Danielle Krop from WNS discusses why AI agents fail in practice: hallucinations, data privacy risks like exposing Slack to OpenAI, and the massive change-management effort required. Cheaper AI doesn't deliver value without human judgment and alignment to actual business goals.
It's totally worth it to upskill yourself. People do need to just experiment within some guardrails and have some fun with these new tools. Like, I've been what I would call a pragmatic tech optimist.
AI agents suddenly got suspiciously good, and that means you probably urgently need to reinvent half your business. If you work at a large enterprise, that's a daunting change management task. How do you make sure that your AI strategy feeds into your business strategy?
Once a resource becomes more— becomes cheaper and more productive, the need for it goes up. Are those agents actually providing value or are they not?
Fortunately, we have Danielle Krop to guide us. Danielle is Executive VP of Digital Strategy and Alliances at WNS, which means she spends all day helping customers run transformation programs to make better use of data and AI. Previously, Danielle was the first Chief Data Officer at American Express, where she built out a data capability from scratch. I'm curious as to how she'd approach that now.
Who wants OpenAI to have access to all of their Slack data? It's a probabilistic model. It's never going to be perfect. It's going to do unexpected things, which is that, you know, it will hallucinate. You still have to use your brain.