Generic use cases fail to persuade leadership. To get genuine AI investment, build a custom tool that solves a specific, tangible pain point for an executive. An example is an 'AI board member' trained on past feedback to critique board decks before a meeting, making the value undeniable.

Investor Stacy Brown-Philpot advises that to win large enterprise deals, an AI startup must create a solution so compelling it beats the customer's internal team vying for the same budget. The goal is to access the core 15% budget pool, not the 1% 'play money' budget.

General Catalyst's CEO notes a change in enterprise AI GTM strategy. The old model was finding product-market fit, then repeating sales. The new model involves "forward deployed engineering" to build deep trust with an initial enterprise client, then focusing on expanding the services offered to that single client.

The massive TAM expansion for AI relies on shifting spend from labor to technology budgets. This shift won't happen because of top-down CIO mandates. It must be driven by bottom-up product pull, where the value proposition is so overwhelmingly clear that customers are compelled to adopt it.

Unlike normal sales cycles where only 5-6% of prospects are actively buying, an AI super cycle forces all enterprises to seek solutions concurrently. This creates an unprecedented, time-sensitive window to capture budget if your product is perceived as an essential AI need.

C-suites are more motivated to adopt AI for revenue-generating "front office" activities (like investment analysis) than for cost-saving "back office" automation. The direct, tangible impact on making more money overcomes the organizational inertia that often stalls efficiency-focused technology deployments.

Selling foundational AI isn't a standard IT sale. It requires a dual-threaded process targeting the CTO, who builds the agents, and the CRO, who must monetize them. The key is educating the CRO to shift from selling seats against IT budgets to capturing value from larger headcount and outsourced labor budgets.

Moonshot AI's CEO effectively sells his product by "vision casting"—framing it not as an e-commerce tool but as a partner that enables businesses to thrive. This focus on the ultimate outcome, rather than product features, resonates deeply with customers and powerfully articulates the value of a complex AI solution.

Enterprise surveys show a major shift: CEOs are taking direct control of AI initiatives from CIOs. They are increasingly willing to make substantial, long-term investments in AI—even if a recession hits or if tangible ROI isn't immediately measurable—viewing it as an existential imperative for survival and growth.