At a Glance
- AI tool selection routinely happens before anyone has measured whether the organization has the shared understanding, cross-functional alignment, or process maturity to actually use what it’s buying.
- Research from Secured Research finds that among equipment finance companies that shelved or significantly scaled back an AI initiative within eighteen months of launch, 58% report no formal organizational readiness assessment was conducted before the tool was selected; firms that did conduct a readiness assessment before selection reported an initiative survival rate roughly twice that of firms that skipped it.
- Two Converge AI sessions on October 8 attack this from complementary angles: Deborah Reuben (CEO/Founder, TomorrowZone) and Moto Tohda (VP Information Systems, Tokyo Century USA) on the shared-understanding and alignment scoring an organization needs before it can run its AI “parkour course,” and Tawnya Stone (VP Strategic Technology, GreatAmerica) on building AI readiness as a people-and-process capability rather than a technology purchase.
- A firm that sends only its technology buyer to evaluate readiness is measuring the wrong thing with the wrong person.
The Postmortem That Names the Wrong Cause
When an AI pilot gets quietly shelved, the postmortem — when one happens at all — almost always names a technology cause: the model wasn’t accurate enough, the vendor’s roadmap slipped, integration took longer than scoped. Those causes are real and also frequently downstream of a readiness gap nobody measured going in: operations didn’t understand what the tool was supposed to change about their workflow, IT and the business unit had different definitions of what “working” meant, or the executive sponsor changed roles six months into the project and nobody had documented enough shared understanding for a successor to pick it up.
A technology postmortem cannot see an organizational cause, because nobody scored the organizational variable before or during the project. It only shows up as “the tool didn’t work,” which is a diagnosis that sends the next initiative shopping for a different vendor instead of fixing the actual gap.
What “Shared Understanding” Actually Means as a Measurable Thing
Reuben and Tohda’s framing — that AI adoption is a parkour course requiring specific readiness conditions, not a straight line from purchase to value — treats organizational alignment as something that can be scored rather than assumed. A concrete version of this: can the operations lead who will use the tool daily and the executive sponsor who approved its budget describe, independently and in the same terms, what success looks like in month six? In most stalled initiatives, they cannot, and the gap between their two answers is a readiness score nobody calculated before the contract was signed.
Why This Is a People Project Wearing a Technology Costume
Stone’s session reframes the same problem from the capability-building side: an AI-ready organization is built through people and process development, not technology procurement, and firms that treat adoption as a training-and-rollout afterthought to a tool purchase are building the capability backward. The technology selection is frequently the easiest and fastest part of the entire initiative. The harder and slower part — building the shared vocabulary, the process changes, the trust in the tool’s output — is the part most project timelines don’t budget for because it doesn’t show up on a vendor’s implementation Gantt chart.
A Firm That Scored Readiness First
A middle market equipment lender considering an AI-assisted document review tool spent six weeks before vendor selection interviewing the operations staff who would use it daily and scoring, on a simple rubric, how aligned their expectations were with the executive sponsor’s stated goals. The gap they found was specific: the sponsor wanted headcount efficiency, and operations staff assumed the tool was meant to reduce their error rate, not their team size, and were prepared to work around anything that read as a headcount threat. A VP of operations at the firm described resolving it before selection: “We would have bought a tool aimed at the sponsor’s goal and rolled it out to a team quietly resisting it for a different reason nobody had said out loud. Finding that out before the RFP, instead of during a stalled pilot, is the entire reason this one is still running.”
Why This Gap Survives Every Steering Committee
A steering committee is structurally the wrong forum to catch a readiness gap like this, because everyone in the room has already self-selected into being aligned enough to attend — the sponsor, a senior IT lead, maybe a department head. The person whose actual daily workflow the tool will change is rarely in that room, and the alignment being measured at the steering-committee level is alignment among people who agree on the project in the abstract, not among the specific individuals whose behavior determines whether the tool gets used the way it was designed to be used. A readiness score built from steering-committee consensus measures the wrong population.
Turning Readiness Into an Ongoing Measurement, Not a Gate
The firms getting the most value from this framing are not treating readiness as a one-time gate passed before a project starts. They are treating it as a metric revisited at defined checkpoints through the pilot — thirty days, ninety days, first full quarter — because organizational readiness is not static. A team that scored low on shared understanding at kickoff can close that gap during a well-run pilot, and a team that scored well can drift apart if the executive sponsor changes or the tool’s actual behavior diverges from what was communicated at launch. Building the readiness check into the project’s ongoing cadence, rather than only its front door, catches the drift before it produces the shelved-initiative outcome the data above describes.
This also reframes what an executive sponsor’s job actually is on one of these initiatives. It is not simply approving budget and receiving a status update at the steering committee. It is being personally responsible for maintaining the shared understanding the readiness score depends on, which means noticing when a successor takes over the sponsorship role, when the tool’s behavior in production starts to diverge from what was pitched at kickoff, or when the operations team’s stated understanding of the goal quietly drifts from the one the sponsor still holds. Firms that assign this as an explicit, named responsibility — rather than an implicit expectation of whoever holds the sponsor title — are the ones catching the drift while it is still cheap to correct.
What To Do About It
- Score organizational readiness — shared understanding between sponsor and end users, process maturity, defined success criteria — before tool selection, not after a pilot stalls.
- Require the executive sponsor and the daily end user to independently describe what success looks like in month six, and treat any gap between their answers as the actual project risk.
- Budget the people-and-process capability-building work as its own line item, separate from and comparable in size to the technology procurement budget.
- Send both a technology decision-maker and an operations or change-management leader to the October 8 Reuben/Tohda and Stone sessions at Converge AI — this is explicitly not a single-owner problem.
The tool rarely fails on its own terms. It fails because nobody scored whether the organization around it was ready to run the course, and that score is knowable in advance if anyone bothers to measure it. Converge AI’s October 8 sessions from Reuben, Tohda, and Stone are built to give you that measurement before the next contract gets signed. Bring your team and register at Converge AI.
Secured Research is a commercial capital research practice formed as a joint venture between Monitor/ABF Journal and Sawbux. Since 2010 its panels have surveyed more than 900 secured finance companies, 28,000 middle-market decision makers, 11,000 equipment and technology sellers, and 506,000 small businesses. Findings cited in Monitor Suite are drawn from the following always-on 2026 research programs:
- 2026 Annual Survey of Commercial Finance Decision Making — more than 6,200 equipment buyers, from small business through the upper middle market, across 38 SIC industry groups.
- 2026 Commercial Study of Indirect Asset Finance — 10,609 equipment vendors across 27 SIC industry groups, from local dealers to the largest global OEMs.
- 2026 Back Bench Operations Research — more than 600 finance companies across the capital stack, examining operations, leadership, customer experience, and go-to-market strategy.
