MARKET ANALYSIS

Is SaaS Dead?

Yuvin Kim

July 10, 2025

MARKET ANALYSIS

Is SaaS Dead?

Yuvin Kim

July 10, 2025

1. The Rise of AI Agents and the Crisis of Function-Centric SaaS

Since 2023, the rapid evolution of generative AI has opened a new paradigm with AI Agents — autonomous execution entities that go beyond simple language responses. AI Agents can track user states, infer intentions, and autonomously orchestrate multiple apps and services.

For instance, a user might request, “Schedule next week’s meetings based on my availability and share relevant documents with the team.” An Agent could then access Google Calendar, analyze Gmail and Slack messages, upload files to Notion, and send notifications to a team channel — all without any manual interaction. This is the power of multi-app orchestration.

This raises a crucial question: “If AI can do all this automatically, do we still need individual SaaS apps?” This is not a fringe concern — the tech world is actively debating it. The phrase “The SaaS is Dead” is no longer just rhetorical — emerging trends and data lend weight to the claim:

  • The global AI Agent market is projected to grow from $525M in 2024 to $23.6B by 2030, at a CAGR of ~45–46% (MarketsandMarkets, Superhuman).

  • Over 85% of global enterprises plan to adopt AI Agents by 2025, with reported productivity gains of 55% and cost savings of 35% (Fortune Business Insights, Business Insider).

AI Agents don’t require user-centric UI. They invoke SaaS features via APIs or function calls, interpreting them as callable components. As a result, SaaS is transitioning from a frontend product for users to a backend execution layer for Agents.

Frameworks like Zapier AI, LangChain, and AutoGPT illustrate this shift. Users delegate tasks, and Agents recompose existing SaaS features based on outcome-driven logic. Consequently, traditional SaaS faces structural threats on three fronts:

  1. The trigger of action is shifting from user → agent

  2. Click-based UX is becoming obsolete

  3. API-first redesign is becoming essential

This isn’t just technical progress — it’s an ontological shift. SaaS must redefine its purpose: from human-operated software to machine-executed infrastructure.

2. Is SaaS Dead — or Just Changing?

If AI can complete tasks independently, do we need multiple SaaS apps at all? The question strikes at the heart of SaaS’s future. And while “The SaaS is Dead” is a provocative statement, the true answer depends on how we define SaaS.

AI Agents aren’t eliminating SaaS — they’re repositioning it. Once a user-facing product, SaaS is evolving into a function node within automated workflows. This isn’t a feature update — it’s an existential pivot.

2–1. SaaS Isn’t Dying — It’s Shifting Form

According to Statista and Gartner, the global SaaS market is projected to grow from $297B in 2023 to $482B by 2028, at a CAGR of ~10.5%. That’s a slowdown from the 16–18% CAGR seen between 2015–2020, suggesting not stagnation — but structural transformation.

2–2. Agent-Friendly SaaS vs UI-Centric SaaS

AI Agents prefer SaaS products with:

  • Well-defined API endpoints

  • Predictable output structures

  • Minimal latency

  • High reliability

In contrast, UI-driven SaaS — optimized for human interaction — may fall behind. Here’s the comparison:

2–3. Zapier and Notion: Survivors by Evolution
  • Zapier (2024 revenue: $310M, 3M+ users) has launched Natural Language Automation (NLA) and Zapier AI, enabling agent-to-agent workflows like “Summarize my emails and update Notion.”

  • Notion (valuation ~$10B) integrates Notion AI to boost user productivity by over 50%, offering contextual environments for structured agent outputs.

These examples show the shift from “human-used SaaS” to “agent-invoked SaaS.”

2–4. SaaS Evolution: From Product → Platform → Protocol

Key transitions include:

  • From user interface → function calls

  • From UI design → data/API reliability

  • From apps → composable infrastructure

2–5. Final Thought: SaaS Becomes the Neural Layer of AI Ecosystems

SaaS is no longer the final touchpoint — it’s becoming the middleware that enables intelligent orchestration.

