Hosted by Chandra Wobschall and Paul Houtkooper

Hey JDE Connection listeners, Chandra and Paul here! In this episode, we took our ongoing conversation with Nathan Diamond in a new direction, one that seems to come up in just about every discussion these days: AI. But instead of talking about AI in the abstract, we focused on something much more practical: how Business Analysts can actually use AI today to improve their work without giving up the skills that make BAs valuable in the first place.

From BABOK Knowledge to AI in Action

Nathan shared a great example of how his BABOK foundation became the fuel for a very practical AI use case. Anyone who’s written requirements knows they’re essential and time-consuming. Capturing business, stakeholder, functional, non-functional requirements, assumptions, constraints, dependencies, and test cases takes real effort. Rather than skipping steps, Nathan built an AI agent that respects the BABOK structure. He trained it using his organization’s requirements template, clear definitions, and consistent labeling conventions (BR-1, SR-1, and so on).

The result? He can focus on having better conversations, while the agent does the heavy lifting of organizing and documenting what was discussed.

Better Conversations, Not Shortcuts

One thing we all agreed on: AI doesn’t replace good business analysis; it amplifies it. Nathan emphasized that the real value still comes from elicitation skills: asking the right questions, understanding context, and listening carefully. The AI agent only works well because it’s fed high-quality input from thoughtful conversations. As we talked it through, it became clear that AI helps BAs spend less time formatting and more time engaging. That’s a win for everyone involved.

Consistency as the Secret Sauce

Chandra called out something that really resonated – consistency. In many organizations, documentation varies wildly depending on who wrote it. That makes life harder for developers, testers, and anyone who inherits the solution later. By routing notes and transcripts through a shared AI agent, teams can produce requirements that follow the same structure and standards every time. Different people, same playbook. That consistency doesn’t just make development easier; it creates a foundation for continuous improvement. As Paul pointed out, once you have a standard, you can refine it. Update the agent, and the improvement applies everywhere.

Closing the Loop (and Finding the Gaps)

We also explored a powerful idea: using AI not just to generate requirements, but to challenge them. If a requirements document comes back with no constraints, that’s a signal, not that the AI failed, but that the BA may need to dig deeper. The agent becomes a mirror, reflecting where questions were missed and where follow-up is needed. That feedback loop helps sharpen BA skills over time, rather than dulling them.

Forward, Backward, and Everywhere in Between

Things got especially interesting when we started talking about what comes next.

• Could AI help translate business requirements into technical artifacts?
• Could it help developers comment code based on requirements?
• Could it even help reverse-engineer existing solutions where the original “why” is long gone?

We didn’t claim all of that is here today, but we could clearly see the path. Small, practical steps now. Bigger possibilities later.

Adoption Is the Hard Part

Of course, tools don’t adopt themselves. Nathan shared some honest challenges around getting teams to actually use AI agents, especially when people are anxious about change or worried about what AI might mean for their roles. We landed on a simple truth: AI isn’t going to replace BAs, but BAs who learn to work effectively with AI will have a serious advantage.

It’s not about flipping a switch. It’s about experimenting, learning, and figuring out how these tools make you better at what you already do well.

Why the Human Still Matters

As much as we explored AI’s potential, we kept coming back to what it can’t do (at least not yet):

• Read body language
• Sense hesitation or discomfort
• Know when to pause, reframe, or lighten the mood
• Decide when an email won’t cut it and a quick call will

Those moments like the raised eyebrow, the crossed arms, the sigh before an answer, all still matter. And that’s where great BAs continue to shine.

Midwesternism of the Week

We can’t end an episode without a Midwesternism and with the Super Bowl, Chandra shared an appetizer suggestion from her friend in run group. Let’s just say, you had me at, “Velveeta”!

Until next time, let’s keep learning, sharing, and most importantly, laughing together.

Toodles!

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