By Kimberly Tan – As AI turns labor into software, the opportunity to productize external professional services (e.g., in legal or accounting) has become a hot topic. However, we believe there is also substantial opportunity in productizing internal work within organizations. These responsibilities often fall under the umbrella term of “operations” and can range from full-time data entry and front desk roles, to routine operational tasks embedded in every other role. This work generates fewer media headlines, but it is the internal stitching that holds companies together.

These ops roles involve critical, but often repetitive and mundane tasks. Companies have historically attempted to automate these tasks by using Robotic Process Automation (RPA), but with generative AI, we believe true automation through agents is now possible. We’ve already seen early examples of agents working in production, such as Decagon’s automated customer support. And with companies like Anthropic launching capabilities like computer use to enable models to meaningfully interact with existing software, there is a clear emerging infrastructure stack for founders to build verticalized intelligent automation applications.

These examples preview a world in which AI agents are able to fulfill the original promise of RPA, turning what used to be operations headcount into intelligent automation and freeing workers to focus on more strategic work.

Operations work is sprawling and diverse, including tasks like data entry, document extraction, information transfer, system migrations, and web scraping. These tasks are essential, but they often lack the APIs or direct integrations required for traditional software to manage them efficiently. Despite the shift toward software eating the world, tons of work is still done over phone calls, spreadsheets, fax lines, and paper forms.  Read On: