The integration of Artificial Intelligence (AI) into the modern workplace presents a complex frontier for Human Resources (HR) leaders, positioning them as pivotal navigators of their organizations’ AI journeys. This role, while crucial, is fraught with inherent uncertainties. Many of these variables, such as the unpredictable trajectory of AI evolution and its broader economic ramifications, lie beyond direct HR control. However, HR professionals can carve out significant areas of clarity and influence by prioritizing continuous measurement, particularly by understanding employee sentiment and the tangible impacts of AI on workflows and organizational culture. This people-centric approach is a cornerstone of Cisco’s strategy, as articulated by Chief People Officer Kelly Jones.
For the past 18 months, Jones and her team have been diligently examining the human dimensions of AI integration at the technology giant. This deep dive involves a combination of long-term, enterprise-wide surveys and focused group discussions. The insights gleaned have been profoundly illuminating. Early findings indicate a strong correlation between active AI utilization by employees and enhanced engagement levels, a heightened sense of confidence in the company’s future trajectory, and improved employee retention rates. While acknowledging the need for careful interpretation to avoid overstating causal relationships, Jones emphasizes that these initial patterns are significant and are actively shaping Cisco’s evolving AI integration strategy. A particularly salient discovery underscores the critical role of leadership in fostering widespread AI adoption.
"Employees are twice as likely to use AI if their leaders do and if they talk about it," Jones stated, highlighting a pivotal finding that extends the scope of successful AI integration beyond mere technological implementation. She posits that sustainable transformation necessitates a focus on leadership modeling, underscoring that "The successful AI adoption of Cisco is as much about leadership modeling as it is about the tools." This sentiment suggests a paradigm shift in how organizations approach AI adoption, moving from a technology-first to a people-first methodology.
Measuring Employee Sentiment: A Competitive Advantage
The proactive measurement of employee sentiment regarding AI has emerged as a significant competitive advantage for Cisco. Kelly Jones views this not as a new practice, but as a discipline that has amplified in importance during the current AI transition. "For us, it’s been a huge competitive advantage," Jones explained. "To be fair, understanding employee sentiment has always been core to how we run our people team at Cisco. We have an employee listening function that is at the early steps of design when we’re trying to decide what we roll out. It’s not new, but I do think that the discipline of doing it matters more now with this transition we’re in."
Jones further elaborated on the deeply personal nature of AI integration, stating, "When I think about AI, it’s not necessarily just the technology change, it’s actually this deeply personal one." She described the spectrum of employee reactions, noting that "Our employees, they range—they’re curious, some are anxious." The risk of proceeding without this crucial feedback loop is akin to "flying blind on what I think is probably the most important transformation of my career, if not everybody who runs HR right now."
While many organizations focus on quantifiable metrics like usage rates and productivity, Jones argues that these represent only a fraction of the complete picture. The human element, she contends, is paramount. "A lot of people are talking about usage rates and productivity, and that is certainly interesting and we want to understand that, but it’s just a little sliver of the story." The true indicators of successful human-centric transformation lie in fostering trust, confidence, and readiness. Crucially, it’s about ensuring employees feel equipped to use AI responsibly. These qualitative signals are vital for discerning whether AI adoption is genuine or merely superficial compliance. This nuanced understanding allows Cisco to differentiate between true integration and what Jones terms "compliance theater."
Pivoting Strategy Based on Employee Feedback
Cisco has demonstrably adjusted its AI integration strategy in response to employee feedback, with significant shifts occurring in the realm of learning and development. A key insight derived from employee data was the ineffectiveness of a top-down, mandatory approach to AI training. "We absolutely have," Jones confirmed when asked about strategic pivots. "One of the biggest was probably in how we were thinking about learning. One of the things that came out very clearly in the data is you can’t legislate or require a mandatory class—‘Watch this webinar, get this certification’—and get real enthusiasm and usage with AI. It’s individual and it’s personalized."
This realization led to the development of Cisco’s "Leading Edge" program, a hands-on initiative designed to facilitate experiential learning. Approximately 90% of employees indicated a preference for learning through practical application. Consequently, Cisco established three dedicated hands-on labs that offer employees dedicated time and space to engage with AI. "About 90% of our employees basically said they learned through doing. So, we set up a program at Cisco called Leading Edge, where we have three hands-on labs. Once a month, we give people the time and the space to come and join Edge Up Labs."
