Enterprise software is moving from assistance to execution. The most compelling systems fuse context, reasoning, and action into core workflows.

As agents grow more autonomous and long-running, reliability becomes a new engineering discipline, requiring better ways to build, evaluate, observe, and control them.

AI is reshaping what the data layer must provide and how it operates, requiring infrastructure that is real-time, composable, and machine-usable.

The bottleneck is shifting from training to serving intelligence efficiently at runtime. Compute optimization, model routing, and runtime systems are becoming critical.

The next frontier is embodied intelligence: models built for generalization and infrastructure that accelerates learning across data, simulation, and deployment.

As software gains agency, governance must expand from access to action, enabling deployment of autonomous systems with confidence.