Basis, Clay, and Exa Labs use agents for onboarding, account management, and developer integrations. Their examples show what enterprise leaders can borrow.

OpenAI’s latest Enterprise Signals shows enterprise AI moving from assistance to execution at sharply different speeds. Frontier firms (those with the top 10% of AI usage) now generate 8.3× as many output tokens per active user as typical firms, up from 2.6× in January. The widening gap points to a deeper operating shift: leading firms connect agents to company context and tools, delegate more substantive work, and make successful workflows easier to repeat.

For leaders, the challenge is to turn that depth into work people can trust, measure, and improve. Leaders should also leave room for experimentation, including use cases whose value is not obvious on the first try.

Startups Basis⁠(opens in a new window), Clay⁠(opens in a new window), and Exa Labs⁠(opens in a new window) have built agents into employee onboarding, account management, and developer ecosystem growth. Their workflows differ, but the progression is instructive: teach an agent a stable process, give it persistent context as work changes, then let it carry opportunities into tested action.

Together, these examples show how teams can build agents into familiar work and improve the process over time.

Onboarding has long been cumbersome for employers and employees. At Basis, which builds AI agents for accounting firms, first-day onboarding now takes 30 minutes instead of two hours, giving HR more time for culture and support.

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