These labs cater to different user groups: leadership, individuals, and teams. The environment is intentionally experimental, moving away from prescriptive scripts towards interactive, storytelling-driven sessions. A critical element of the Leading Edge program is its adaptability, with facilitators actively monitoring real-time sentiment and adjusting content based on audience response. "We have them for leadership, for individuals and for teams. And it really is a lab environment where people are experimenting. They’re not necessarily getting a script that says, ‘Here are the things you need to know.’ It’s interactive, it’s storytelling and it’s giving us real-time sentiment. We watch the chat and the audience sentiment and change what we’re talking about in the session based on how people are responding." This agile approach ensures that the learning experience remains relevant and responsive to the evolving needs and interests of the workforce.
AI’s Tangible Impact on Performance
The study conducted by Cisco’s HR team has revealed a direct link between increased AI utilization and improved employee performance metrics. Employees who engaged with AI more frequently not only received higher performance ratings but were also more likely to be recommended for promotion. The data indicated that individuals recommended for promotion in the most recent review cycle used AI 50% more often than those who were not.
"In the study we did, we learned that employees who are using AI more frequently received higher performance ratings. They’re more likely to be recommended for promotion. People who in the most recent cycle were recommended for promotion used AI 50% more often than those who didn’t." Furthermore, over 70% of Cisco employees reported that AI had contributed to time savings and enhanced productivity. This organic momentum, driven by observable benefits in daily work, is fostering stronger employee engagement and retention. The overarching implication is that when implemented effectively, AI can serve as a powerful catalyst for improved organizational performance.
Jones cautioned against a common pitfall: treating AI implementation as a mere software rollout rather than a profound cultural transformation. "One of the biggest mistakes that organizations make with AI is treating it like a software rollout rather than a cultural shift. If you just push a tool to people, you get compliance. If you want innovation, you have to foster experimentation." This perspective underscores the importance of creating an environment that encourages exploration and learning, rather than simply mandating tool usage.
Rethinking Mandates and Performance Metrics
Cisco has opted against mandating AI usage or directly integrating it into performance reviews, believing that demonstrated value is a more potent driver of adoption than policy. "We’re not currently mandating AI or tying it to performance reviews," Jones confirmed. "What we’re seeing is that adoption is being driven by demonstrated value, not by the policy."
Jones expressed reservations about making raw AI usage a primary metric, emphasizing the potential for employees to focus on the quantity of use rather than the quality of outcomes. "I think organizations should be a little careful about making raw AI usage the metric. I don’t want people across Cisco optimizing for, how often did I use the tool? —instead of, did I improve the outcome?" The more pertinent question, in her view, revolves around the effective and responsible application of AI to drive improvements in quality, speed, innovation, or customer impact.
The approach to training also reflects this people-centric philosophy. Instead of traditional, button-clicking tutorials, Cisco advocates for an AI-embedded, hands-on training model. This involves integrating storytelling, role-playing, and real-time problem-solving to allow employees to interact directly with AI and perceive it as a cultural evolution rather than a purely technological shift. "You have to move away from this old school model of how you train people and instead make it a hands-on, AI-embedded training. When you do that, you’re not just saying, ‘Here’s how to use this button.’ When you add the storytelling and the role-playing and the real-time problem-solving, you’re allowing people to get their hands on it and treat it more as a cultural change than a technology change."
The core message is to empower, not just train, the workforce. This involves providing a "sandbox" for experimentation, granting permission to explore, and offering data-driven evidence of productivity benefits. When these conditions are met, Jones believes that mandated adoption becomes unnecessary. "If you want your workforce to embrace AI, you’ve got to stop training them and start enabling them. You’ve got to give them a sandbox to play in; you’ve got to give them permission to experiment and the data to show them that their own productivity is actually benefiting. When you do that, you don’t have to mandate."
Unexpected Emergence of Self-Forming Communities
An unexpected but highly positive outcome of Cisco’s AI integration efforts has been the emergence of self-forming communities of practice within business units, particularly around specific roles. The customer experience team has been a frontrunner in this phenomenon. Employees in similar roles across different units have begun to organically organize their own AI learning groups. These communities share best practices, discuss effective prompt engineering techniques, and analyze the resulting customer outcomes.
"One of the areas that’s going really well is that we’re seeing communities that are self-forming within business units around roles. Our customer experience team actually led the way in this. What we found was similar job titles across multiple units in customer experience were self-organizing their own AI learning communities around what were some of the best agents they were building, what were some of the best prompts they were using, what were the outcomes they were seeing for their customers?" This organic peer-to-peer learning and knowledge sharing is a testament to the power of enabling employees to take ownership of their AI development and highlights the vital role of fostering an environment where such collaboration can flourish. The ability for these communities to self-organize and share knowledge is a strong indicator of genuine AI adoption and a significant step towards embedding AI as a natural part of daily work.
