Initial AI market skepticism was based on a SaaS model of selling limited-value subscriptions ('seats'). The new reality is a utility model based on consumption ('tokens'). In an agentic era, a single user can drive thousands of dollars in token usage, creating a virtually uncapped revenue stream that justifies massive infrastructure investment.

Developers are shifting from using single AI agents to running and 'babysitting' five to ten agents at once. This new multi-agent workflow creates an enormous and insatiable appetite for tokens that are cost-effective rather than state-of-the-art, validating the market for efficient models.

While frontier labs initially explored diverse applications like image generation and chatbots, the market has matured. The most significant revenue and competitive focus is now squarely on coding tokens and building co-workers and agents for enterprise software development, rendering other applications secondary.

Kavak avoids measuring AI adoption by token consumption. Instead, they use a three-tier framework to evaluate token quality. Tier 3 (most valuable) are tokens with direct, measurable ROI, like those in sales agents. This brings financial discipline and focuses investment on high-impact AI applications, rather than unmonitored usage.

Investors mistakenly assume all AI tokens have equal market potential. The total addressable market for tokens varies wildly by industry. Society's capacity to consume legal services ('law tokens') is far more limited than for healthcare services, impacting ultimate value creation.

While AI agents will be used personally, their high token costs make the return on investment far greater in enterprise settings. An agent's ability to generate output that directly impacts GDP means business use cases will receive development priority over consumer or personal automation.

The AI market has cleared its first ROI hurdle: model revenue has justified massive infrastructure investment. Now it faces a second, harder test. Enterprises spending billions on AI tokens must demonstrate tangible financial benefits, like higher margins or revenue, to sustain the flywheel.

As companies spend billions on tokens, they will demand justification, similar to how law firms use the billable hour. Vertical AI startups can win by demonstrating the specific ROI of every token used for a business task, answering the question: 'Where's my ROI?'

The hedge fund Citadel Securities observes that the AI market is splitting. After initial enthusiasm, companies are now facing the reality of high token costs and compute constraints, causing a shift away from expensive frontier models toward simpler, more cost-effective AI that offers clearer ROI.