AI agents are spreading across the data and AI industry, promising to automate everything from research to outreach. At the same time, teams are learning that these tools can hallucinate, leak data, or act in surprising ways. In day-to-day work, the challenge is deciding which tasks to hand off, what data to share, and how to keep the output trustworthy. Do your agents actually add value, or just add noise? Are they running in a secured, ring-fenced environment? How do you balance playful experimentation with critical checking when an agent confidently gets a key fact wrong?
Danielle leads go-to-market strategy at WNS, Capgemini's AI transformation services arm. Previously, Danielle was Chief Data Officer at American Express and Albertsons. She also write The Remix substack on technology trends, and is an Editorial Board Member for CDO Magazine.
In the episode, Richie and Danielle explore AI agents at work, experimentation with guardrails, data privacy, access, tone controls, OpenClaw automation wins and failures, token costs, tying AI plans to P&L strategy, shifts in careers and hiring, how data teams handle unstructured data governance, and much more.
Links Mentioned in the Show:
- WNS
- Connect with Danielle
- AI-Native Course: Intro to AI for Work
- Catch Danielle speaking at RADAR—April 1
- Related Episode: AI Agents Are the New Shadow IT (And Your Governance Isn’t Ready) with Stijn Christiaens, CEO at Collibra
- Explore AI-Native Learning on DataCamp
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