to do more with less. And they’re feeling that pressure acutely today. According to survey findings from research firm Gartner, 57% of CIOs face pressure to improve productivity and 52% to reduce costs.

CIOs also have a mandate to use technology, especially AI, to transform workflows across the business to deliver productivity and efficiency gains. They also are seeking to deliver as much in their own IT departments.

“We want to make sure we’re daring to reimagine IT processes and what’s possible with AI to unlock value,” says Anisha Vaswani, chief information and customer officer at Extreme Networks.

Vaswani has put transformation of IT workflows front and center. Like Anderson, she’s using AI (specifically Claude Code) to speed coding. She has adjusted workflows, shifting workers from writing code to prompting, reviewing, and managing quality.

She is also transforming help desk operations, as many CIOs are, using AI and automation to increase self-service options.

More complex workflows are benefitting as well, says Vaswani, who is using AI to scale IT’s QA function by generating test strategies and automating testing. “There is a lot of promise there to reduce to minutes what could take weeks manually,” she says. She sees AI’s use as a way to add capacity without increasing costs.

And she’s exploring how IT teams can use AI to better capture user requirements when working on new products or enhancements.

“I want to reimagine how IT interacts with our business partners to be more responsive and agile, so we can deliver value more frequently and be a lot more customer-centric,” she adds. “The goal is to do more with the team we have. We want to innovate faster, to deliver more, to get more done.”

Transformational mandate

Alex Wyatt, a director at consultancy West Monroe, says IT’s process-driven work is ripe for transformation.

“AI has re-sparked the conversation around that,” he says. “Now with AI CIOs are getting more pressure to cut costs, and boards are saying, ‘This process has to get 50% more efficient.’”

As is the case throughout a typical organization, CIOs can — and should — go after the easier transformation tasks first to chalk up wins and build skills before tackling harder goals, Wyatt advises.

“There are different stages with optimizing your workflows and processes,” he says.

The first stage is using AI to automate repetitive tasks and shift humans to oversight functions. The stage also involves maximizing the capabilities that system providers have incorporated into the tools and technologies that IT uses to get work done.

“That’s the lowest hanging fruit and where you can get the biggest bang for your buck in the shortest amount of time,” Wyatt says. “And then you go after the more sophisticated opportunities that exist.”

Although Wyatt says AI has pushed workflow and process transformation into the limelight, “it doesn’t mean AI is the only solution.” He reminds executives that “there are opportunities for pure process improvement,” like lean process design.

“There is a risk of automating a bad, inefficient process, so you have to think about outcomes, the KPIs you’re driving, and how you restructure work to achieve those,” he adds. “You don’t get more efficient by buying more tools. You have to rethink your workflows. You have to think about how people work.”

That longstanding advice has proven its worth through the decades. Aggressive workflow and process redesign can deliver significant gains — well over 50% improvements — “but to get that you really have to think about how work gets done and have the systems in place to do that,” Wyatt says.

Not all CIOs are able to put in the amount of work it takes. That shouldn’t deter CIOs from doing something, he adds. “You can get a 10% to 20% lift from doing some basic process redesign and then use AI to get you even more lift,” he notes.

Ross Tisnovsky, a partner at Everest Group and leader of the firm’s CIO research and advisory practice, stresses the transformation component, saying CIOs can encounter problems if they automate without it.

Efficiency gains in coding/development and testing are case in point, he says, noting that AI is boosting efficiency in coding by 70% or more, while on the testing side it’s closer to 30%. As a result, CIOs who don’t remake workflows soon find they’ve created an imbalance, with code being produced faster than testing can handle.

As such, Tisnovsky suggests, the reason most AI initiatives don’t deliver value often stems from failure to rework the workflows.

Dual pressure and desired outcomes

CIOs face other challenges in transforming how the IT department works, Wyatt says.

To start, they and their IT teams are fully engaged in doing such work for all the other departments in the organization, with priority typically given to transformations that boost revenue, market share, customer retention, and the like.

