McKim & Co. · An operations advisory practice
Most AI investments fail. Let's make you the exception.
The tool isn't why they fail. The operation is. We fix the operation first — so when AI arrives, it works.
The market without operational preparation
This is how AI implementation is going for most.
$252B
Invested in AI in 2024
Total global corporate AI investment, private funding up 44.5% — Stanford HAI AI Index, 2025
74%
Show no tangible value
Survey of 1,000 CxOs across 59 countries — BCG, “Where’s the Value in AI?”, October 2024
42%
Of companies abandoned most AI initiatives
Up from 17% the year before; 1,000+ enterprises in North America and Europe — S&P Global Market Intelligence, March 2025
61%
Report no bottom-line impact from AI
Just 39% attribute any EBIT (operating profit) impact to AI, and most of those put it under 5%; 1,993 respondents in 105 nations — McKinsey Global Survey on the State of AI, 2025
In our experience, that gap traces to one thing: the operation wasn’t evaluated before the tool was purchased. McKinsey found that fundamentally redesigning workflows made one of the strongest contributions to business impact of all the factors it tested — and that the organizations seeing real value were nearly three times as likely to have done it. Redesign the work first, then choose the tool. That sequencing is what this practice does.
Every one of these is solvable. In sequence. Before you buy anything.
The pattern across all five
Five reasons AI fails. All of them operational.
These are the five we find most often. None of them are technology problems — they’re operations problems the wrong tool makes visible, expensively, at scale.
01
The process was never documented.
Two people run it from memory. There is nothing for AI to follow — only a person to replace. You can't automate what isn't written down.
02
Shadow AI created exposure nobody audited.
Staff was already using ChatGPT with client data before any policy existed. The insurer is now asking. The audit trail doesn't exist.
03
Handoffs weren't owned by anyone.
Sales tells ops verbally. Ops tells billing by memory. When nobody owns the workflow, nobody owns the failure — and AI executes those gaps at machine speed.
04
The tool was bought before the operation was evaluated.
Vendors assessed the tech stack. Nobody walked the floor. The organization couldn't absorb what it just paid for.
05
Capability left with the consultant.
The engagement ended. Nothing ran without outside help. The organization was dependent by design, not by accident.
The receipts
A career of fixing operations, before the tool.
>$4M
Annual savings · Post-merger integration
200%
EBITDA expansion · Churchill Downs subsidiary
24×
Platform scale · 500 → 12,000+ units
Every number above has the same person behind it. Mike McKim — operations executive across healthcare services, regulated gaming, and multi-site logistics; engineer by training; COO and VP Operations seats in PE-backed and founder-owned companies. He built the systems, not just the slide decks. More about Mike →
A practice, not a platform.
McKim & Co. is an operations advisory practice, run by an operator. The assessment, the governance products, the reports — those are tools the practice built, because the work needed them. They are not the practice. The work is what it has always been: look hard at an operation, name what it can actually support, and build the structure that holds what comes next.
There are two ways to engage.
AI Operational Readiness
For owner-operated businesses, 5–200 people
Know exactly where your operation stands before you spend a dollar on AI. Start with the free Readiness Assessment — a real diagnostic, not a lead-gen tool. You'll leave with something true about your operation whether or not you take another step.
Start the free assessment →
Interim & Integration Leadership
For midsize and PE-backed companies, $5M–$250M
Post-close stabilization. Post-merger integration. Margin recovery. Led the operational merger of a $100M healthcare enterprise — full platform migration in eight months, $4M in annual savings found line by line. Available for interim, fractional, and project engagements.
Start the conversation →
Why this site looks the way it does
Everything here — the assessment engine, the pattern analysis, the reporting, the payment rails, this page — was designed and built in-house by the founder, working with AI the way we advise clients to work with it: on a documented foundation, governed, and pointed at a real operational need. We don't sell AI. We use it the way it should be used. This site is what that looks like.
In their words
He wasn't someone who solved problems in isolation, but someone who built the capability of the people around him.
Mark Schlepphorst
Solution Security Officer, former colleague
He has a rare ability to identify gaps in technology infrastructure before they become problems — and to build plans that close them.
Syaidah Awls
HR Administrator, former colleague
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