Mid-October 2026 (Data: Sep through Oct 15)

Wait, what is this?

Hey friends!

You're reading my first ever tracker on Minnesota's Business & Ops Transformation to the AI-Era ("MNBOT" for short?). I wanted you to see it. Ha, don't you feel special? ;)

Basically, I collect job postings related to AI transformation in MN, distill trends, and of course, hopefully use it to help me get hired. (It was actually much trickier than it looks. But I digress.)

Will I create future editions? Who knows. As with anything AI, it's good not to get precious about the future. All I hope is that you find it an interesting view of this nutty space.

Orientation:

  1. I collect job postings as a "convenience sample." Aka, I manually search job listing sites (LI, Indeed, etc.). I won't catch them all. Why you care: Take this as directional.
  2. Speaking of convenience: It conveniently starts at a point in time. It ain't comprehensive. Companies and industries that hired in the past aren't in here. Why you care: Take this as just a part of the elephant.
  3. This is pretty crude. But I have dreams of making it way better ... reality permitting. Why you care: Got ideas? Go on, share them please. 😄
  4. I focus on the business and ops side of AI transformation. HR, Data & analytics, and Engineering only when I happen to see roles. Why you care: I'll look out for those of you who'd care about other topics than mine whenever possible. But know that I just don't cover everything.

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My asks:

See other postings I should know about? Please lmk!

Think someone else should get any future editions? Send it on or tell me their info.

Ok, enough with the intellectual throat-clearing. On to the data and stuff.

State of the market

Four observations.

Hiring for MNBOT is still painfully in its infancy, no matter the general AI hubbub.

  • I've found ~ 5 - 15 postings/ week so far.
  • Reasonable people might argue up or down a bit. But it wouldn't change the big picture. And the variation on small numbers washes out formal trends anyway.

Hiring appears to focus on process-heavy industries and functions. (AI business cases proven-enough to get $ for new roles?)

  • 34 of 40 roles cluster in four industries: healthcare, manufacturing, professional services, financial services
  • Functionally, most work is technology, transformation, and strategy. Only 10 tie to a named business function (HR, finance, marketing).
  • By the way, a few companies stand out. In a way, MNBOT is them, not the whole state right now: UnitedHealth/ Optum (13 postings), Thomson Reuters (4), U.S. Bank (3), nVent (2).

My read is that much of the hiring is team and capability setup (with lots of variation of course):

  • Sr/ directors are 22 of 47 roles.
  • 27 roles build new capabilities and 12 sit on AI-specific teams.
  • I see hiring into different org structures. Too early to call trends. But patterns I've seen include hiring into business units, corporate functions, and IT.

There's more action in consulting:

  • I didn't include national consultancies (BCG, EY, PwC, and friends) here. They'd have added another 1-3ish posts/ week, plus evergreen "resume harvester" roles. Buuuut ... what does that mean? Are they precursors for future hiring in industry or just a sign of flash-in-the-pan prestige projects that will fizzle once the consultants leave? Idk.
  • A few local consultancies (Trissential, plus consulting arms of Optum and Thomson Reuters) also show up. I included them above in my MN figures.

Some light reading

Ok, this ain't about job postings. Instead, here are my recent, related blog posts. Sharing in case my thinking interests you.

Why it makes sense for many companies not to hire for MNBOT yet.

This was kind of a revelation for me and really focused the industries where I look for interest.

In short: Follow the money. Companies should only hire up if AI has significant, short-term impact on value generation, risks, and available options, as they relate to one or more of their solution (product/ service), its production and delivery, or company admin.

For workers newer to AI

Simple things people can do to get traction with AI early on, before their company gives them a full roadmap.

I read a lot of stuff that over-complicates things for many non-technical people.

Instead, early in their AI journey, people can just create: 1. Simple AI tools ("jigs") to standardize routine tasks. 2. Automations that save them 10 hours or $10k per year. 3. Things that make their core work 1% better on every run. 4. Interfaces that let them replace rote interactions and manual work with automations.

Current postings

Notes: 47 roles at 31 Minnesota-run employers, posted Sep through Oct 15, 2026 (7 of them client-facing consulting roles). · Dates are estimates worked back from “posted X days ago”. · Role URLs expire of course. But I keep posting copies, should you need them. · To be listed, AI needed to be a meaningful part of roles, whether as an explicit term or by implication. But it didn't need to appear in the role title. · Roles sorted newest posting date first, within each role type, then alphabetical. Sections sorted.

Transformation & change (13)

Technical, data & AI (10)

Consulting (client work) (7)

Strategy & planning (7)

Programs & products (6)

Business leadership (4)

And there you have it.

May you ever keep the humans in charge of your own AI!