Yapay zeka tabanlı şirketler iş akışlarını nasıl işletme kapasitesine dönüştürüyor?

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. Basis: Make onboarding teachable with agents 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.

On day one, employees receive immediate access to Codex and a company-specific onboarding skill (a reusable set of instructions and resources for a specific workflow). Codex welcomes them, introduces key company concepts, and uses their computer to complete integration setup in the background. When recurring questions or exceptions appear, HR can update the skill before the next cohort. Basis demonstrated the onboarding process once, then turned it into a reusable skill with a clear trigger, known steps, access to the right tools, and a clear definition of “done.” The process no longer depends on one person’s availability, yet the team can step in for exceptions or complex questions. Onboarding is now more consistent, repeatable, and easier to improve, and new employees gain an immediate model for working with AI.