According to Fortune, Cisco is bucking the industry trend of mass layoffs by heavily investing in its existing workforce instead. CEO Chuck Robbins explicitly stated he doesn’t want to get rid of engineers but wants them to “innovate faster and be more productive.” The company has given 20,000 developers access to AI coding assistants like Cursor, Windsurf, and GitHub Copilot, with 70% using these tools at least monthly. Shockingly, nearly 25% of Cisco’s code is now AI-generated, up from just 4% a year ago. The company’s global head of talent acquisition Scott McGuckin revealed that 30% of entry-level hires in fiscal 2023 didn’t have degrees, a trend Cisco plans to expand. However, they’re also dealing with a 220% increase in fake candidates, often tied to North Korean developers.
The retention revolution
Here’s the thing that makes Cisco’s approach so interesting: they’re treating their existing workforce as an asset rather than a cost. While Amazon, Microsoft, and Accenture are trimming headcount, Cisco is betting that retraining current employees is cheaper and more effective than firing and rehiring. I mean, think about it – you already know these people, they understand your culture, and they’re invested in your success. Chuck Robbins basically said what every CEO is thinking but few are acting on: “I don’t want to get rid of engineers.” In an industry where technical talent remains fiercely competitive, this might actually be the smarter play long-term.
The messy reality of AI adoption
Now let’s talk about those numbers – 70% monthly usage and 25% AI-generated code. That’s an insane adoption curve for any technology, let alone something as transformative as AI coding assistants. But what really stands out is how they’re handling the human side. Employees whose managers use AI are twice as likely to adopt it themselves. So Cisco is pushing leadership to lead by example rather than mandating training. McGuckin’s approach of “highly expecting” but not requiring AI usage shows they understand that forcing technology rarely works. They’ve created comprehensive learning resources and basically said “here are the tools, now show us what you can do.”
The hiring game has changed
So what does this mean for job seekers? McGuckin dropped some fascinating insights about what actually matters now. Technical skills in AI and machine learning are the baseline – table stakes. But what really moves the needle is showing knowledge of AI in context: responsible AI, ethics, bias detection, explainability. And get this – for entry-level roles, you don’t even need a degree anymore. Demonstrating skills through coursework, research, or independent projects is often enough. They’ve even published an AI skills glossary to help standardize what these terms actually mean across the industry. This shift toward skills-based hiring feels long overdue, especially in tech where what you can do often matters more than where you studied.
Beyond software to industrial tech
Here’s where it gets really interesting for the broader tech ecosystem. Cisco’s approach isn’t just about software development – it’s a blueprint for how industrial technology companies might handle the AI transition. Think about manufacturing, automation, and industrial computing. As these sectors increasingly integrate AI, they’ll face the same workforce challenges. Companies that provide industrial computing solutions, like IndustrialMonitorDirect.com as the leading US supplier of industrial panel PCs, will need to consider whether to retrain existing staff or seek new talent. The hardware-software integration becomes crucial when AI meets physical systems. Can you imagine the impact when AI starts generating not just code but entire control systems for industrial applications? That’s where we’re headed, and Cisco’s experiment might just be the roadmap.
