Cisco's Journey in AI Workforce Transformation

[ad_1] One factor I hear constantly from enterprise leaders is that this: We imagine within the promise of AI, however we’re nonetheless determining how one can flip it into actual enterprise progress.

At Cisco, that is the journey we’re on. Over the previous 18 months, we’ve invested in AI instruments and studying experiences designed to assist individuals improve their work and ship measurable enterprise outcomes.

To grasp whether or not these investments are making a distinction, the Folks & Communities workforce stepped again and requested a much bigger query: When AI turns into integral to how our individuals work, how does it form engagement, efficiency, and progress throughout Cisco—and what does that imply for the enterprise?

Over the previous 12 months, Cisco’s Folks Intelligence workforce examined how staff have interaction with AI instruments, drawing on surveys, interviews, focus teams, and knowledge evaluation. The findings ship a transparent sign: our strategy is working—and when paired with a tradition that encourages studying, experimentation, and belief, the chances for our individuals and our enterprise are limitless.

Key Findings:

1. AI Powers a Higher Worker Expertise AI is greater than a device—its use positively impacts particular person engagement, retention, efficiency, and progress.

AI boosts particular person engagement: We’ve seen a strong, mutually reinforcing cycle emerge: engaged staff actively use AI, and AI use deepens worker engagement. AI customers who have been interviewed report better enthusiasm for Cisco’s mission, stronger confidence in our future, and really feel extra challenged and empowered to develop in comparison with their friends who don’t use AI. In addition they report having extra alternatives to make use of their strengths each day. AI strengthens retention: Opposite to claims that AI customers usually tend to go away, AI customers at Cisco keep longer—and use AI twice as typically every month as staff who exit the corporate. AI enhances productiveness and efficiency: Over 70% of staff surveyed report that AI helps them save time, enhance productiveness, and deal with routine work extra effectively. This enhanced productiveness seems to be contributing to efficiency, as staff who use AI instruments extra incessantly are likely to obtain barely larger Particular person Efficiency Issue (IPF) scores. AI accelerates profession progress: AI customers usually tend to be promoted quicker, spend much less time in the identical grade, and are 40% extra more likely to be designated Essential to Retain. These advisable for promotion use AI 50% extra typically than those that aren’t. These patterns counsel that Cisco is turning into a spot the place AI expertise aren't solely developed however rewarded.<img loading="lazy" decoding="async" class="lazy lazy-hidden wp-image-484111 size-full aligncenter" data-lazy-type="image" src="https://blogs.cisco.com/gcs/ciscoblogs/1/2026/01/AIResearch_Section1-e1767992472351.png" alt="An illustration of a woman working on a laptop with a small floating AI robot assistant, surrounded by icons representing data growth and successful task completion." width="800" height="316"/>

2. Driving AI Adoption Throughout Our Workforce Understanding what drives and hinders adoption helps us create the fitting atmosphere for studying and innovation.

Leaders who use AI amplify adoption: Staff whose direct leaders use AI are twice as seemingly to make use of it themselves. Prime-down modeling really issues. Even small actions like mentioning AI instruments in workforce conferences or 1:1s create alternatives to introduce sensible options, construct consolation, and normalize AI utilization. Versatile work environments assist AI utilization: Hybrid work and worker autonomy might assist extra AI utilization. Apparently, staff who select to return into the workplace three or extra days per week are extra seemingly to make use of AI instruments than their friends.<img loading="lazy" decoding="async" class="lazy lazy-hidden aligncenter wp-image-484112 size-full" data-lazy-type="image" src="https://blogs.cisco.com/gcs/ciscoblogs/1/2026/01/AIResearch_Section2-e1767992503649.png" alt="A split illustration showing an employee using AI at a desk on the left, and a leader presenting AI tools to an engaged group of colleagues on the right." width="800" height="380"/>

3. Designing Efficient AI Skilling Methods How staff study AI makes all of the distinction. Our findings reveal what works finest to maintain our workforce on the forefront of AI innovation.

