It’s been 100 days since I joined Cisco and one shift stands out clearly – the strategic impact of the Cisco/Splunk acquisition. What began as a $28B transaction on paper is already reshaping how we think about observability, AI, and secure infrastructure for customers.
It’s easy to see $28 billion as a headline about size, but it’s a statement of intent and feels more like a bet on convergence. Infrastructure meets intelligence, detection meets response. The acquisition gives customers more than just integrated tooling and it offers them the context they need to act faster and more precisely.
Take Splunk’s AI assistant. What’s interesting is the ability to turn intent into automation by generating SPL queries on the fly, much like prompting a co-pilot to write SQL. That’s powerful on its own, but even more valuable when you’re operating AI applications across distributed architectures (logs in GCP, API calls hitting OpenAI, a datasource sitting on-prem.) Correlating those signals used to take hours… now it’s minutes.
What excites me is how this changes observability for AI itself. Logging token-level inputs and outputs helps surface model drift, trace failure points, and fine-tune performance over time. As models evolve, the systems around them need to be just as observable – and that’s where Cisco + Splunk feels genuinely differentiated.
For most people I speak to, especially those leading operations, security, or transformation efforts – the value is pretty clear – it simplifies things. It’s one platform that lets you see across your entire digital environment. You can detect issues faster, and automate responses, so no more stitching together dozen-point solutions or context switching. You get answers faster and the signals are more clear, so you can stay ahead of issues instead of reacting to them like most do.
It was just one of a few things that changed the way I view Cisco, and there are a good few more that I’ll write about as I find the time.
#CiscoAI
