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AI Will Shift Sales to 80% Selling Time by 2026

As the AI era evolves, one of the most difficult aspects of predictions is how quickly humans will be abstracted away from today’s “point of work.” Take something as simple as building a toy. The first level of abstraction is already here: humans use AI for ideation, prototyping, manufacturing, and distribution. The next level? Prompting an AI to “create a toy that launches a profitable product line.” Beyond that? A single prompt—“bring joy to children”—with AI orchestrating the entire value chain end to end. Will we reach those higher levels of abstraction? If so, when? No one knows. Applying this abstraction framework to go-to-market, we can hypothesize a similar progression: Phase I: AI Handles Non-Selling Work Sales reps still “sell,” but AI owns research, targeting, CRM updates, and prep. Selling time jumps from ~25% to ~80%. Early adopters are already here. My guess: ~5% of sales teams reach this level by the end of 2026. Also expect a reversal of the specialization trend. Instead of SDR -> AE -> CSM -> AM, we will see an increase in full-cycle AEs that manage appointment setting, customer acquisition, and customer retention/expansion. Phase II: AI Sells to Human Buyers AI begins selling directly to humans—starting with low-risk, high-volume transactions (PLG), then expanding into larger deals as trust compounds. Human sellers remain as the escalation path, especially for complex or high-stakes decisions. Phase III: AI Buys from AI AI agents buy from AI sales agents. Humans shift from execution to setting upfront strategy and validating recommendations. Phase IV: Functional Walls Blur Our functional silos—Finance, Product, Engineering, Sales, Marketing, HR—exist largely because of human limitations. Few people major in Finance and become engineers, and vice versa. These structures help coordinate human effort, but they also introduce inefficiencies. Product could benefit from insights buried in support calls. Finance could benefit from real-time signal in sales conversations. Eventually, AI removes these constraints, organizing work around end-to-end jobs-to-be-done, rather than functional department capabilites. You can already see early signals of Phase IV. At Stage 2 Capital , we’ve seen our portfolio companies like Momentum.io surface market intelligence by identifying patterns across weeks of sales conversations. Perhaps AI 1.0 is workflow optimization, and AI 2.0 is workflow reinvention. This may be a simple example. Thanks to the teams at Hard Skill Exchange and the Agentic Singularity Summit for hosting a thoughtful discussion on the future of GTM AI. I elaborate on these themes, and degine the first principles of go-to-market best practices, in The Science of Scaling. 100% of proceeds are donated to mental health. https://lnkd.in/gH9jUy5b