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Cisco CIO Fletcher Previn, says advancements in AI are leading him to rethink workflows not just for Cisco Systems’ 10,000 IT workers, but also the broader employee base of around 90,400.
“There’s the bottom up inertia of people asking for access to tools, and then there’s the top-down inertia of saying, ‘Here’s how we see this role evolving,’” says Previn, who has served as chief information officer at the networking-equipment company since 2021. “You sort of have both trying to meet in the middle.”
Around 70% of the company’s 20,000 developers log into AI coding tools at least once per month. The acceptance rate for AI-generated code is around 24% compared with 4% nearly a year ago. “AI is getting better,” he adds. “It’s supporting more programming languages. Developers are getting more comfortable with it.” Over time, he hopes that as much as 70% of Cisco Systems’ code will be AI generated.
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Rethinking IT and non-technical roles
Previn is reevaluating the primary work done for each role, as well as job titles, the ways to reevaluate work with AI tools, and what future training may be required to support such big, sweeping changes.
Examples include using AI to do more intelligent onboarding, which allows for Cisco to more accurately assess exactly what tools or software are needed to support the role a new employee is hired for. Cisco Systems is also using AI for planning hardware updates. “Upgrading laptops is a significant amount of money at a company of our size,” says Previn. “And sometimes a lot of people are perfectly happy with the laptop they have.”
To attract talent, Previn says he prioritizes creating a workplace that encourages “emotional safety for people to be able to innovate and experiment and fail fast.”
“There’s a huge productivity loss when you’re kind of dynamically forming and un-forming teams by project,” asserts Previn, describing Cisco’s move to small, cross-functional teams supporting systems such as Workday, SAP, and Oracle.
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Balancing innovation and cost
Previn says Cisco Systems fields a lot of pitches from software-as-a-service providers to add on more expensive AI capabilities. “You can consume all of those things, but run the risk of controlled cost,” says Previn. “It can create employee experience confusion, similar to what we had when chatbots started to become a thing.”
He expects generative AI will evolve to an agent-to-agent world, where a digital workforce can perform tasks on behalf of employees. “The rate of innovation in AI is happening so quickly that if you find out your developers are using a language model that is six months old, then effectively, all the software you’re writing is already six months out of date,” says Previn.
