Contrary to fears of job displacement, AI agents are voracious data consumers needing far more context than humans. Salesforce's CDO finds this dramatically increases the workload and hiring needs for data teams, as they must produce a much higher volume of trusted, agent-ready data to fuel the new automated workforce.

Customers now expect DaaS vendors to provide "agentic AI" that automates and orchestrates the entire workflow—from data integration to delivering actionable intelligence. The vendor's responsibility has shifted from merely delivering raw data to owning the execution of a business outcome, where swift integration is synonymous with retention.

Aaron Levie predicts a new job will be created for technical operators who implement AI agents within enterprise teams. These individuals will redesign business workflows around agents, manage their performance, and handle the necessary change management.

The need to power AI agents has created extreme urgency for enterprises to get their data in order. The focus is no longer just storing data, but breaking down silos, ensuring quality, and establishing strong governance so automated systems can use the information effectively and reliably.

Companies will need a new IT role, the "Master of Bots" or "Chief Agent Officer," to manage, deploy, and secure AI agents. This role is a modern-day sysadmin responsible for the internal bot ecosystem and for helping non-technical employees leverage them.

Managing numerous AI agents is like managing a team of people, creating a single point of failure. This necessitates a new dedicated role, a "Chief Agent Officer," with a blend of technical and marketing skills to oversee operations, prevent system failure, and ensure continuity.

The data engineer's focus is shifting from building data platforms to curating the semantic context layer that AI agents need. Their strategic value is no longer just in moving data, but in structuring and securing it so internal AI tools can provide trustworthy answers while respecting data privacy.

The competition between data platforms and model companies is not about providing a better tool. It is a battle to define the future enterprise operating model, where core processes are executed by a collaboration of humans and AI agents, fundamentally changing roles and workflows.

Companies will move beyond simply giving employees AI tools by building organizational infrastructure to support agent-driven work. This will create entirely new job families focused on coordination, evaluation, and strategy, such as "Agent Ops Engineers," "Context Librarians," and "Experiment Portfolio Managers."