To remain relevant, SaaS must provide:

  • Trustworthy APIs

  • Structured data

  • Secure, compliant environments

  • Context-aware response layers

SaaS isn’t dying. It’s just no longer clicked — it’s called.

3. Strategic Response: From Services to Stacks

The rise of Agents demands identity-level redesign for SaaS companies. No longer just “services for people,” SaaS must become stacks that are callable, modular, and context-aware.

3–1. Build Agent-Friendly APIs

Agent compatibility requires:

  • Stable, well-documented APIs (OpenAPI/Swagger)

  • JSON-based I/O

  • Low latency and clear error handling

  • Flexible function chaining

Platforms like Slack, OpenAI Function Calling, and LangChain are setting standards. Without callable endpoints, SaaS risks irrelevance in the agent-driven world.

3–2. Beyond Built-in AI: Serve the Agents

Embedding AI in your SaaS is no longer enough. What matters more is external Agent integration:

  • Integrate with Zapier AI, Replit, LangChain

  • Expose services via callable, modular APIs

  • Example: Salesforce’s Agentforce now handles 84% of customer queries via Agent-led support (Inc.com, The Australian)

3–3. From App to Stack: Modularizing SaaS

SaaS must evolve from being a monolithic product to a function layer in the AI stack.

OpenAI’s plugin and function APIs have turned countless SaaS tools into callable infrastructure, powering a $10B+ revenue engine.

3–4. Summary: Only Agent-Callable SaaS Will Survive

Winning strategies include:

  • API-first design

  • External AI integration

  • Robust backend infrastructure for agents

Future success depends not on visibility to users, but on discoverability by Agents.

4. Conclusion: SaaS Is for Agents, Not Just Users

AI Agents are transforming how work gets done. Clicking and typing are being replaced by commands that orchestrate tasks autonomously.

Thus, some say “SaaS is dead.” But what’s truly disappearing is UI-based SaaS — not the functionality underneath. In fact, AI depends more than ever on SaaS as a structured, callable layer.

To function, an AI Agent needs:

  • Reliable APIs

  • Structured data

  • Secure and persistent execution layers

SaaS now evolves from user-facing software to backend infrastructure for intelligent systems.

4–1. B2C SaaS: UI-Based Models at Risk

B2C SaaS tools face headwinds:

  • Rising user expectations

  • Agent-based substitutes

  • Obsolescence of UI-based differentiation

Unless restructured for agent-compatibility, B2C tools risk irrelevance.

4–2. B2B SaaS: Positioned as Strategic Backends

B2B SaaS remains robust with:

  • Enterprise-grade security

  • Compliance certifications

  • Modular APIs for agent workflows

These make B2B tools ideal agent infrastructure layers.

4–3. Final Thought: SaaS Isn’t Dead — Just Different

SaaS is no longer about screen design. It’s about API design.

Future competition will hinge on:

  • Being easily callable by agents

  • Delivering accurate, timely responses

  • Embedding trust through compliance and reliability

The winners in the AI economy will not be services — they will be stacks.

5. References & Sources
5–1. Market Reports & Data
  1. Statista — SaaS Market Forecast: https://www.statista.com/statistics/510333

  2. Gartner — SaaS Trends: https://www.gartner.com/en/newsroom

  3. Fortune Business Insights — AI Adoption: https://www.fortunebusinessinsights.com

  4. Markets & Markets — AI Agent Market: https://www.marketsandmarkets.com

  5. TechJury — AI Efficiency Stats: https://techjury.net

  6. Business Insider — AI in Business: https://www.businessinsider.com

5–2. Agent Ecosystem Insights
  1. Superhuman Blog — SaaS is Dead: https://blog.superhuman.com

  2. WSJ — AI Agents & SaaS: https://www.wsj.com

  3. LangChain Docs — https://docs.langchain.com

  4. OpenAI Docs — Function Calling: https://platform.openai.com

5–3. Platform Case Studies
  1. Zapier Blog: https://zapier.com/blog

  2. Notion AI: https://notion.so/blog

  3. Salesforce Agentforce: https://www.theaustralian.com.au

  4. Plivo Blog — AI SaaS: https://www.plivo.com/blog

1. The Rise of AI Agents and the Crisis of Function-Centric SaaS

Since 2023, the rapid evolution of generative AI has opened a new paradigm with AI Agents — autonomous execution entities that go beyond simple language responses. AI Agents can track user states, infer intentions, and autonomously orchestrate multiple apps and services.

