IGA Benchmark Report 2026 — Engineering Capacity & Exit Risk

Benchmark Report · 2026 · Free Download

In 2021 Engineering Capacity Was a Headcount Problem. In 2026 AI Made It an Expertise Problem.

AI has changed what engineering value means at exit. The model you chose to scale your team now determines your technical debt rate, IP exposure, and exit multiple. This report maps all five models against the four dimensions acquirers examine in due diligence.

Which of the five engineering models you're running — and what it's costing you
How AI impacts each of the capacity models
The full comparison matrix: technical debt, IP ownership, team transferability, EBITDA
A 10-minute self-diagnostic to score your specific exit exposure
Hold-period cost trajectory across all five models over 72 months

25 minute read

35 pages

2026 Edition

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What's inside

35 pages. No filler.
Everything acquirers examine.

The report maps what actually changed in engineering value when AI entered teams at scale — and why the capacity model you chose in 2021 now determines your exit multiple.

What AI Changed

AI didn't create technical debt. It accelerated it in models that were already structurally weak. This section explains the mechanism and why it compounds.

Why bad engineers with AI are worse, not better
Stack Overflow 2025: 66% spend more time fixing AI code
GitClear: 4× more duplicate code in AI-assisted output

The Five Models Compared

Direct Hire · Recruitment Agencies · Traditional Outsourcing · Freelance Platforms · Build-Operate-Transfer. Each described as it actually works — not how it was sold.

Who employs the engineers
Who owns the IP
What happens at exit

Hold-Period Cost Trajectory

Cumulative engineering cost across a 72-month hold period for a 10-engineer team. Two lines improve. Three do not. The difference compounds every month.

BOT: only model where cost falls
Outsourcing: permanent vendor margin, never improves
Agency: placement fee spikes at every churn cycle

The comparison matrix

One table. Four dimensions.
Five models.

The ratings follow from structural mechanics — who employs the engineers, who owns the IP, what happens at exit. Not vendor data. Not opinion.

Model	Technical Debt	IP Ownership	Team Transfer	EBITDA Trend
Direct Hire	LOW	CLEAN	HIGH	IMPROVING
Recruitment Agencies	MEDIUM	CLEAN	MEDIUM	FLAT
Traditional Outsourcing	HIGH	CONTESTED	NEAR ZERO	DEGRADING
Freelance Platforms	HIGH	CONDITIONAL	ZERO	UNPREDICTABLE
Build-Operate-Transfer	LOW ★	CLEAN ★	HIGH ★	IMPROVING ★

The full report includes AI overlay ratings, model-by-model scoring detail, and a 10-minute self-diagnostic.

Expert contributors

What due diligence
actually looks like.

"What acquirers actually look at is not what most CTOs prepare for. Whether knowledge lives in documentation or in three people's heads. When it's the latter, the acquirer knows exactly what they're buying: a dependency risk dressed up as a team."

Jimi Li CTO / CIO, ALM

"On a EUR 50 million deal, the difference between a clean, flexible engineering cost structure and a rigid one can easily be EUR 10 to 15 million in enterprise value."

Petar Petrovski Former Investment Banker, UBS United Kingdom

"The biggest mistake is wrapping developers in poor QA, deployment, and product management processes that were never questioned after they were put in place. That is the single biggest source of engineering waste entirely within the CTO's control to address before exit."

Sebastian Aspland Tech Partner, Tenzing

Who this report is for

If you raised capital between
2020 and 2022, this is for you.

Over 52% of buyout-backed companies have been in portfolios for four or more years. Exit preparation is no longer theoretical. It's active.

CTOs & VPs Engineering

At investment-backed B2B SaaS and tech companies. You chose the capacity model. You need to know what it's producing at exit — and whether you still have time to act.

PE Portfolio Operators

On value-creation plans or approaching an exit window. The engineering cost structure is already baked into the EBITDA. The question is whether there's runway left to change it.

Founders & Finance Leaders

Preparing for a first institutional exit. Understanding how acquirers value engineering teams — and what the due diligence process actually examines — before the process starts.

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35 pages. Five models. Four dimensions. One diagnostic. Everything you need to understand your exit exposure before due diligence begins.