Cisco's finance chief, Mark Patterson, has spent 26 years at the company and told Fortune he has never seen an opportunity like the one AI now presents. That opportunity is about to reach every employee. At the start of Cisco's new fiscal year, its roughly 90,000 staff will begin receiving access to a personal AI agent capable of answering questions, completing tasks and automatically selecting the most appropriate underlying model.
The timing follows Cisco's 4,000 layoffs, announced in May. The shake-up was intended to facilitate the business to push further into chip design, next-generation networking hardware and AI-focused security, while adding greater weight onto AI investment. Side by side, the developments suggest Cisco's AI strategy is moving beyond product development and marketing to actively embed AI into the daily work of its entire organisation.
What Cisco's AI Deployment Looks Like
"It's not going to burn a whole bunch of tokens with frontier models" for tasks that don't need them, Patterson told Fortune, since the system "knows which tool is most effective and most efficient." That trade-off, between capability and cost, sits at the centre of how the rollout has been built.
Staff across finance, sales and other functions are gaining access to their own AI agent rather than the tool staying confined to a single team, with each request routed dynamically depending on what's being asked. A large share of the underlying system is hosted in-house rather than through external cloud providers, an arrangement that keeps both spending and sensitive data closer to home.
Beyond what shows up in its regular financial results, Cisco isn't putting a figure on what the project costs. The company’s emphasis on intelligent model routing reflects a broader challenge facing enterprises as AI usage scales: the cost of deployment increasingly depends not only on the models organisations choose, but on how efficiently they orchestrate them.
What CX Leaders Can Learn
Cisco's approach suggests that enterprise AI value increasingly depends on organisation-wide adoption rather than isolated customer-facing deployments alone. For customer experience leaders that’s worth noting because the quality of customer-facing AI increasingly depends on the maturity of the enterprise AI infrastructure sitting behind it. Improvements to CX may end up being driven as much by employee enablement as by the tools customers actually see.
Cisco's emphasis on model routing and token efficiency reflects a wider industry concern. Gartner has forecast a 47% increase in global AI spending, suggesting that organisations are investing heavily in AI while also facing growing pressure to manage infrastructure and operational costs. The challenge only increases once AI spans multiple functions and forces organisations to confront who is actually accountable for it. As AI becomes woven into everyday work, the line between employee productivity and customer experience is likely to blur further.
Looking Ahead
Cisco's rollout reflects a wider shift towards operational AI embedded across the workforce rather than confined to specialist teams. Across the CX AI industry, vendors are racing to build the infrastructure needed to orchestrate thousands of AI agents securely and efficiently. Cisco is now demonstrating what that looks like inside its own business, offering customers a practical example of enterprise AI operating at organisational scale.