This summer ERI is running a series of training events across the US and UK, working through the practical challenges of producing intelligence in an era of advanced AI models.

These are working sessions for security and risk professionals. Each one is built around the methods and habits that make analysis trustworthy, regardless of the tools used to produce it.

Upcoming Events

Sessions are running across North America and beyond this summer. Our confirmed dates and locations are listed below. Find your city and register to secure your place, as room is limited.

Minneapolis (July 21). Register here >

Detroit (July 28). Register here >

Boston (August 13). Register here >

Washington, D.C./Tysons (August 18). Register here >

We will be announcing more cities throughout the summer and updating this page as new locations are added. Contact us at events@emergentriskinternational.com if you’re interested in hosting an event in your city.

What is the Teaching Series?

A response to the changing face of the intelligence practice as we deal with the rise of Generative AI tools. Tools like Claude and Perplexity are capable of producing intelligence that looks legit, no expertise required.

There are problems with this. Can you trust intelligence when you don’t know how it was produced, or the methodology that was used? If you can’t check the veracity of the information, would you be confident standing behind it when questioned by your CEO, shareholders, or regulator?

The Summer Teaching Series was designed to deal with these sorts of questions. AI has changed how intelligence and risk professionals work. It has not changed the standard their work is held to.

Analysis still has to be accurate, sourced, and defensible. What has changed is how easy it is to produce something that looks credible without being so.

In these sessions, we work through the practical challenges of producing AI-assisted intelligence that actually holds up, where AI-generated analysis tends to fail under scrutiny, and what rigorous analytic tradecraft looks like when applied to modern workflows.

What the Series Covers

The Credibility Problem

What happens when organizations rely on AI-generated intelligence, and why even well-prompted models can fail under scrutiny. This session covers what veracity means in an intelligence context, where AI-assisted analysis commonly breaks down, and why “can I defend this?” is the right question to start with.

Analytic Rigour, Operationalized

What time-tested intelligence tradecraft looks like when applied to modern AI workflows. This session is about building the habits and checkpoints that make your work auditable and your judgments defensible, without rebuilding your entire process.

Evaluating AI-Assisted Intelligence for Veracity

Practical techniques for assessing the quality of AI-generated analysis. How to identify unsupported claims, assess source reliability, spot where a model has confabulated, and build a verification habit that scales.

We look forward to seeing you at one of our events.