​Why The ‘Super Agent’ Strategy Is Failing In The Enterprise—And What Actually Works

Innovation​Why The ‘Super Agent’ Strategy Is Failing In The Enterprise—And What Actually WorksByPraveen Satyanarayana,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)Jun 11, 2026, 08:00am EDTPraveen Satyanarayana, data and AI leader at Tredence, advancing domain-specific agentic systems for enterprise decision intelligence. gettyEnterprise ambition has shifted from AI that talks to AI that acts, but the reality has been sobering. MIT's Project NANDA found that despite as much as $40 billion in enterprise GenAI spending, 95% of organizations reported no measurable return, and only 5% of pilots reached production.Those numbers track with what I see at Tredence. Few pilots made production. The rest died because organizations tried to solve too many problems with one generalist tool instead of committing to narrow, high-value domain-specific workflows. Postmortems point to a consistent strategic error: the super-agent fallacy, or the belief that one general-purpose agent can span every department, interpret every definition, touch every system and still remain reliable. The real reason super agents fail is not model weakness. It is that enterprises are federated political systems. AI breaks when ownership of meaning, risk and action is centralized more aggressively than the organization itself.I call this the principle of semantic jurisdiction: Each business function owns the meaning of its terms, the data contracts that govern those terms and the escalation rules that apply when those terms drive a decision. Sales owns what "pipeline" means. Finance owns "recognized revenue." Risk owns "exposure." An agent that flattens those distinctions is not helpful. It is breaking the operating model.Consider a composite banking scenario: A single AI assistant is built to serve retail lending, wealth...