“IT is in a unique position: They’re being asked to do transformation across the organization as well as in IT. They have that dual pressure,” he says.

That can challenge CIOs’ ability to allocate the resources and skills needed to redesign IT workflows, Wyatt says.

CIOs also find it hard to get rid of embedded workflows. “There is a lot of work that if you were to build from scratch, you’d do it a different way, but with legacy workflows it is hard to get the momentum to change. It takes a lot of time and money to reengineer,” Wyatt explains.

He has found that leading CIOs overcome such challenges the same way other execs do: putting together business cases for the transformation, focusing on desired outcomes, articulating the value those outcomes will deliver, and using all that to get resources to do the work.

“And they look to rework workflows as opportunities present themselves,” Wyatt adds.

Tisnovsky says as all that happens, CIOs will begin transforming more complex workflows, such as those in the infrastructure space and in the IT knowledge base.

Empowering workers to transform their tasks

Patrick Phillips, CIO of tech company Vasion, is drawing on his process-improvement experience and his workers’ insights to transform his IT department’s workflow, knowing AI alone won’t create maximum efficiencies.

“The process itself has to be completely redefined, so you’re not bolting AI onto legacy processes,” he says. “So I’m asking what if we were building the process today with AI-native tools, what would it look like?”

Phillips has tasked his workers to identify workflows that are primed for transformation, such as those filled with commodity-level tasks.

“Our expectation is that they’re going to consider transforming how they work, and we have the obligation to help them do that by providing the tools and trainings and the empowerment for them to rebuild workflows from ground up,” he says.

For example, Phillips enlisted help-desk staff to transform how that team operates, equipping them with Cursor, an AI-powered code editor designed for software development, and challenging them “to build the help desk just like you think it should be built.”

“They knew what bugged them, and so they had the incentive to make their jobs easier,” Phillips says. “They want to make themselves more efficient because they want to do things that are more valuable and more interesting than resetting a password.”

Phillips says the help-desk staff reworked workflows, boosting efficiency and enabling them to shift time to other responsibilities such as participating in planning meetings.

Instituting a culture of continuous improvement

Ha Hoang, CIO of Commvault, maker of a data protection and cyber resilience platform, says taking on such work is an imperative for CIOs.

“CIOs have historically been very focused on transforming business workflows — sales, finance, customer support — because that’s where the visible ROI is,” Ha says. “But IT has often been the cobbler’s children. That’s changing now, and it needs to. If IT is going to lead transformation, it has to model it. You can’t be pitching automation, AI, and efficiency to the business while your own teams are buried in tickets, swivel-chair processes, and manual handoffs.

“So yes,” she adds, “CIOs should absolutely be putting the same rigor on internal IT workflows. In many cases, that’s actually the fastest path to credibility and cost efficiency.”

AI, generative AI, and now agentic capabilities have prompted Ha and her IT team to rethink workflows entirely, not just optimize them.

“Before AI, we were asking, ‘How do we make this process faster?’ Now we’re asking, ‘Why does this process even exist?’” she explains.

That has led to transformations in various areas.

As is common, Ha and her team started with transforming help-desk workflows, where they have deployed AI self-service and virtual agents, automated ticket triage and routing, and enabled auto-resolution for common issues. The results are fewer tickets reaching IT staff, faster resolution times, and a shift from reactive support to higher-value work.

Then they started looking for transformation opportunities across core IT workflows.

For example, they’re moving to fully automated, policy-based access provisioning with minimal manual approvals. They’re using data and AI to streamline low-risk changes and reduce bottlenecks in change management. And they’re deploying AI-powered search and assistants to eliminate silos and speed issue resolution in knowledge work and troubleshooting.

Ha says these changes are just the start.

“For me, it’s become a continuous discipline, not a one-time initiative,” she says, noting that might be one of the most significant work transformations. “I think the biggest shift isn’t technology, it’s the mindset.”