In the first episode of WTCK? – What the Company Knows, Stephan Ballenweg (BKI Advisory, ex-BASF) and Jakub Zavrel (Zeta Alpha) explore a core challenge for enterprise AI: company knowledge is scattered across documents, systems, and people’s heads—and even capable AI models can’t use information they can’t access or reliably retrieve. They discuss why search, company-specific terminology, secure access, and expert evaluation matter as much as the AI model itself. Their practical message: companies don’t need perfect data or infrastructure to begin. Start with a focused goal, connect relevant knowledge, evaluate results with experts, and improve iteratively.
WTCK? Episode 1: AI has a knowledge problem
6 OCTOBER 2026
Key topics
- Why corporate knowledge is often fragmented, outdated, or hard to find
- Why smarter models alone don’t solve access to proprietary company information
- The role of search, retrieval, permissions, and company-specific context
- Why experts are needed to judge whether AI answers are accurate and complete
- How benchmarks and representative questions can help evaluate results
- Why capability gains may be a more meaningful measure of ROI than time saved
- How to start pragmatically without waiting for a perfect data architecture
- Why enterprise AI is an ongoing effort – not a one-time technical project
Key takeaways
- Enterprise AI depends on access to relevant knowledge, not just model capability.
- Expert judgment and evaluation help make AI results more trustworthy.
- Companies can begin with a focused goal and improve their systems over time.
- Capability gains may reveal value more clearly than time savings alone.
- Aligning stakeholders and information needs is part of the work – not an afterthought.
Dr. Stephan Ballenweg
Founder, BKI Advisory
