Measure Before You Scale
Information Products, Retrieval Readiness, and the Foundation Enterprise AI Depends On
Webinar, October 21, 1pm ET|10am PT
Your AI pilots worked. So why can't you scale them?
In most enterprises, each business unit builds its own assistant, its own content pipeline, and its own way of judging results. Content gets rebuilt project by project, results can't be compared, and leadership can't tell which investments are paying off. Switching models does not fix this. The problem is the information underneath.
There is no AI without IA. In this session, Seth Earley explains the two disciplines that decide whether AI scales across an enterprise or stalls in a series of disconnected pilots, and how to measure where your organization stands today.
What you will learn
- Why standard information products matter. Content with a named owner, agreed definitions, and a governed source can be created once and published everywhere. Search, portals, training, and AI assistants then all draw from the same foundation.
- How tool-agnostic measurement changes decisions. One consistent way to score retrieval quality across tools, vendors, and pipelines lets teams compare results and invest on evidence rather than on demos.
- How to diagnose readiness at three levels of depth.
- The AI Readiness Quick Check is a 12-question diagnostic across knowledge, operational, technical, and governance readiness. It often reveals how differently IT, KM, and business leaders see the same organization.
- AIRR-10 scores the content itself across ten retrieval readiness dimensions.
- The full AI Readiness Assessment reviews maturity across governance, information architecture, content, data, operations, and culture, and produces a sequenced roadmap.
- The session covers when to use each one, and the difference between a score and a remediation plan.
- Why architecture problems and content problems need different fixes. Telling them apart keeps remediation effort from going to the wrong place.
- Why senior sponsorship is required. Business units adopt shared standards only when leadership requires it. The payoff comes both in the near term and as AI use expands.
Who should attend:
Executives and leaders responsible for enterprise AI, knowledge management, content operations, digital experience, and data governance, along with anyone who has to explain why a successful pilot has not become an enterprise capability.
Registrant offer:
Everyone who registers receives a complimentary AI Readiness Quick Check. It takes 10 to 15 minutes and returns a readiness score across knowledge, operational, technical, and governance domains, showing how your organization compares with the patterns discussed in the session.
The score shows where you stand. Organizations that want to go further can follow it with a gap review and remediation plan. That is a separate working session that interprets the results, identifies root causes, and sets out a prioritized path forward.
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Meet The Speaker
Seth Earley
An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions.
Seth has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance by making information more findable, usable and valuable through integrated enterprise architectures supporting analytics, e-commerce and customer experience applications.
