· Software
Most AI Pilots Do Not Fail on the Model. They Fail on the Handoff Nobody Owns.
Three different research teams, three different years, and the data keeps landing on the same answer.
More than 80 percent of AI projects fail, according to a RAND Corporation study that interviewed 65 practitioners with at least five years building AI and machine learning systems. That is roughly double the failure rate RAND cites for ordinary IT projects. A year later, S&P Global Market Intelligence found that the share of companies abandoning an AI project before it reached production jumped from 17 percent in 2024 to 42 percent in 2025. Gartner went further, predicting in June 2025 that more than 40 percent of agentic AI projects will be canceled outright by the end of 2027, and that only about 130 of the thousands of vendors marketing their products as agentic actually qualify.
Three teams, three years, one conclusion holding up across all of them: the bottleneck is almost never the model. RAND ranked the leading cause of failure as a leadership problem, not a technical one, usually a mismatch between what executives asked for and what the team actually understood and built. Read the three studies side by side and a pattern holds. The gap opens after the demo, when someone has to wire the thing into the company's real data, its real legacy systems, and its real approval chain, and nobody specifically owns getting it there.
That gap is the actual argument for hiring a forward-deployed or embedded engineer instead of buying another tool. MojoSoftware does this work: one engineer, embedded with the client, on the client's own systems, staying until the thing runs in production and the client's own people can operate it without help.
Steelman: do not hire one to fix a leadership problem
Here is the honest case against reaching for an embedded engineer first. RAND's own data says the top cause of AI failure is that leadership never pinned down the problem before building anything. If that describes your situation, paying a specialist's premium rate to integrate a tool nobody has actually scoped does not fix that. It just burns the budget faster than a stalled subscription would, because now a premium salary is building the wrong thing with more conviction. An embedded engineer is a cure for a defined technical blocker, a legacy system, a data access wall, an integration no generic connector reaches. It is not a cure for an undefined one. If your team cannot state in one sentence what the tool is supposed to do and how you will know it worked, settle that on paper first, before hiring anyone to build it.
Where the case holds
Once the problem is genuinely scoped, the math changes. Here is a hypothetical, not a client case: a mid-size company spends four months and $60,000 in software and cloud fees piloting a tool meant to route customer tickets automatically, and adoption never clears 20 percent because the tool cannot read the company's own ticket history, which sits in a system the vendor's standard connector does not support. That is not a cheap failure. It is $60,000 gone plus four months of the same backlog the tool was supposed to clear, and that second cost rarely makes it onto anyone's spreadsheet. A scoped engagement, an engineer embedded with the client's own data and systems for four to eight weeks, often lands in a similar dollar range. The difference is what is left afterward: a working integration the client's team owns, not a renewal notice. The Gartner cancellation forecast and the S&P abandonment numbers both describe money spent on exactly this kind of unfinished wiring.
The part that actually matters: how the engagement ends
The real difference between an embedded engineer and a subscription is not the invoice. It is the exit. A subscription renews itself by default, usually at a higher price, and keeps doing that until someone actively cancels it. A good embedded engagement has a defined end: the integration gets built, documented, and handed to the client's own team to run, and then the engineer leaves. If an engagement instead turns into a standing retainer with no date anyone can point to for when it ends, that is the same recurring cost as a bad SaaS contract, just priced as a person instead of a seat.
Ask that question before signing anything: what does finished look like, and who runs the system the day the engagement ends. If nobody can answer that in a sentence, you are not buying engineering. You are buying a second subscription that happens to have a name attached. If you already know your blocker is technical rather than organizational, it is worth a conversation.
Sources
References used in this article. Links also appear alongside the relevant claims.
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