The AI Bets Audit
Your portfolio of AI bets, ranked, evidence-backed, and board-ready in two weeks.
The AI Bets Audit is our front-door diagnostic. We map every live and proposed AI bet, score them on value and evidence, and pretotype the highest-stakes ones, so you walk into the board with a defensible call on what to fund, fix, and kill.
- 95%
- of enterprise GenAI pilots fail to move the P&L
- $37B
- spent on enterprise GenAI in 2025
- 23%
- of firms can tie AI to revenue or cost
The problem
Boards funded AI. The returns never showed up.
Budgets, pilots, and pressure are everywhere. Measurable value is not. The hardest question in the building isn't "how do we do AI?". It's "which of these projects actually deserve more capital, and which should we kill?"
95%
of enterprise generative AI pilots fail to produce measurable P&L impact.
MIT NANDA, 2025
60%
of firms report minimal revenue or cost gains despite heavy AI investment.
BCG, 2025
Only 23%
of companies can currently tie AI initiatives to new revenue or lower costs.
Bain & Company, 2025
Only 16%
of enterprise AI deployments qualify as true agents, the rest are hype.
Menlo Ventures, 2025
What you get
The AI Bets Audit
In two weeks we map your live and proposed AI bets, rank them on value and evidence, and pressure-test the highest-stakes ones with real behavioural pretotypes, so every bet gets a board-ready call: fund, fix, or kill.
What you walk away with
- A mapped portfolio of every live and proposed AI bet across the business
- Value, evidence, and risk ranking for each bet, comparable on one page
- 1–3 pretotypes built on real behavioural evidence for the highest-stakes bets
- A lightweight working demo, concierge workflow, or Wizard-of-Oz agent where useful
- A board-ready funding decision for each bet: fund, fix, or kill
- A recommended next experiment or implementation path for the bets worth backing
01
Map
Surface every live and proposed AI bet into a single portfolio view.
02
Rank
Score each bet on value, evidence, adoption, governance risk, and time-to-impact.
03
Pretotype
Run fast behavioural tests on the high-stakes bets: evidence, not opinion.
04
Decide
Hand you a board-ready call on which bets to fund, fix, and kill.
Who it's for
Built for the people who own the AI budget, and the results.
Start here if you're a mid-market or enterprise organisation already spending on AI but not seeing enough value back. We work best where workflows are expensive, document-heavy, and weighed down by compliance.
Best buyers
Best sectors
Why us
“We don't sell you AI. We prove which AI agents deserve to exist. Pretotyping was built for exactly this problem, finding The Right It before you build It right, and we've now run it across 4,000+ experiments for enterprise teams.”
Leslie Barry
Founder, Exponentially · Pretotyping practitioner since 2017
- 4,000+
- experiments run
- $68M+
- saved on bets not worth backing
- 50+
- enterprise teams
FAQ
What executives ask before booking an AI Bets Audit
What is AI Pretotyping?+
AI Pretotyping is the discipline of validating AI use cases, agents, and workflows before enterprise implementation. Instead of building first and hoping for ROI, you run fast behavioural tests to prove which workflows create measurable value, then build only those.
How is this different from an AI strategy deck or a consultancy pilot?+
Strategy decks give you opinions; pilots commit budget before you have evidence. The AI ROI Sprint sits between the two: a fast, paid, executive-grade method for deciding which AI projects to kill, iterate, or fund, backed by real behavioural data.
How long does the AI ROI Sprint take?+
Two to four weeks. You leave with an opportunity map, a value-and-risk ranking, 1–3 pretotypes, and a board-ready decision on what to fund, fix, or kill.
Do you build the AI agents too?+
We can. The Sprint is the front door, once a use case is proven, we build or orchestrate the agent workflow, governance, integration, and adoption. But we prove value first, so you never overbuild the wrong thing.
What does it cost?+
The diagnostic Sprint typically runs $25k–$50k. Follow-on implementation of a proven agent workflow ranges from $100k+, scaling to an enterprise-wide AI experimentation program where it makes sense.
Who should be in the room?+
The people who own the AI budget and the results, typically the CIO, CFO, COO, Chief Digital Officer, or Head of Innovation, Product, or Transformation.
Map your AI bets
See which AI bets deserve funding, before the next budget cycle.
We're opening a limited number of private AI Bets Audits. Bring your AI spend; leave with a board-ready call on what to fund, fix, and kill.