"It's a brilliant piece of marketing to call this technology AI — because it implies a level of reasoning and intelligence behind the tool that's not there." That bold claim from data-scientist-turned-consultant Sahil Panicar sets the tone for a frank, hype-free conversation recorded live at SAFe Summit 2026 in Amsterdam. Joined by Atlassian's Zach Brown and host Raghurani from Accenture, the trio unpacks what today's AI actually is (predictive, not deductive), why companies are bleeding money on "AI sprawl," and what individuals and enterprises should really be doing to get value from these tools. If you've felt the pressure to "go get AI" without knowing why, this episode is your reset button.

Saahil Panikar — CIO of Atlas Revolutions, SAFe SPCT & Fellow, former data scientist. Specializes in lean portfolio management, value-stream management, and cyber-physical systems.

Zack Brown — Partner Solution Strategist at Atlassian. Helps partners understand Atlassian's product strategy and go to market with joint solutions.

Host: Renaud Granier — Accenture Business Agility

AI is prediction, not reasoning. LLMs don't know when they're wrong — they predict what you want to hear based on billions of parameters.

Don't invent the technology, then find a problem. Understand your workflows and data first; AI is a force multiplier that amplifies what already exists — good and bad.

Beware AI sprawl. Dozens of siloed AI tools create more confusion, not less. Start with specific, high-value use cases.

Data quality is non-negotiable. A "gated garden" (curated, secure data source) combined with RAG is essential for trustworthy AI outputs.

Change management > tooling. Training, communication, and human-in-the-loop governance drive real ROI.

Check your LLM licensing. Know what happens to your data when you use frontier models — many license agreements allow the provider to reuse your inputs.

Start personally. Experiment with AI on something you're an expert in to understand its boundaries — then bring that competence to your organization.

Test an AI on something you're an expert in this week. Ask it questions where you already know the answers, see where it shines and where it breaks — and share what you learn with your team. That single step is where responsible AI adoption starts.

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