How to centralize AI usage data with Fivetran’s AI connectors

Fivetran describes how it centralized fragmented AI usage and spending data from providers such as OpenAI and Anthropic to help leadership assess costs, adoption, productivity, and return on investment. Previously, finance and analytics teams relied on provider portals, CSV exports, and manual processes to map user-level consumption to business cost centers, a task that could take at least a day per reporting cycle. Using Fivetran’s AI connectors, combined with HR, employee, financial, engineering, and operational data, the company created a unified cost model and near-real-time dashboard that can analyze usage by vendor, team, user, model, and activity type. Fivetran also released Quickstart models and an AI Reporting package to help customers turn raw provider data into analysis-ready metrics covering cost, user activity, coding productivity, and per-user summaries. The company says centralized visibility supports budgeting, vendor negotiations, employee AI allowances through its internal AI wallet, and efforts to connect AI consumption with outcomes from systems such as GitHub, Jira, CRM, and support platforms, framing AI management as an ongoing business investment rather than a standalone expense.

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