According to Forbes, artificial intelligence has entered what they call the “token paradox” of 2025, where AI costs have dropped 90% from $36 to $4 per million tokens while corporate spending has surged. The shift comes from moving from simple question-answer AI to agentic workflows where AI systems autonomously pursue complex goals through multiple iterations. In healthcare, where medical practices process 43 authorization requests weekly requiring 12 staff hours, AI agents could consume tens of thousands of tokens per case but still cost less than human labor. Similarly, in accounting, with 75% of CPAs expected to retire within 15 years, agentic AI offers a solution despite higher token consumption. This paradox is driving 90% of IT executives to explore agentic workflows according to the Agentic AI Report, fundamentally changing how organizations approach automation.
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The Coming Market Realignment
What we’re witnessing is a fundamental realignment of competitive advantage in enterprise software. Companies that continue optimizing for token efficiency are essentially fighting the last war, while forward-thinking organizations are re-engineering entire business processes around continuous AI operation. The economics are staggering: at $4 per million tokens, an agent consuming 100 tokens per second costs approximately $1.50 per hour to operate. This creates a permanent structural advantage for early adopters that will be difficult for competitors to overcome without complete process redesign.
Industry Winners and Losers
The implications cascade across multiple sectors. Business process outsourcing (BPO) companies face existential threats as their labor arbitrage models become obsolete against AI agents costing pennies per hour. Healthcare administration, where prior authorization costs the system billions annually, stands to benefit enormously from automation. Insurance, financial services, and professional services firms that can rapidly adopt agentic workflows will achieve cost structures that traditional competitors cannot match. The realignment isn’t just about efficiency—it’s about redefining what’s economically possible in service delivery.
Investment and Strategic Implications
For technology investors and corporate strategists, the token paradox signals a shift in valuation metrics. Companies should be evaluated not on their current token consumption but on their ability to deploy AI agents across high-value workflows. The most valuable AI companies will be those that identify processes where autonomous agents can consume millions of tokens while generating disproportionate business value. This explains why AI spending continues climbing despite falling unit costs—organizations aren’t just buying cheaper AI, they’re purchasing entirely new capabilities that redefine their competitive positioning.
The Coming Talent Transformation
The workforce implications are equally profound. Rather than eliminating jobs, agentic AI will transform them. Professionals will shift from performing routine tasks to designing, monitoring, and optimizing AI agents. The accounting firm of the future won’t employ hundreds of junior accountants doing reconciliations but will instead employ AI specialists who design systems that autonomously handle thousands of transactions. This creates both disruption and opportunity—organizations that retrain their workforce to work with rather than against agentic systems will gain significant advantages.
New Competitive Dynamics
The most significant market impact may be the emergence of winner-take-most dynamics in industries previously resistant to technological disruption. Companies that master agentic workflows first will achieve cost structures and service levels that create nearly insurmountable competitive moats. The insurance CIO mentioned in the Forbes article who saw token usage triple while costs barely moved represents the new competitive reality. In this environment, the greatest risk isn’t overspending on AI—it’s underinvesting in the capabilities that will define market leadership for the next decade.
