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Matt McKinney, CEO of Loop, states his supply chain customers don't care about "agentic buzzwords." They are buying superior business outcomes like faster book closing or better error detection. This emphasizes that for many enterprises, AI is a means to an end, not the product itself.
Customers are hesitant to trust a black-box AI with critical operations. The winning business model is to sell a complete outcome or service, using AI internally for a massive efficiency advantage while keeping humans in the loop for quality and trust.
Enterprise buyers are drawn to the vision of full automation ("the sizzle"), but their immediate need is improving existing human workflows ("the steak"). A startup must offer both. The visionary product gets them in the door, while the practical agent-assist tool delivers immediate value and gathers necessary data for future automation.
Despite the industry's obsession with AI, product executives are primarily concerned with connecting product initiatives to revenue, margin, and profit. They are being held accountable for financial results, a significant shift from the previous era of growth-at-all-costs.
In a market where every vendor claims to be "AI-powered," differentiation comes from focusing on outcomes. AI should be messaged as a force multiplier that improves existing workflows, enhances efficiency, and provides intelligence, not as a standalone product.
SMB owners are not asking for technologies like AI by name. They are asking for outcomes and efficiency. B2B marketers should position advanced features not as 'AI' or 'video tools,' but as embedded, invisible solutions that make a marketing hour more impactful. The goal is to provide tools that a business owner can naturally use to get a return, without needing to become a technology expert.
While initial sales conversations for BPO replacement focus on 50-75% cost savings, customers discover greater value in AI's unique abilities. These include superhuman speed to close business faster, instant scalability for seasonal demand, and unprecedented observability into previously "black box" processes.
The standard for success in enterprise software sales is no longer simply implementing the system. Driven by the high stakes of AI, customers now demand proof of tangible business outcomes and value, forcing a fundamental change in sales pitches away from features and timelines to demonstrating concrete ROI.
C-suite conversations have evolved from encouraging broad AI experimentation to demanding measurable ROI. The critical mindset shift is away from fascination with specific models and toward redesigning core, enterprise-grade workflows for tangible business impact, moving from a 'playground' to 'production grade' mode.
AI companies are pivoting from simply building more powerful models to creating downstream applications. This shift is driven by the fact that enterprises, despite investing heavily in AI promises, have largely failed to see financial returns. The focus is now on customized, problem-first solutions to deliver tangible value.
A clear market shift has occurred: enterprise clients are no longer interested in AI pilots. They now demand outcome-based contracts where AI is a core pillar tied to measurable productivity gains. The conversation has moved from "Can AI help?" to "How fast can we scale it?"