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.
Moonshot AI overcomes customer skepticism in its AI recommendations by focusing on quantifiable outcomes. Instead of explaining the technology, they demonstrate value by showing clients the direct increase in revenue from the AI's optimizations. Tangible financial results become the ultimate trust-builder.
Focusing on AI for cost savings yields incremental gains. The transformative value comes from rethinking entire workflows to drive top-line growth. This is achieved by either delivering a service much faster or by expanding a high-touch service to a vastly larger audience ("do more").
Instead of fully automating conversations and risking sounding robotic, use AI to provide real-time suggestions and prompts to a human sales rep. This scales expertise and consistency without sacrificing the human touch needed to close deals.
A critical error in AI integration is automating existing, often clunky, processes. Instead, companies should use AI as an opportunity to fundamentally rethink and redesign workflows from the ground up to achieve the desired outcome in a more efficient and customer-centric way.
Enterprises struggle to get value from AI due to a lack of iterative, data-science expertise. The winning model for AI companies isn't just selling APIs, but embedding "forward deployment" teams of engineers and scientists to co-create solutions, closing the gap between prototype and production value.
The true enterprise value of AI lies not in consuming third-party models, but in building internal capabilities to diffuse intelligence throughout the organization. This means creating proprietary "AI factories" rather than just using external tools and admiring others' success.
The most effective use of AI isn't full automation, but "hybrid intelligence." This framework ensures humans always remain central to the decision-making process, with AI serving in a complementary, supporting role to augment human intuition and strategy.
A powerful framework for the human-AI partnership: AI provides the "intellectual capacity" (data, options, research), but the salesperson must serve as the "intellectual activator." Their irreplaceable role is applying strategic judgment and critical thinking to activate the information AI provides.
To get mainstream users to adopt AI, you can't ask them to learn a new workflow. The key is to integrate AI capabilities directly into the tools and processes they already use. AI should augment their current job, not feel like a separate, new task they have to perform.
Adopt a 'more intelligent, more human' framework. For every process made more intelligent through AI automation, strategically reinvest the freed-up human capacity into higher-touch, more personalized customer activities. This creates a balanced system that enhances both efficiency and relationships.