A lot goes into what determines that value, such as whether the agent output is correct, whether humans must supervise or repair it, how much compute it consumes while reasoning, and whether the value of the completed work exceeds the full operational cost of generating it. In essence, for CEOs this boils down to answering a basic question: Are the AI agent capabilities we’re building and running worth the value we’re getting from them? Answering that question is becoming ever more pressing for CEOs as AI systems move from agentic coworkers to agents capable of more complex tasks like reasoning and orchestrating workflows across the enterprise. Furthermore, AI spending is expected to rise to roughly 25 percent of enterprise IT budgets within the next several years. Yet many organizations still cannot clearly explain which AI systems are generating value, what they truly cost to operate, or how those economics change as usage scales.
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