For instance, a user might request, “Schedule next week’s meetings based on my availability and share relevant documents with the team.” An Agent could then access Google Calendar, analyze Gmail and Slack messages, upload files to Notion, and send notifications to a team channel — all without any manual interaction. This is the power of multi-app orchestration.

This raises a crucial question: “If AI can do all this automatically, do we still need individual SaaS apps?” This is not a fringe concern — the tech world is actively debating it. The phrase “The SaaS is Dead” is no longer just rhetorical — emerging trends and data lend weight to the claim:

  • The global AI Agent market is projected to grow from $525M in 2024 to $23.6B by 2030, at a CAGR of ~45–46% (MarketsandMarkets, Superhuman).

  • Over 85% of global enterprises plan to adopt AI Agents by 2025, with reported productivity gains of 55% and cost savings of 35% (Fortune Business Insights, Business Insider).

AI Agents don’t require user-centric UI. They invoke SaaS features via APIs or function calls, interpreting them as callable components. As a result, SaaS is transitioning from a frontend product for users to a backend execution layer for Agents.

Frameworks like Zapier AI, LangChain, and AutoGPT illustrate this shift. Users delegate tasks, and Agents recompose existing SaaS features based on outcome-driven logic. Consequently, traditional SaaS faces structural threats on three fronts:

  1. The trigger of action is shifting from user → agent

  2. Click-based UX is becoming obsolete

  3. API-first redesign is becoming essential

This isn’t just technical progress — it’s an ontological shift. SaaS must redefine its purpose: from human-operated software to machine-executed infrastructure.

2. Is SaaS Dead — or Just Changing?

If AI can complete tasks independently, do we need multiple SaaS apps at all? The question strikes at the heart of SaaS’s future. And while “The SaaS is Dead” is a provocative statement, the true answer depends on how we define SaaS.

AI Agents aren’t eliminating SaaS — they’re repositioning it. Once a user-facing product, SaaS is evolving into a function node within automated workflows. This isn’t a feature update — it’s an existential pivot.

2–1. SaaS Isn’t Dying — It’s Shifting Form

According to Statista and Gartner, the global SaaS market is projected to grow from $297B in 2023 to $482B by 2028, at a CAGR of ~10.5%. That’s a slowdown from the 16–18% CAGR seen between 2015–2020, suggesting not stagnation — but structural transformation.

2–2. Agent-Friendly SaaS vs UI-Centric SaaS

AI Agents prefer SaaS products with:

  • Well-defined API endpoints

  • Predictable output structures

  • Minimal latency

  • High reliability

In contrast, UI-driven SaaS — optimized for human interaction — may fall behind. Here’s the comparison:

2–3. Zapier and Notion: Survivors by Evolution
  • Zapier (2024 revenue: $310M, 3M+ users) has launched Natural Language Automation (NLA) and Zapier AI, enabling agent-to-agent workflows like “Summarize my emails and update Notion.”

  • Notion (valuation ~$10B) integrates Notion AI to boost user productivity by over 50%, offering contextual environments for structured agent outputs.

These examples show the shift from “human-used SaaS” to “agent-invoked SaaS.”

2–4. SaaS Evolution: From Product → Platform → Protocol

Key transitions include:

  • From user interface → function calls

  • From UI design → data/API reliability

  • From apps → composable infrastructure

2–5. Final Thought: SaaS Becomes the Neural Layer of AI Ecosystems

SaaS is no longer the final touchpoint — it’s becoming the middleware that enables intelligent orchestration.

To remain relevant, SaaS must provide:

  • Trustworthy APIs

  • Structured data

  • Secure, compliant environments

  • Context-aware response layers

SaaS isn’t dying. It’s just no longer clicked — it’s called.

3. Strategic Response: From Services to Stacks

The rise of Agents demands identity-level redesign for SaaS companies. No longer just “services for people,” SaaS must become stacks that are callable, modular, and context-aware.

