Even if AI dramatically lowers coding costs, it won't destroy established SaaS businesses. Technical expenses only account for 10-20% of revenue for major SaaS players. The other 80% is spent on marketing, events, and client service, creating an opportunity for significant margin expansion.

The ROI of AI in professional services is dramatic. A marginal 1% improvement in the utilization rate of skilled professionals—achieved through AI-powered staffing and automation—directly translates to a 1.3-1.5% increase in top-line revenue and a 1.5% increase in profit margins for large firms.

Historically, software did ~10% of the work (tracking, organizing). AI will invert this, with software actively performing 70-80% of tasks. This fundamental shift means customers will refuse to buy legacy software that doesn't do the majority of the work for them, massively expanding the total addressable market.

A new generation of AI application companies are being run with extreme leanness and efficiency. They are achieving revenue-per-employee figures between $500K and $5M, dwarfing the public software company average of ~$400K and signaling a fundamental shift in scalable operating models.

Companies are re-architecting operations around maximizing revenue per employee (RPE), driven by a push for efficiency. This metric has become the primary focus for leadership and boards, with AI seen as the key enabler, shifting focus from trends like Product-Led Growth (PLG).

In labor-intensive service industries, growth is painful as it requires proportional hiring, yielding low margins. AI breaks this cycle by making existing teams 30-40% more efficient. This allows companies to scale revenue with high incremental margins, transforming their financial profile to resemble a software company's.

AI tools aren't just making employees more efficient; they are replacing human labor. This allows software companies to move from cheap per-seat pricing to a new model based on outcomes, like charging per support ticket resolved, capturing a much larger share of the value.

Vista CEO Robert Smith classifies enterprise software's future into three paths. Companies will either become 'agentic' (creating new value with AI), 'AI-powered operators' (massively boosting efficiency), or 'fail to thrive' if they lack proprietary data and workflows.

Traditional SaaS metrics like 80%+ gross margins are misleading for AI companies. High inference costs lower margins, but if the absolute gross profit per customer is multiples higher than a SaaS equivalent, it's a superior business. The focus should shift from margin percentages to absolute gross profit dollars and multiples.