Lightbloom AI vs a consultancy vs an AI agency vs hiring in-house: which one actually changes the P&L?
A consultancy delivers a plan, an agency a build, a hire their time. What each is right for, and the option that starts from how the work really runs.
The option that changes the P&L is the one that starts from how the company actually works, not from a plan, a build or a hire. A consultancy is paid for the plan, an agency for the build, and an in-house team for its time, and each is the right choice in a specific situation. Lightbloom AI starts every engagement with Transcript and the world model it builds, which is why it is worth considering and why it is not for everyone.
Most AI spend is committed before anyone knows whether it worked
BCG's survey of 1,000 executives (BCG, 2024) put companies yet to show tangible value at 74 percent. MIT NANDA's 2025 study, as reported by Fortune (2025), found that about 95 percent of pilots had little or no measurable P&L impact.
Most of those projects did not fail at the technology. They failed at the choice of what to build: automation of the documented process, while the real work carried on around it.
A consultancy is the right call when the answer is a decision
Hire a consultancy when the deliverable is a decision: which business to exit, how to restructure a function. You are paying for pattern recognition across many companies.
The engagement ends at the recommendation, and the fee was earned when the deck was accepted. If the plan does not fit how the work actually runs, you find out after they have left.
An AI agency is the right call when you already know exactly what to build
An agency is a good buy when the scope is precise: a document pipeline for one named workflow, say. The MIT researchers, in Fortune's account, found that purchasing from specialised vendors succeeded about 67 percent of the time, while internal builds succeeded a third as often.
An agency builds what it is asked to build. Choosing the process is your job, and the base rates above say that is where programs go wrong. The project is done at go-live; nobody verifies the P&L effect, and running it is your problem from that day.
Hiring in-house is right when AI is the product, and slow when it is the tool
If AI is what you sell, hire. If it is a way to run finance or operations cheaper, the maths changes. Among EU enterprises that considered AI and did not adopt it, 71 percent cited a lack of relevant expertise (Eurostat, 2025). Deloitte's survey of 3,235 senior leaders (Deloitte, 2026) names insufficient worker skills as the biggest barrier to putting AI into existing workflows. In the same survey, 74 percent hope AI will grow revenue and 20 percent see it doing so already.
In a mid-sized company the first hire has to be strategist, engineer and change manager at once. Payroll starts on day one. The verified number, if it comes, comes quarters later.
The four options side by side
| Consultancy | AI agency | In-house hire | Lightbloom AI | |
|---|---|---|---|---|
| Who decides what to build | You, from their recommendation | You, before the brief | The hire and their sponsor | Together, from discovery; every opportunity gets a number first |
| Who builds | Usually a separate firm | The agency | The hire | Lightbloom AI's engineers, with your team |
| Who stays to run it | Your team | Your team | The hire, if they stay | Lightbloom AI, until your team runs it |
| How the result is checked | Rarely; the report is the deliverable | At go-live, if at all | Self-reported by the builders | Against a business number agreed before the build |
| Best for | Strategic decisions | A precise scope | Companies where AI is the product | Owner-operated companies that want the build, not a report |
| Not for | Getting things built and run | Choosing what to fix | Results needed this year | A report, or a build without verification |
Our view
Our view, and a CFO should press us on it: most AI money goes on the build, but most AI projects are lost before the build, at the choice of what to build. Seventy-four percent of companies with no tangible value mostly built the wrong thing well.
The alternative is to start with the world model. Transcript hears everyone in the company, writes up every problem with a number, and the company chooses the visions worth building before anything is built. The partner then builds with the company's team and stays until it runs. How that works, in full.
Questions people ask next
Why not a consultancy for strategy and an agency for the build?
Many do. You then own the gap: the plan that does not fit the real process, and the build nobody verifies.
Do you only pick easy wins?
We pick the wins that show up in your numbers. Often unglamorous ones in finance and operations, because those are the ones that move EBITDA.
What if we already have an internal AI team?
Then discovery is usually what they are missing, and it is where we start. They build with us, and they own what ships.
What size of company does this work for?
Owner-operated companies that run on people, where enough of the work sits with the team for a build to move a business number. For one precise, well-scoped build, a good agency is usually the better buy.
Lightbloom AI is the option here that starts from the company itself: the world model first, then the visions the company chooses, built with its team. The full picture is at /service-offering.
References
- BCG, AI Adoption in 2024: 74% of Companies Struggle to Achieve and Scale Value (2024), https://www.bcg.com/press/24october2024-ai-adoption-in-2024-74-of-companies-struggle-to-achieve-and-scale-value
- Fortune, MIT report: 95% of generative AI pilots at companies are failing, reporting on MIT NANDA, The GenAI Divide: State of AI in Business 2025 (2025), https://fortune.com/2025/08/18/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo/
- Eurostat, Use of artificial intelligence in enterprises (2025), https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Use_of_artificial_intelligence_in_enterprises
- Deloitte, State of AI in the Enterprise, 2026 report (2026), https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.html
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