Unlike SaaS sales with a single buyer, transformational AI products are bought by a committee. The sale requires convincing a C-level executive responsible for AI transformation and a technical expert who evaluates the infrastructure, in addition to the functional business leader.
To succeed in the AI era, SaaS companies cannot just add AI features. They must undergo a 'brutal' transformation, changing everything from their org chart and GTM strategy to their core metrics and pricing model. This is a non-negotiable, foundational shift.
Traditional SaaS development starts with a user problem. AI development inverts this by starting with what the technology makes possible. Teams must prototype to test reliability first, because execution is uncertain. The UI and user problem validation come later in the process.
To keep pace with AI development, the barrier between design and engineering must fall. Intercom made it a non-negotiable job requirement for every product designer to ship code to production. This empowers them to fix UI bugs directly and accelerates the entire development cycle.
In SaaS, value was delivered through visible UI. With AI, this is inverted. The most critical, differentiating work happens in the invisible infrastructure—complex RAG systems and custom models. The UI becomes the smaller, easier part of the product, flipping the traditional value proposition.
When a SaaS company successfully launches a new AI product, it creates a second, conflicting business. It must manage the legacy SaaS model (seats, predictable metrics) alongside the new AI model (outcomes, unpredictable metrics), creating tension in strategy, branding, and operations.
Many companies market AI products based on compelling demos that are not yet viable at scale. This 'marketing overhang' creates a dangerous gap between customer expectations and the product's actual capabilities, risking trust and reputation. True AI products must be proven in production first.
Incremental change is insufficient for the AI transition. To find the true extent of what needs to change, leaders must be willing to go 'too far.' This means dismantling established teams, processes, and roadmaps entirely, rather than iterating, to rebuild them from scratch for the new reality.