How AI Data Clearinghouse can boost enterprise AI

Enterprise IT vendors are moving to position themselves for the AI era. As subsequent M&A activity picks up, a tendency to bolt together "AI stacks" for IT teams should be challenged. True value from enterprise AI will come from empowering those familiar with the context that makes business processes tick: business users and analysts. In my latest article for @TechRadarPro I discuss how the AI Data Clearinghouse process helps address the root causes of stunted enterprise AI rollouts by empowering businesses to uncover transparent, trusted AI use cases. Read more here: https://lnkd.in/gVqumAfJ

James Kaikis

Preparing CROs & CEOs for the future of B2B SaaS | GTMshift | CRO Functional Head @ Pavilion | Former CRO | Co-Founder @ PreSales Collective (Acquired) | Breaking The GTM Playbook |

5d

Great article. The following concept really stood out to me because it’s the best approach to improving accuracy and minimizing risk. I heard about “SLM” last year and that concept really makes a ton of sense. “Connecting AI models directly to vast stores of sensitive data is a governance nightmare for boards wary of risk. A better approach is selective: giving AI access only to the limited, highly relevant data needed for each specific use case.”

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