New Podcast Launch: WTCK? What the Company Knows
Every week brings announcements of smarter foundational models, million-token context windows, and sophisticated agentic workflows. But inside large enterprises, the real bottleneck often lies elsewhere: with the industrial knowledge itself.
Enterprise knowledge is notoriously fragmented across disconnected systems and buried in legacy documents. On top of that, there’s the implicit context that never gets written down. Quality and provenance are rarely tracked, and mere access doesn’t necessarily mean permission to use the data.
AI doesn’t create these problems, it exposes them.
AI has a knowledge problem
For years, executives have echoed the decades-old problem statement attributed to both Lewis Platt (former CEO of HP) and Heinrich von Pierer (former CEO of Siemens):
"If only the company knew what the company knows."
While generative AI finally provides the technical base to realize that vision, bringing it to life requires treating knowledge management as a key priority.
Introducing WTCK? (What the Company Knows?)
To explore this frontier at the intersection of Enterprise AI and Knowledge Management, we’ve teamed up with Stephan Ballenweg, former Head of Knowledge Systems at BASF, to launch our new podcast: WTCK?
In our debut episode, AI Has a Knowledge Problem, we tackle:
Knowledge readiness vs. AI readiness: Why raw model capability can’t compensate for fragmented data architecture.
Retrieval & verification: Why enterprise deployments depend heavily on secure, permission-aware retrieval and domain-expert validation.
Pragmatic implementation: How to start delivering business value without waiting for a perfect data architecture.
Listen in to the full conversation on youtube or via your preferred podcast platform.
Wondering where your organization stands on knowledge-readiness?
Check out our Solutions page to see how we partner with enterprise teams, or get in touch to walk through your current knowledge architecture.
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