One thing I hear consistently from business leaders is this: We believe in the promise of AI, but we’re still figuring out how to turn it into real business growth.
At Cisco, this is the journey we’re on. Over the past 18 months, we’ve invested in AI tools and learning experiences designed to help people enhance their work and deliver measurable business results.
To understand whether those investments are making a difference, the People & Communities team stepped back and asked a bigger question: When AI becomes integral to how our people work, how does it shape engagement, performance, and growth across Cisco—and what does that mean for the business?
Over the past year, Cisco’s People Intelligence team examined how employees engage with AI tools, drawing on surveys, interviews, focus groups, and data analysis. The findings send a clear signal: our approach is working—and when paired with a culture that encourages learning, experimentation, and trust, the possibilities for our people and our business are limitless.
Key Findings:
1. AI Powers a Better Employee Experience
AI is more than a tool—its use positively impacts individual engagement, retention, performance, and growth.
- AI boosts individual engagement: We’ve seen a powerful, mutually reinforcing cycle emerge: engaged employees actively use AI, and AI use deepens employee engagement. AI users who were interviewed report greater enthusiasm for Cisco’s mission, stronger confidence in our future, and feel more challenged and empowered to grow compared to their peers who don’t use AI. They also report having more opportunities to use their strengths every day.
- AI strengthens retention: Contrary to claims that AI users are more likely to leave, AI users at Cisco stay longer—and use AI twice as often each month as employees who exit the company.
- AI enhances productivity and performance: Over 70% of employees surveyed report that AI helps them save time, boost productivity, and handle routine work more efficiently. This enhanced productivity appears to be contributing to performance, as employees who use AI tools more frequently tend to receive slightly higher Individual Performance Factor (IPF) scores.
- AI accelerates career growth: AI users are more likely to be promoted faster, spend less time in the same grade, and are 40% more likely to be designated Critical to Retain. Those recommended for promotion use AI 50% more often than those who aren’t. These patterns suggest that Cisco is becoming a place where AI skills are not only developed but rewarded.
2. Driving AI Adoption Across Our Workforce
Understanding what drives and hinders adoption helps us create the right environment for learning and innovation.
- Leaders who use AI amplify adoption: Employees whose direct leaders use AI are twice as likely to use it themselves. Top-down modeling truly matters. Even small actions like mentioning AI tools in team meetings or 1:1s create opportunities to introduce practical solutions, build comfort, and normalize AI usage.
- Flexible work environments support AI usage: Hybrid work and employee autonomy may support more AI usage. Interestingly, employees who choose to come into the office three or more days a week are more likely to use AI tools than their peers.
3. Designing Effective AI Skilling Strategies
How employees learn AI makes all the difference. Our findings reveal what works best to keep our workforce at the forefront of AI innovation.
- Most employees are learning by doing: 87% of employees surveyed report learning AI through curiosity-driven, role-relevant experimentation with AI tools. Access to supporting opportunities and resources is key to sustained confidence and adoption.
- Leaders need tailored support: Director-level leaders surveyed report slightly lower confidence in using our internal AI tool than mid-level employees, as well as lower overall satisfaction with AI tools. These findings suggest that senior leaders may benefit from tailored learning opportunities and targeted support to help build their confidence and satisfaction with AI, so they can more effectively champion AI adoption across the organization.
- Mid-level employees are seeking more specialized AI skills: The AI Solutions on Cisco Infrastructure Essentials Learning Path (a role-specific training for mid-level IT professionals offered through Cisco U.’s Ladder Up program) saw three times the enrollment of previous offerings. This surge reflects a strong demand among mid-level IT professionals to move beyond foundational AI concepts and gain highly practical, role-specific skills, such as deploying, managing, and optimizing AI systems in real-world environments.
4. Building Excitement Around AI
Growing AI adoption at Cisco is grounded in optimism and a shared belief that technology should elevate human work.
- AI is sparking excitement: While research such as Pew Research Center’s 2025 study on AI in the workplace finds that many workers are more worried than hopeful about AI’s impact on their jobs, Cisco employees who were interviewed described feeling enthusiastic about its potential.
- AI adoption is growing across Cisco: Both technical and non-technical groups show progress toward more frequent AI usage.
- Corporate guardrails are making a difference: Cisco’s Responsible AI Framework, along with clear and consistent messaging from leadership, is resonating. Employees who were interviewed understand that AI is most effective with human oversight and see verifying accuracy and applying critical thinking as essential parts of using AI well.
Closing Thoughts
AI is already making a meaningful difference for Cisco’s workforce, and its impact is growing.
Each employee’s journey with AI is different, and everyone at Cisco has a role to play. As this transformation continues, we remain committed to equipping our people with the skills, tools, and culture they need to thrive in an AI-powered future. By embracing findings like these, we are evolving together, building on what works, and shaping what comes next.
Methodology
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Scope: Comprehensive analysis (August 2024 – October 2025) of AI tool adoption, usage, experience, and impact within Cisco, focusing on CIRCUIT (Cisco’s internal AI assistant), GitHub Copilot, and Ask Cody.
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Data Sources: Anonymized and aggregated data from AI tool usage, AI learning, employee experience surveys (Real Deal, Engagement Pulse, IT@Cisco, AI@Cisco), employee demographics, collaboration data (Webex, event/office attendance), performance/rewards, skills, and hiring/termination data.
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Analytical Methods: Hybrid approach combining quantitative and qualitative methods, including descriptive statistics, statistical modeling (e.g., XG Boost, OLS regression), employee interviews, and employee focus groups.
Acknowledgments
This research was made possible through the dedicated efforts of the People Intelligence team and IT partners:
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Sponsors: Roxanne Bisby Davis, Matt Starr, Madison Beard, John Lagonigro
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Leads: Hanqi Zhu, May Liew
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Researchers & Data Scientists: Mary Williams, Peiman Amoukhteh, Madi Brumbaugh, Erik Wangerin, Delia Zhou, Casey Bianco, Ty Busbice, Rachith KS, Sara Hardesty, Joshua Rickard
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Support Team: Kensleigh Gayek, Kate Pydyn, Grace Jain, Charlie Manning, Samantha Everett, Lauren Grimaldo, Elle Sawa, Shavonda Locke, John Misenheimer
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IT Partners: Tammi Fitzwater, Jenna Tracy, Areebah Ajani, Dick Loveless