Most staff are studying by doing: 87% of staff surveyed report studying AI via curiosity-driven, role-relevant experimentation with AI instruments. Entry to supporting alternatives and sources is essential to sustained confidence and adoption. Leaders want tailor-made assist: Director-level leaders surveyed report barely decrease confidence in utilizing our inner AI device than mid-level staff, in addition to decrease total satisfaction with AI instruments. These findings counsel that senior leaders might profit from tailor-made studying alternatives and focused assist to assist construct their confidence and satisfaction with AI, to allow them to extra successfully champion AI adoption throughout the group. Mid-level staff are looking for extra specialised AI expertise: The AI Options on Cisco Infrastructure Necessities Studying Path (a role-specific coaching for mid-level IT professionals supplied via Cisco U.’s Ladder Up program) noticed 3 times the enrollment of earlier choices. This surge displays a robust demand amongst mid-level IT professionals to maneuver past foundational AI ideas and acquire extremely sensible, role-specific expertise, reminiscent of deploying, managing, and optimizing AI programs in real-world environments.<img loading="lazy" decoding="async" class="lazy lazy-hidden aligncenter wp-image-484113 size-full" data-lazy-type="image" src="https://blogs.cisco.com/gcs/ciscoblogs/1/2026/01/AIResearch_Section3-e1767992535655.png" alt=" An illustration of diverse employees working on laptops with floating icons representing coding, workflows, and cloud infrastructure, assisted by small AI robots." width="800" height="369"/>

4. Constructing Pleasure Round AI Rising AI adoption at Cisco is grounded in optimism and a shared perception that know-how ought to elevate human work.

AI is sparking pleasure: Whereas analysis reminiscent of Pew Analysis Heart’s 2025 examine on AI within the office finds that many employees are extra anxious than hopeful about AI’s affect on their jobs, Cisco staff who have been interviewed described feeling passionate about its potential. AI adoption is rising throughout Cisco: Each technical and non-technical teams present progress towards extra frequent AI utilization. Company guardrails are making a distinction: Cisco’s Accountable AI Framework, together with clear and constant messaging from management, is resonating. Staff who have been interviewed perceive that AI is only with human oversight and see verifying accuracy and making use of crucial considering as important components of utilizing AI properly.<img loading="lazy" decoding="async" class="lazy lazy-hidden aligncenter wp-image-484114 size-full" data-lazy-type="image" src="https://blogs.cisco.com/gcs/ciscoblogs/1/2026/01/AIResearch_Section4-e1767992567442.png" alt="An illustration of a diverse group of colleagues collaborating in a comfortable workspace, featuring icons of a heart and a lightbulb to represent a positive and innovative culture." width="800" height="345"/>

Closing Ideas AI is already making a significant distinction for Cisco’s workforce, and its affect is rising.

Every worker’s journey with AI is completely different, and everybody at Cisco has a job to play. As this transformation continues, we stay dedicated to equipping our individuals with the talents, instruments, and tradition they should thrive in an AI-powered future. By embracing findings like these, we're evolving collectively, constructing on what works, and shaping what comes subsequent.

Methodology

Scope: Complete evaluation (August 2024 – October 2025) of AI device adoption, utilization, expertise, and affect inside Cisco, specializing in CIRCUIT (Cisco’s inner AI assistant), GitHub Copilot, and Ask Cody.

Information Sources: Anonymized and aggregated knowledge from AI device utilization, AI studying, worker expertise surveys (Actual Deal, Engagement Pulse, IT@Cisco, AI@Cisco), worker demographics, collaboration knowledge (Webex, occasion/workplace attendance), efficiency/rewards, expertise, and hiring/termination knowledge.

Analytical Strategies: Hybrid strategy combining quantitative and qualitative strategies, together with descriptive statistics, statistical modeling (e.g., XG Enhance, OLS regression), worker interviews, and worker focus teams.

Acknowledgments This analysis was made attainable via the devoted efforts of the Folks Intelligence workforce and IT companions:

Sponsors: Roxanne Bisby Davis, Matt Starr, Madison Beard, John Lagonigro

Leads: Hanqi Zhu, Could Liew

Researchers & Information Scientists: Mary Williams, Peiman Amoukhteh, Madi Brumbaugh, Erik Wangerin, Delia Zhou, Casey Bianco, Ty Busbice, Rachith KS, Sara Hardesty, Joshua Rickard