Which kinds of work are missing from AI training data?

Which work is thin in public training data?

Four task types are consistently thin: back-office workflows, B2B negotiations, internal decisions, and long projects. All four are carried out inside companies, in tools that outsiders cannot read, and almost none of it is written for publication.

This page sorts the gaps by task type rather than by industry. It reflects the shift from models that answer questions to agents that carry out tasks, and it gives a referral partner a quick lens for scanning a personal network.

What are the four gaps?

Each gap has the same underlying cause. Public text shows finished results. Training an agent that must act needs the steps in between, the exceptions, the approvals and the outcome.

Why are back-office workflows so scarce?

Because nobody posts them. A published article may describe how to reconcile accounts, but it does not show a hundred real reconciliations with the mismatches, the questions to the vendor and the final correction. That detail sits in finance systems and email.

Records that pair each step with a resolution are especially useful: a ticket opened, escalated, answered and closed, or a purchase order changed, approved and invoiced. The guide on why agents need workflow records goes deeper on this shift.

Why are B2B negotiations missing?

Negotiations are confidential by design. Pricing, concessions and walk-away points are exactly what companies protect. The few public examples are sanitized or staged.

Real quote-to-contract records, with outcomes of won, lost or renegotiated, are therefore rare. They are also among the hardest to license because they involve counterparties. A company can only license what it has the right to, and where a customer's confidential terms are involved, rights review comes first.

Why are internal decisions and their reasoning missing?

Decisions leave outcomes in public, but reasoning stays private. A memo that weighs three options, records the objection and explains the choice is worth more as training material than the decision alone.

Look for companies that keep decision records with outcomes: board and steering notes, architecture decision records, pricing committees, vendor reviews. Where the outcome is known later, the record shows whether the reasoning held up.

Why are long projects missing?

Short examples mostly teach short tasks, while real work stretches over weeks as context changes. Complete project histories, from kickoff to handover, show how requirements shift and how teams recover. The guide on long-horizon tasks covers why this matters.

How can a partner scan their network?

Use the 3-question gap scan when you talk to an owner or executive:

1. Does your team follow multi-step processes that live in software tools, such as quoting, onboarding, claims or close?
2. Are the results recorded, including the outcome and any exceptions?
3. Do those records go back several years and can someone export them?

A yes to all three is a reason to look closer. The company fit checker runs a preliminary, non-binding screen without contact details. The company still has to meet the baseline: 50+ full-time employees at peak (contractors excluded), several years of documented operations, rights to license and an authorized sponsor. Companies with 10-15+ systems and long histories tend to screen best. For how industry-specific records fit, see vertical AI companies and the industry data they need.

What this does not mean

• It does not mean every company's records are wanted. Buyers decide after review.
• It does not mean the data is sold. Companies keep ownership and license it, and nothing is binding until they agree price and terms and sign.
• It does not mean your records make you replaceable; see whether AI trained on your data will replace your business.
• Partners never handle records. They introduce and give basic fit information.

Beyond headlines, the market is described in enterprise AI data licensing deals.

How rewards work

Partners earn 25% of the eligible platform fees SourceX actually collects from the referred company's licensing deals, capped at $100,000 per referred company. The reward is paid only after the buyer pays and SourceX receives its fee; no reward is guaranteed. The reward is a share of SourceX's fee and is never deducted from what the company receives.

Next step

Pick one business you know that runs on repeatable workflows, then register as a partner to make the introduction. The steps after that are listed in how it works.