3–1. Build Agent-Friendly APIs

Agent compatibility requires:

  • Stable, well-documented APIs (OpenAPI/Swagger)

  • JSON-based I/O

  • Low latency and clear error handling

  • Flexible function chaining

Platforms like Slack, OpenAI Function Calling, and LangChain are setting standards. Without callable endpoints, SaaS risks irrelevance in the agent-driven world.

3–2. Beyond Built-in AI: Serve the Agents

Embedding AI in your SaaS is no longer enough. What matters more is external Agent integration:

  • Integrate with Zapier AI, Replit, LangChain

  • Expose services via callable, modular APIs

  • Example: Salesforce’s Agentforce now handles 84% of customer queries via Agent-led support (Inc.com, The Australian)

3–3. From App to Stack: Modularizing SaaS

SaaS must evolve from being a monolithic product to a function layer in the AI stack.

OpenAI’s plugin and function APIs have turned countless SaaS tools into callable infrastructure, powering a $10B+ revenue engine.

3–4. Summary: Only Agent-Callable SaaS Will Survive

Winning strategies include:

  • API-first design

  • External AI integration

  • Robust backend infrastructure for agents

Future success depends not on visibility to users, but on discoverability by Agents.

4. Conclusion: SaaS Is for Agents, Not Just Users

AI Agents are transforming how work gets done. Clicking and typing are being replaced by commands that orchestrate tasks autonomously.

Thus, some say “SaaS is dead.” But what’s truly disappearing is UI-based SaaS — not the functionality underneath. In fact, AI depends more than ever on SaaS as a structured, callable layer.

To function, an AI Agent needs:

  • Reliable APIs

  • Structured data

  • Secure and persistent execution layers

SaaS now evolves from user-facing software to backend infrastructure for intelligent systems.

4–1. B2C SaaS: UI-Based Models at Risk

B2C SaaS tools face headwinds:

  • Rising user expectations

  • Agent-based substitutes

  • Obsolescence of UI-based differentiation

Unless restructured for agent-compatibility, B2C tools risk irrelevance.

4–2. B2B SaaS: Positioned as Strategic Backends

B2B SaaS remains robust with:

  • Enterprise-grade security

  • Compliance certifications

  • Modular APIs for agent workflows

These make B2B tools ideal agent infrastructure layers.

4–3. Final Thought: SaaS Isn’t Dead — Just Different

SaaS is no longer about screen design. It’s about API design.

Future competition will hinge on:

  • Being easily callable by agents

  • Delivering accurate, timely responses

  • Embedding trust through compliance and reliability

The winners in the AI economy will not be services — they will be stacks.

5. References & Sources
5–1. Market Reports & Data
  1. Statista — SaaS Market Forecast: https://www.statista.com/statistics/510333

  2. Gartner — SaaS Trends: https://www.gartner.com/en/newsroom

  3. Fortune Business Insights — AI Adoption: https://www.fortunebusinessinsights.com

  4. Markets & Markets — AI Agent Market: https://www.marketsandmarkets.com

  5. TechJury — AI Efficiency Stats: https://techjury.net

  6. Business Insider — AI in Business: https://www.businessinsider.com

5–2. Agent Ecosystem Insights
  1. Superhuman Blog — SaaS is Dead: https://blog.superhuman.com

  2. WSJ — AI Agents & SaaS: https://www.wsj.com

  3. LangChain Docs — https://docs.langchain.com

  4. OpenAI Docs — Function Calling: https://platform.openai.com

5–3. Platform Case Studies
  1. Zapier Blog: https://zapier.com/blog

  2. Notion AI: https://notion.so/blog

  3. Salesforce Agentforce: https://www.theaustralian.com.au

  4. Plivo Blog — AI SaaS: https://www.plivo.com/blog

1. The Rise of AI Agents and the Crisis of Function-Centric SaaS

Since 2023, the rapid evolution of generative AI has opened a new paradigm with AI Agents — autonomous execution entities that go beyond simple language responses. AI Agents can track user states, infer intentions, and autonomously orchestrate multiple apps and services.

