❓ Problem

Every company wants an AI employee. Very few have checked what that employee will be reading on day one.

The numbers are grim. Gartner predicts that 60% of AI projects without AI-ready data will be abandoned through 2026, and 63% of data leaders it surveyed lack confidence in their data practices for AI. It’s even worse at the coalface: in Validity’s latest CRM study, 76% of companies said less than half of their CRM data is accurate and complete, and 37% admitted staff make up data to keep the bosses happy. That’s the material agents are about to learn from.

Here’s the kicker. Agents are already shipping. A recent Modern Data survey found 57.3% of organizations are piloting or running AI agents, yet only 8.4% say the data feeding them is trustworthy enough for production. Fivetran’s readiness index found only 15% of companies are fully prepared for agentic AI, even though 41% already have agents live.

A human employee who finds three conflicting refund policies asks someone. An agent picks one and confidently tells a customer. The model isn’t the bottleneck. The filing cabinet is.

✅ Solution

An agency that gets company data ready for AI agents, one workflow at a time.

• Audit the mess. Crawl the CRM, Google Drive, help desk and Slack. Surface duplicate records, conflicting documents, stale pricing and orphaned files nobody owns.
• Pick one workflow and make it bulletproof. Start with customer support. Sit with the team, approve the current answer to every common question, retire the rest, and assign an owner to each source of truth.
• Sort out who sees what. Map access permissions before the agent gets connected, so the support bot can’t quote salary bands from an HR folder someone shared with “anyone with the link”.
• Connect and stress-test. Wire the cleaned knowledge into whichever agent the client has chosen (Intercom Fin, Zendesk AI, a custom build), then run it against a few hundred real historical tickets before handover.
• Stay on as the caretaker. A monthly retainer catches new contradictions, broken connections and documents that drift out of date.

The wedge is a service. The endgame is software: every engagement teaches you which checks repeat, and those become the product.

📊 Key Numbers

Market size

• The AI consulting services market is worth roughly $11.9 billion in 2026, growing about 25% a year toward $74 billion by 2034, with the US the single biggest buyer.
• The software side is just as big. The data preparation market sits at around $7.6 billion and is forecast to hit $33 billion by 2035.
• The pain has a price tag. Gartner puts the cost of poor data quality at an average of $12.9 million a year per organization (self-reported by vendor customers, so treat it as directional).