Enterprise Architecture in the Age of AI—with Fred Hennige (Jack in the Box)
About the episode
If everyone in your organization wants AI, but half of them can't explain what for—where do you start?
In this episode of Futureproof, Xano CEO Prakash Chandran sits down with Fred Hennige, Director of Enterprise Architecture at Jack in the Box, to explore what enterprise architecture actually looks like inside a fast-growing restaurant company navigating AI adoption. Fred shares lessons from building EA practices at three very different organizations (Jack in the Box, Starbucks, and Alaska Airlines) and explains why the discipline must start with business outcomes, not technology inventories. Together, they unpack how AI is showing up across the organization today, why cross-functional AI value is harder to unlock than personal productivity, and how to govern AI adoption without over-indexing on hype.
Topics covered include:
- Business-first EA over technology-first EA: Why starting from business outcomes and process alignment yields better results than cataloging application inventories.
- EA across three industries: How enterprise architecture looks radically different at a growing brand, a mature global operation, and a safety-critical airline—and what each taught Fred about the discipline.
- AI adoption at different maturity levels: Why some teams are already creating value with AI while others are still learning to spell it—and how to stack-rank where to invest.
- Cross-functional AI is the hard part: Why personal productivity gains come first, but the real challenge is unlocking AI value across departments and business functions.
- The AI uncanny valley: Why AI output still requires human synthesis, and why using your own voice matters more than copying and pasting what a model returns.
Chapters
00:00
A Career Across Every Frontier
Fred traces his path from infrastructure through support, software engineering, and product management—including stints at Alaska Airlines and Starbucks.
02:06
The Job Behind the Long Title
He explains his current role at Jack in the Box: making sure business and technology line up for the greater good, with a small team spanning solution architecture and information architecture.
03:42
Where AI Shows Up First
Fred describes how AI adoption starts with personal productivity and why cross-functional AI value is the harder, more important challenge.
05:20
Business-First vs. Technology-First EA
A case for starting with business outcomes and process alignment rather than technology inventories, and why sussing out edge cases and process overlaps matters more than service orientation.
07:06
Three Companies, Three Architectures
Fred walks through how enterprise architecture looked at Jack in the Box (building from step one), Starbucks (field-to-cup and cup-to-customer at global scale), and Alaska Airlines (operational safety above all else).
09:42
How to Start an EA Practice
Practical advice on finding what matters most to the business, measuring quality of life—not just transactions per minute—and drawing a clear line from measurement to change.
11:45
Build Portfolios, Not Inventories
Fred challenges conventional enterprise architecture wisdom: instead of cataloging every application, focus on business initiatives and let architecture artifacts accumulate naturally from the work.
13:45
Stack-Ranking AI Maturity Across the Org
How Fred polled the organization to find where AI value already existed, gravitated toward more mature perspectives, and used that energy to grow adoption outward.
15:33
Where AI Value Is Hardest to See
A candid breakdown of why quantitative disciplines like finance and operations adopt AI more easily, while softer sciences like HR and recruiting struggle to translate vendor pitches into real value.
17:29
Governing AI Without Over-Indexing
Fred explains the AI governance council at Jack in the Box and his key takeaway from Gartner: match governance tempo to the hype cycle so the organization is ready when the technology matures.
19:33
Data Foundations and the Order-Taking Lesson
Why understanding your data estate comes before visioning, and what Wendy's failed AI experiment reveals about the gap between hype and operational readiness.
22:57
Scale Means Different Things
How experimentation scales differently across a quick-service restaurant franchise, a global coffee chain, and an airline where one failure can ground planes across the network.
25:27
The AI Uncanny Valley
Fred's signature take: AI output still lives in an uncanny valley where you can see the potential but can't cross it yet—and why using your own voice remains essential.
29:00
How Fred Actually Uses AI Today
Practical examples: comparing software packages, analyzing help desk tickets (including catching when the analysis smells wrong), and structuring unstructured inventory data.
32:30
Be Clear About Value and Build for Iteration
Fred's closing advice: stay objective about value even when you fall in love with a technology, and prepare for a future where the ideal state iterates every six months instead of sitting on a three-year roadmap.
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