Companies seeing real returns on agents (www.wsj.com)

Although only a handful of companies have widely deployed autonomous AI agents, several early adopters report real, measurable payoffs—suggesting that agent-based workflows can already deliver ROI even as overall corporate AI spending climbs. That gap between headline costs and demonstrable value explains the tension in industry strategies: some firms are prudently waiting for agents and tooling to mature, while others are moving fast to capture potential long-term advantages from being first movers. For the AI/ML community this is a practical inflection point. The positive returns from pioneers validate investments in agent orchestration, model integration, evaluation pipelines, cost controls and guardrails, but they also underscore that success hinges on execution: selecting the right tasks for automation, instrumenting business metrics, and managing inference/infra costs. The near-term landscape will likely include a mix of vanguard, fast-follower and cautious adopters—each approach defensible—so researchers and engineers should prioritize robust evaluation frameworks, reproducible deployment patterns and safety tooling that enable scalable, sustainable agent deployments.