Aiger Data
Operating model

What changes for the organization.

When the foundations are in place and the failure modes avoided, a few shifts are worth flagging because they have direct implications for how business and operations leaders should be planning.

01 ─ THE SHAPE OF TEAMS CHANGES

Functions get flatter. The middle layer of work — the coordination, the routine judgment, the status-checking — is what agents do well. The remaining human work concentrates at the strategic top (setting intent, designing policy) and the operational edge (handling exceptions, building relationships, applying judgment to the genuinely novel).

02 ─ PERFORMANCE MANAGEMENT CHANGES

"Productivity" measured in human-hours becomes a less useful metric. The relevant questions become: what was the quality of the decisions our agents made, what did they cost, how often did they need to escalate, and how did our customers experience the result?

03 ─ THE TECHNOLOGY OPERATING MODEL CHANGES

Buying software becomes less about features and more about agent-readiness — data extensibility, API maturity, observability, the platform's posture toward operating alongside other agents from other vendors. The CIO's evaluation criteria shift; procurement's contracts shift; security's threat model shifts.

04 ─ RISK AND COMPLIANCE CHANGE

Boards and regulators are catching up quickly. Organizations that have invested in trust infrastructure will find themselves with a defensible posture. Organizations that have not will find themselves explaining, after the fact, why they could not.