For many years, CIOs have chased incremental enhancements in IT productiveness. However what if the way forward for work isn’t about 10% or 20% features, however about 10Xing human potential? At Cisco, we consider that the longer term is already right here.
Since becoming a member of Cisco as CIO in 2022, our purpose for Cisco IT has advanced from doubling throughput to an bold 10X improve in productiveness, remodeling us into an innovation engine. As CIO, I see AI not as an incremental achieve, however because the engine to realize this 10X human potential to empower our individuals and rework IT in addition to our firm tradition. We’re accelerating this by combining machine studying (ML), generative AI (GenAI), and agentic AI to optimize IT operations and create proactive, customized worker experiences. Our IT technique is constructed on Agile, AI, and Person Expertise.
Fletcher Previn, CIO of Cisco, on AI, productiveness, and the way forward for work
An IT framework constructed for AI
To remain true to our technique and lean into our imaginative and prescient, we developed a tangible framework for an AI-ready workforce, relevant to any group.
It began with a complete, job-by-job evaluation throughout our 19 IT job households, encompassing over 10,000 workers.
For every position, we systematically requested:
- What’s the present headcount?
- What are the first duties?
- What’s the AI potential?
- What particular AI instruments are wanted?
- What coaching and reskilling will uplevel our workforce?
- And critically, what are the important thing metrics to measure success?
This blueprint recognized potential productiveness features, the mandatory tooling, and the particular coaching and expertise required for each position.
Creating pleasant worker experiences and growing productiveness
This strategic method is already yielding unimaginable outcomes. In software program growth, AI-first engineering with instruments like GitHub Copilot reveals a 3X improve in output, shifting from human coding to human assessment. Throughout all IT capabilities, we’re seeing 30-50% productiveness features, projected at 36% general, with out sacrificing high quality. These numbers are based mostly on the present state of AI tooling—and they’re solely going to enhance.
“These additionally aren’t simply efficiencies; they’re about creating pleasant worker experiences by automating mundane duties, permitting our individuals to give attention to doing one of the best work of their lives.”
We’re additionally utilizing AI to boost and ease the {hardware} updates for our workers by detecting a laptop computer’s reminiscence, software efficiency and community telemetry to decipher between efficiency issues that may be fastened by the IT workforce versus when a tool might fail and can should be changed. All of that is about enhancing the worker expertise to chop down on friction and create a extra constructive, enabled working surroundings so workers can do one of the best work of their lives.
A deeper take a look at our methodology
With the rollout of AI-powered engineering instruments—together with our inner AI assistant—we’ve entered a brand new period of scale. And we’re simply getting began.
Right here’s how we’re eager about it:
Developer Expertise
- Upskilling with AI-first content material and training
- Rising a robust AI engineering group
- Measuring what issues: Pace, High quality, Expertise, and Affect
- Celebrating daring thinkers and early adopters
Agile, Accelerated
- Redefining groups: 2 professional AI first engineers + AI brokers
- Understanding the enterprise want, having the fitting nicely formed work within the pipeline
- Prioritizing pace, iteration, and ease
- Automating testing, high quality, and launch pipelines
- Shifting from upfront design to AI-enabled experimentation
AI-First Engineering
- Unblocking entry to AI platforms and instruments
- Utilizing our inner AI assistant for engineering, safety, and ops
- Managing agent identification and entry clearly
- Monitoring mannequin utilization and optimizing outcomes
We’re nonetheless early on this journey, however the outcomes are actual—and accelerating.
A cultural basis constructed on our personal AI-ready infrastructure
An AI-ready workforce (individuals and course of) requires an AI-ready infrastructure (expertise) to really ship on its potential. The blueprint tells you who wants AI, what instruments, and what coaching, however these instruments and educated individuals want a sturdy, high-performance, and safe basis to function successfully.
We’re not solely leveraging AI to boost the worker expertise, however Cisco IT additionally companions with enterprise models inside Cisco to construct the AI infrastructure that supercharges the worker expertise throughout the enterprise.
“We’re doing this by profiting from our personal Cisco tech stack to construct a sturdy AI infrastructure.”
It consists of low-latency materials connecting compute, storage, and GPUs, managed by a management airplane. This entire Cisco stack, usually leveraging Nvidia GPUs, types a shared AI material throughout the corporate, offering validated designs for our clients.
Finally, we all know our success hinges on our individuals and our tradition. Inside Cisco IT, we consider the way you get issues completed is as vital as what you get completed. At Cisco, we’re not simply speaking about AI; we’re constructing, securing, and making it work, each single day for ourselves, our clients and our companions.
