For years, the ADM debate has been framed as a productivity story: automation would reduce effort, AI would help developers code faster, and providers would deliver more with fewer resources. This is true, but incomplete.
The larger shift is that applications are becoming active participants in their own management. Embedded AI agents can detect anomalies, resolve incidents, optimize workflows, generate code, configure processes and recommend business actions with limited human intervention.
That shift challenges one of ADM's oldest assumptions: applications are maintained by people, demand is measured through tickets and effort, and value is linked to the resources required to keep systems running. If applications increasingly manage themselves, that logic starts to break down.
For CIOs and sourcing executives, the issue is immediate. ADM contracts signed today may still be active in 2030 – but by 2030, we will likely be living in a world of self-healing operations, AI-generated development, autonomous testing and embedded agents. The risk is not simply cost. It is structural misalignment with how application services are delivered. An ADM agreement can be contractually alive and commercially obsolete.
The question is whether today's ADM model can support tomorrow's autonomous enterprise.
Traditional ADM contracts were built for human-centric delivery. Pricing linked to full-time equivalents, ticket volumes or predefined service activities made sense when human labor was the primary driver of cost and value.
AI weakens that proxy. As routine support, testing, configuration, documentation and development tasks are executed by agents, effort becomes a less reliable measure of value. Resource consumption becomes harder to justify when value comes from prevention, automation maturity, continuity and speed of change.
This is not a one-sided customer argument. Providers will still invest in platforms, orchestration, governance, monitoring, compliance, security and specialist talent. They need a model that rewards innovation and value creation. Organizations need one that reflects how work is performed as autonomy increases.
That is where outcome-oriented and autonomy-aware pricing become central. ISG's Autonomy-Level Pricing framework links price to execution maturity, human oversight, risk ownership and embedded governance. It asks how work is delivered, how much autonomy is used, what controls applied and where accountability sits. In the ADM market of 2030, autonomy will become a commercial variable.
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