For instance, a user might request, “Schedule next week’s meetings based on my availability and share relevant documents with the team.” An Agent could then access Google Calendar, analyze Gmail and Slack messages, upload files to Notion, and send notifications to a team channel — all without any manual interaction. This is the power of multi-app orchestration.

This raises a crucial question: “If AI can do all this automatically, do we still need individual SaaS apps?” This is not a fringe concern — the tech world is actively debating it. The phrase “The SaaS is Dead” is no longer just rhetorical — emerging trends and data lend weight to the claim:

  • The global AI Agent market is projected to grow from $525M in 2024 to $23.6B by 2030, at a CAGR of ~45–46% (MarketsandMarkets, Superhuman).

  • Over 85% of global enterprises plan to adopt AI Agents by 2025, with reported productivity gains of 55% and cost savings of 35% (Fortune Business Insights, Business Insider).

AI Agents don’t require user-centric UI. They invoke SaaS features via APIs or function calls, interpreting them as callable components. As a result, SaaS is transitioning from a frontend product for users to a backend execution layer for Agents.

Frameworks like Zapier AI, LangChain, and AutoGPT illustrate this shift. Users delegate tasks, and Agents recompose existing SaaS features based on outcome-driven logic. Consequently, traditional SaaS faces structural threats on three fronts:

  1. The trigger of action is shifting from user → agent

  2. Click-based UX is becoming obsolete

  3. API-first redesign is becoming essential

This isn’t just technical progress — it’s an ontological shift. SaaS must redefine its purpose: from human-operated software to machine-executed infrastructure.

2. Is SaaS Dead — or Just Changing?

If AI can complete tasks independently, do we need multiple SaaS apps at all? The question strikes at the heart of SaaS’s future. And while “The SaaS is Dead” is a provocative statement, the true answer depends on how we define SaaS.

AI Agents aren’t eliminating SaaS — they’re repositioning it. Once a user-facing product, SaaS is evolving into a function node within automated workflows. This isn’t a feature update — it’s an existential pivot.

2–1. SaaS Isn’t Dying — It’s Shifting Form

According to Statista and Gartner, the global SaaS market is projected to grow from $297B in 2023 to $482B by 2028, at a CAGR of ~10.5%. That’s a slowdown from the 16–18% CAGR seen between 2015–2020, suggesting not stagnation — but structural transformation.

2–2. Agent-Friendly SaaS vs UI-Centric SaaS

AI Agents prefer SaaS products with:

  • Well-defined API endpoints

  • Predictable output structures

  • Minimal latency

  • High reliability

In contrast, UI-driven SaaS — optimized for human interaction — may fall behind. Here’s the comparison:

2–3. Zapier and Notion: Survivors by Evolution
  • Zapier (2024 revenue: $310M, 3M+ users) has launched Natural Language Automation (NLA) and Zapier AI, enabling agent-to-agent workflows like “Summarize my emails and update Notion.”

  • Notion (valuation ~$10B) integrates Notion AI to boost user productivity by over 50%, offering contextual environments for structured agent outputs.

These examples show the shift from “human-used SaaS” to “agent-invoked SaaS.”

2–4. SaaS Evolution: From Product → Platform → Protocol

Key transitions include:

  • From user interface → function calls

  • From UI design → data/API reliability

  • From apps → composable infrastructure

2–5. Final Thought: SaaS Becomes the Neural Layer of AI Ecosystems

SaaS is no longer the final touchpoint — it’s becoming the middleware that enables intelligent orchestration.

To remain relevant, SaaS must provide:

  • Trustworthy APIs

  • Structured data

  • Secure, compliant environments

  • Context-aware response layers

SaaS isn’t dying. It’s just no longer clicked — it’s called.

3. Strategic Response: From Services to Stacks

The rise of Agents demands identity-level redesign for SaaS companies. No longer just “services for people,” SaaS must become stacks that are callable, modular, and context-aware.

