How Do You Tell Whether an AI Pilot Actually Saved Money?
Compare what the work cost before the pilot with what it costs now, measured the same way, and count everything the new version costs: the model bill, the subscriptions, and the hours people still put into checking its output. If the before number was never written down, you can’t tell yet, and rebuilding that baseline […]
What Should a Medical Practice Check First With AI Heading Into 2027?
Check five things on your own data before you plan any new AI for 2027: whether payers are paying visits at a lower level than you billed, whether you are paid what your contracts say, whether the AI tools you already pay for were vetted, whether anyone measures what those tools produce, and how many […]
How Should a Medical Practice Evaluate an AI Vendor Before It Buys?
Start with your own number before you take the first demo: name the one result the tool has to move and measure it on your practice’s own data, then judge every vendor against it. Then get in writing what MGMA tells practices to require of any AI vendor, including evidence of performance and known failure […]
What Should a Fractional Head of AI Cost in 2026?
A fractional Head of AI should cost well under what the constraint it fixes is costing your business, and the number should be set after someone has diagnosed that constraint, never read off a rate card. Our view is that in 2026 most of the fee should pay for judgment and verification, meaning the call […]
Where Does a Medical Practice Actually Lose Revenue, and Where Can AI Help?
In MGMA Stat’s January 6, 2026 poll, 48% of respondents named denials and appeals as the biggest revenue cycle leak and 23% named the front end, and their comments described the denial losses as overwhelmingly payer-driven, from medical necessity and non-covered services to bundling edits, prior authorization friction, eligibility problems and timely filing. In our […]
Where Does a Medical Practice Find the Money for AI in 2027?
In our read, mostly from money it already pays for work that software can now take on. We would look in four places first: billing and denial rework, the hours that go into prior authorization, front-office turnover, and the tools bought to patch around the EHR. We would fund a first AI project in a […]
Fractional Head of AI or Fractional CTO: Which One Does Your Company Actually Need?
A fractional CTO owns engineering, meaning the stack, the team building on it, and whether the software ships and stays up. A fractional Head of AI owns where AI gets pointed and whether its output can be trusted before anyone acts on it, so a company whose software is the bottleneck needs the CTO, and […]
Can AI Handle Prior Authorization for a Small Medical Practice?
Yes, for a small practice’s repeatable prior authorization steps, and we’d set two conditions: a person in the practice keeps the medical necessity call and signs off on every appeal, and the practice times its own authorizations before it buys anything. The Peterson Health Technology Institute (PHTI), which publishes independent evaluations of healthcare technology, lists […]
The four questions: is this worth building at all?
These four questions are our test for whether a thing is worth building at all, given what AI can and cannot reproduce. Run them before starting a business, before adding a service line, and before pointing AI at any process inside a company that already exists. Same four questions, and the first use is the […]
What Is a Fractional Head of AI, and When Does a Company Need One?
A fractional Head of AI is a part-time senior operator who owns two decisions inside a company: where AI gets pointed, and whether what it produces can be trusted before anybody acts on it. My rule of thumb: a company needs one once AI is touching work that carries money, and nobody’s job description says […]