Operationalizing, Shadow AI, Moving Beyond Demos
Over the past year, I’ve attended countless sessions about AI—especially those that hover around cybersecurity. I sat through one this week, and thought I would distill the key non-vendor-speak points for those of you who are interested:
🔹 It’s Not “If”—It’s “How” (Ok, this one is obvious) Nearly every executive in the audience had used generative AI within the past 24 hours—personally or professionally. Adoption is happening whether you’ve sanctioned it or not. This is a wake-up call for security leaders: shadow AI is already embedded in your environment.
🔹 Core Use Cases (get beyond the chatbot) From customer service chatbots (used by 73% of companies) to automated software engineering and legal document generation, enterprises are seeing real productivity gains. But the message was clear: don’t chase novelty—identify scalable, repeatable use cases aligned to business goals.
🔹 Governance Can’t Be an Afterthought Without a robust governance framework, AI introduces ethical landmines, security gaps, and reputational risk. Suggested approach: create an AI Council across IT, Legal, Risk, and Compliance, and align around policies, data provenance, and model explainability.
🔹 Measure ROI, Not Hype CISOs and CIOs are expected to articulate the business case—yet many are stuck in experimentation mode. The guidance here was to treat generative AI as a strategic investment, not a skunkworks project. Tie it to metrics: time saved, revenue lifted, customer satisfaction improved.
🔹 Start Small, Scale Smart Pilot projects are useful—but only when you’ve pre-defined success criteria. The best-in-class leaders are building centers of excellence to support AI adoption across business units, not just isolated experiments.