3–1. Build Agent-Friendly APIs

Agent compatibility requires:

  • Stable, well-documented APIs (OpenAPI/Swagger)

  • JSON-based I/O

  • Low latency and clear error handling

  • Flexible function chaining

Platforms like Slack, OpenAI Function Calling, and LangChain are setting standards. Without callable endpoints, SaaS risks irrelevance in the agent-driven world.

3–2. Beyond Built-in AI: Serve the Agents

Embedding AI in your SaaS is no longer enough. What matters more is external Agent integration:

  • Integrate with Zapier AI, Replit, LangChain

  • Expose services via callable, modular APIs

  • Example: Salesforce’s Agentforce now handles 84% of customer queries via Agent-led support (Inc.com, The Australian)

3–3. From App to Stack: Modularizing SaaS

SaaS must evolve from being a monolithic product to a function layer in the AI stack.

OpenAI’s plugin and function APIs have turned countless SaaS tools into callable infrastructure, powering a $10B+ revenue engine.

3–4. Summary: Only Agent-Callable SaaS Will Survive

Winning strategies include:

  • API-first design

  • External AI integration

  • Robust backend infrastructure for agents

Future success depends not on visibility to users, but on discoverability by Agents.

4. Conclusion: SaaS Is for Agents, Not Just Users

AI Agents are transforming how work gets done. Clicking and typing are being replaced by commands that orchestrate tasks autonomously.

Thus, some say “SaaS is dead.” But what’s truly disappearing is UI-based SaaS — not the functionality underneath. In fact, AI depends more than ever on SaaS as a structured, callable layer.

To function, an AI Agent needs:

  • Reliable APIs

  • Structured data

  • Secure and persistent execution layers

SaaS now evolves from user-facing software to backend infrastructure for intelligent systems.

4–1. B2C SaaS: UI-Based Models at Risk

B2C SaaS tools face headwinds:

  • Rising user expectations

  • Agent-based substitutes

  • Obsolescence of UI-based differentiation

Unless restructured for agent-compatibility, B2C tools risk irrelevance.

4–2. B2B SaaS: Positioned as Strategic Backends

B2B SaaS remains robust with:

  • Enterprise-grade security

  • Compliance certifications

  • Modular APIs for agent workflows

These make B2B tools ideal agent infrastructure layers.

4–3. Final Thought: SaaS Isn’t Dead — Just Different

SaaS is no longer about screen design. It’s about API design.

Future competition will hinge on:

  • Being easily callable by agents

  • Delivering accurate, timely responses

  • Embedding trust through compliance and reliability

The winners in the AI economy will not be services — they will be stacks.

5. References & Sources
5–1. Market Reports & Data
  1. Statista — SaaS Market Forecast: https://www.statista.com/statistics/510333

  2. Gartner — SaaS Trends: https://www.gartner.com/en/newsroom

  3. Fortune Business Insights — AI Adoption: https://www.fortunebusinessinsights.com

  4. Markets & Markets — AI Agent Market: https://www.marketsandmarkets.com

  5. TechJury — AI Efficiency Stats: https://techjury.net

  6. Business Insider — AI in Business: https://www.businessinsider.com

5–2. Agent Ecosystem Insights
  1. Superhuman Blog — SaaS is Dead: https://blog.superhuman.com

  2. WSJ — AI Agents & SaaS: https://www.wsj.com

  3. LangChain Docs — https://docs.langchain.com

  4. OpenAI Docs — Function Calling: https://platform.openai.com

5–3. Platform Case Studies
  1. Zapier Blog: https://zapier.com/blog

  2. Notion AI: https://notion.so/blog

  3. Salesforce Agentforce: https://www.theaustralian.com.au

  4. Plivo Blog — AI SaaS: https://www.plivo.com/blog

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The form you've been searching for?

Walla, Obviously.

Paprika Data Lab Inc.

557, Yeoksam-ro, Gangnam-gu, Seoul

The form you've been searching for?

Walla, Obviously.

Paprika Data Lab Inc.

557, Yeoksam-ro, Gangnam-gu, Seoul

The form you've been searching for?

Walla, Obviously.

Paprika Data Lab Inc.

557, Yeoksam-ro, Gangnam-gu, Seoul