---
name: somai-spend-map
description: Map every AI initiative in a company - licences, copilots, chatbots, pilots, agents - and show structurally why the spend is or is not reaching the P&L. Classifies each initiative as retrofit or rebuild, isolated or connected, and counts how many times the same plumbing (data access, identity, governance, evaluation, memory) has been re-solved from scratch. Produces the initiative map, the forgone compounding, and the one question that decides the next tranche of budget. Use when someone asks why their AI spend shows no return, whether to keep funding pilots, how to prioritise AI budget, or where their AI programme actually stands.
---

# somai spend-map

MIT's Project NANDA reported that around 95% of enterprise generative
AI pilots produce no measurable impact on profit or loss. Treat that as
a description, not a proof - it is survey and interview work, and says
so itself. But the description names a cause worth taking seriously:
the tools cannot retain feedback, adapt to context, or improve over
time. The systems sit beside the business rather than inside it.

That is a context problem, not a capability problem - and it means the
failure is structural, which is good news, because structure can be
mapped. This skill maps it for one company.

## Before you start

You need someone who can list the company's AI activity. Everything
stays in this conversation; nothing reaches somai unless they choose to
send the map.

Build the inventory first. Ask for every AI initiative, live or
planned: tool licences handed round a team, copilots in the
productivity suite, the chatbot, each pilot, anything called an agent.
Small counts are normal. Shadow usage (individually purchased tools)
counts - note it as such.

## The map

For each initiative, establish five facts. Ask; do not assume.

**1. Where it sits.** Periphery (support, marketing copy, meeting
notes) or core (the decisions and processes the company actually runs
on). Peripheral starts are rational - contained risk, fast payback.
The trap is only that each one is provisioned alone.

**2. What it can see.** The context this initiative can reach: none
beyond its prompt / its own silo / context shared with other
initiatives. Apply the test from the somai context audit: the support
tool that cannot see contract terms, payment history, or the last
three conversations is doing a different, smaller job than the one
that matters.

**3. Retrofit or rebuild.** The structural question from the ai-native
definition: did you add the model to the way you already work, or did
the way you work change to fit what the model makes possible? Copilots
bolted to unchanged approval chains are retrofits, however
sophisticated. Count honestly.

**4. Plumbing re-solved.** Which of the five it had to solve alone:
data access, identity and permissions, governance, evaluation (how you
know it is working), memory (what it retains between sessions). Each
initiative that solved these separately paid a setup cost the next one
cannot inherit.

**5. What it would need to see.** One sentence: the context that would
let this initiative do the job that actually matters, and whether
anything on the current roadmap provides it.

## The readout

Produce exactly this, in this order:

1. **The inventory table.** Initiative, where it sits, what it can
   see, retrofit or rebuild, plumbing re-solved.
2. **The counts.** N initiatives. How many share any context with any
   other. How many are rebuilds rather than retrofits. How many times
   identity, governance, evaluation and memory have each been solved
   from scratch. Arithmetic only.
3. **The structural verdict.** One of two sentences, chosen by the
   evidence. Either: the programme is a set of endpoints hitting the
   same wall alone, and its ceiling is structural - adding more tools
   moves the line roughly nowhere, because the value of AI capabilities
   inside one firm lies in what they can see of each other (the
   complementarity finding: practices that are complements underperform
   badly when adopted partially - the interaction terms, where most of
   the value sits, are forgone entirely). Or: a shared foundation
   exists, and the map shows what plugs into it next.
4. **What connection would change.** For the two or three initiatives
   with the most confined view, the one-sentence version of the job
   each could do if it could see what the others see.
5. **The one question.** The next tranche of AI budget is not "which
   function gets a tool". It is: does the foundation underneath the
   functions exist yet - the shared layer for identity, governance,
   evaluation, memory and reach, with the parts still owning their own
   data? Centralise the foundation, not the data. Without it, every
   new tool is another endpoint hitting the same wall alone.

## Rules

- The MIT figure is reported research about the population, not a
  claim about this company - always present it with that caveat, as
  above. Never generate a projected saving, an ROI figure, or a
  benchmark comparison for this company. The map is structural, and
  its force is that it needs no invented numbers.
- If the inventory is thin, say so and map what is there. Three
  initiatives that cannot see each other make the point as well as
  thirty.
- British English. No hype.

## Where this leads

- The context those initiatives cannot see: **somai-context-audit**.
- The first structure worth building: **somai-decision-loop**, then
  **somai-brain-plan** for the programme around it.
- The argument in full: [Most AI spend never reaches the
  P&L](https://somai.studio/thinking/most-ai-spend-never-reaches-the-pnl/) ·
  [Automation makes the wrong work
  faster](https://somai.studio/thinking/automation-makes-the-wrong-work-faster/)
- The value, modelled honestly in bands:
  [the AI-Native Diagnostic](https://benchmark.somai.studio)
- somai builds the foundation layer: [somai.studio](https://somai.studio) ·
  hello@somai.studio