Where the Value Flows: The $2T SaaS Market Redistributes, Not Evaporates
The most common mistake in the "SaaS โ as explored in the shift from SaaS to agentic service models โ is dead" narrative is treating the $2 trillion SaaS market as a single block that either survives or dies. The reality is far more nuanced: the value redistributes across horizons , and the timing differs dramatically.
Key Components
Horizon 1 (Now to 2028): TAM Grows as Revenue Model Shifts
The counterintuitive H1 insight: agents increase total software consumption while decreasing human-seat-based consumption. TAM grows. Revenue model shifts.
Horizon 2 (2027-2030): Value Shifts Decisively
Data infrastructure captures 20-25% as the decisive value magnet. Security + Observability expand their TAMs as every agent becomes a new endpoint to secure and monitor.
Horizon 3 (2030+): Three Moats Remain
Value consolidates around data gravity , protocol position , and regulatory moats .
Real-World Examples
AdobeGoogleSalesforceOpenaiAnthropic
Key Insight
The most common mistake in the "SaaS is dead" narrative is treating the $2 trillion SaaS market as a single block that either survives or dies. The reality is far more nuanced: the value redistributes across horizons , and the timing differs dramatically.
Exec Package + Claude OS Master Skill | Business Engineer Founding Plan
FourWeekMBA x Business Engineer | Updated 2026
The most common mistake in the “SaaS is dead” narrative is treating the $2 trillion SaaS market as a single block that either survives or dies. The reality is far more nuanced: the value redistributes across horizons, and the timing differs dramatically.
The Great Interface Inversion โ Animated Explainer
Horizon 1 (Now to 2028): TAM Grows as Revenue Model Shifts
The counterintuitive H1 insight: agents increase total software consumption while decreasing human-seat-based consumption. TAM grows. Revenue model shifts.
Agent Platforms (Anthropic, OpenAI, Google) capture the intent layer โ the agent becomes the new browser
Self-Cannibalizers (Salesforce, ServiceNow, Adobe) trade seat revenue for infrastructure revenue at 25-30% of value
Protocol Infrastructure โ the MCP ecosystem, connectors, gateways, agent identity and authentication
Horizon 2 (2027-2030): Value Shifts Decisively
Data infrastructure โ as explored in the economics of AI compute infrastructure โ captures 20-25% as the decisive value magnet. Security + Observability expand their TAMs as every agent becomes a new endpoint to secure and monitor. Self-cannibalizers either complete their transition or join the destruction tier.
Horizon 3 (2030+): Three Moats Remain
Value consolidates around data gravity, protocol position, and regulatory moats. The companies that own the most structured, semantically rich, agent-readable data become the equivalent of what Google was to the web.
What is Where the Value Flows: The $2T SaaS Market Redistributes, Not Evaporates?
The most common mistake in the "SaaS is dead" narrative is treating the $2 trillion SaaS market as a single block that either survives or dies. The reality is far more nuanced: the value redistributes across horizons , and the timing differs dramatically.
What are the horizon 1 (now to 2028): tam grows as revenuemodel shifts?
The counterintuitive H1 insight: agents increase total software consumption while decreasing human-seat-based consumption. TAM grows. Revenue model shifts.
What is Horizon 2 (2027-2030): Value Shifts Decisively?
Data infrastructure captures 20-25% as the decisive value magnet. Security + Observability expand their TAMs as every agent becomes a new endpoint to secure and monitor. Self-cannibalizers either complete their transition or join the destruction tier.
What is Horizon 3 (2030+): Three Moats Remain?
Value consolidates around data gravity , protocol position , and regulatory moats . The companies that own the most structured, semantically rich, agent-readable data become the equivalent of what Google was to the web.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
