The AI agent most companies use doesn't code — it consolidates, drafts, and organizes

There's a persistent myth about AI agents: that they're a tool for technical teams, that you need to code or have an engineering department to build them. Data Anthropic published this week dismantles it with real production evidence. They analyzed a huge sample of Claude Cowork sessions — their autonomous agent tool — from a large number of organizations in mid-year. The result: only a small share of sessions involve software development. The largest use, well ahead of the next category, is business operations: reports, checklists, and reconciling scattered spreadsheets.

The most common agent use isn't coding — it's the work nobody wants to own

The most common tasks within the business operations block are exactly the kind of work that exists in any company without a tech department: pulling scattered updates into a single report, building employee onboarding checklists, and reconciling spreadsheets arriving through different channels. None require code. All require time — the same time that costs money. In second place is content creation: drafts, slide decks, proposals. Software development, which many assume is the core use case, only ranks third.

Hours back every week: what each employee recovers in production

Several independent studies this year converged on the same conclusion: employees using agents in production recover several hours of work every week. McKinsey, Salesforce State of Service, Slack Workforce Index, and Anthropic's enterprise telemetry all land on very similar results. In the highest-friction roles — customer service and senior practitioners — savings run even higher. Those hours aren't recovered from creative or strategic work: they come from the same type of work that dominates the sessions — processing, organizing, consolidating.

• Consolidating weekly project updates from many different sources into a single document.
• Generating a first draft of a commercial proposal from meeting notes.
• Comparing two versions of a contract and listing differences clause by clause.
• Building an onboarding agenda for a new hire based on the existing process.
• Classifying and prioritizing a support request inbox.

The cost of doing that work — and the cost of not doing it

When an agent handles customer service, the cost per ticket drops to a fraction of a human-handled ticket. Most executives who deployed agents report measurable return within the first year, and a growing share already have at least one agent in production, according to Google Cloud data. But the cost that rarely appears in the calculation is the time quietly accumulating without visibility — the report nobody consolidates on time, the checklist that doesn't exist, the spreadsheet living in the email of the employee who no longer works there.

For Fiona Tan, CTO of Wayfair, AI agents can be applied to so many use cases that practically every business should adopt them, and the savings can be pointed to in hard dollars. (Google Cloud Blog)