Why AI Agents Are the New SaaS (and How to Ride the Wave)

AI agents are emerging as a transformative force in tech, much like SaaS did in the past (Read: Why software is eating the world by Marc Andreesen). SaaS revolutionized software delivery by offering applications over the internet on a subscription basis, making powerful tools accessible over the web without installation or maintenance.

Now, AI wrappers and Agents are taking this a step further by encapsulating AI models into user-friendly interfaces, enabling even non-technical users to leverage AI capabilities. This shift is highlighted by Satya Nadella's bold claim that "SaaS is dead", pointing to AI agents automating tasks across systems, as discussed in a recent podcast.

Why AI Agnts Are the New SaaS

AI Agents parallel SaaS by democratizing access to advanced technologies. Just as SaaS lowered barriers with its subscription model, AI Agents make AI accessible by abstracting complex model interactions, allowing users to build applications without deep technical expertise.

For instance, platforms like Okara AI enable users to create and launch custom AI agents in 60 seconds, mirroring how SaaS platforms once simplified software use. This trend is fueled by the availability of AI APIs from companies like OpenAI and Google, driving innovation similar to the SaaS boom.

Read: Which LLM is Best for Your AI App?

How to Capitalize on This Trend

Businesses can ride this wave by building their own AI agents, integrating them into existing products, or developing platforms for others. Okara AI stands out, offering a no-code solution where users can define an AI agent's purpose, choose models like OpenAI or Claude, and customize behavior, all without coding.

Analysing the "SaaS is Dead" Claim

Why AI agents are becoming the new SaaS, how businesses can leverage this trend, and the challenges they face, let's talk about each of these by taking examples from recent news and anecdotes.

Background on SaaS

SaaS transformed the software industry by delivering applications over the internet on a subscription basis, eliminating the need for installation and maintenance. This model democratized access to enterprise-grade software, enabling small businesses and individuals to use tools previously reserved for large organizations.

Satya Nadella, CEO of Microsoft, recently declared in a BG2 podcast that "SaaS is dead," emphasizing that AI agents are automating and orchestrating tasks across systems, replacing traditional CRUD (Create, Read, Update, Delete) operations. This statement underscores a shift toward AI-driven solutions. Microsoft's Copilot Studio, with 70,000+ customers worldwide as of Q2 2025, exemplifies this trend, highlighting the growing adoption of AI agents.

Defining AI Agents / AI Wrappers

AI agents are lightweight applications or software components that encapsulate one or more AI models, providing a unified interface for interaction. They simplify integration by abstracting the complexity of direct AI model interactions, making AI accessible to developers and non-technical users.

For instance, an AI wrapper might use OpenAI’s GPT-4 for natural language processing, offering a user-friendly interface for tasks like generating marketing copy or analyzing emails.

These agents often include additional functionalities like error handling, logging, and performance optimization, enhancing usability. They act as a bridge between complex AI models and applications, enabling users to leverage AI without needing deep expertise, much like SaaS platforms simplified software access.

Parallels with SaaS

The similarities between SaaS and AI agents are evident. Both models address accessibility and simplicity in technology adoption. SaaS shifted the industry from a capital expenditure (CapEx) model to an operational expenditure (OpEx) model, lowering barriers with subscription pricing. Similarly, AI agents are shifting the AI landscape, making it possible for small businesses and individuals to create and monetize AI-driven applications without significant resources.

The adoption of AI APIs from companies like OpenAI, Google, and others fuels this trend, providing the backbone for AI agents. This mirrors the SaaS boom, where cloud infrastructure enabled widespread software delivery. An unexpected detail is the speed of adoption: platforms like Okara allow users to launch AI agents in 60 seconds, a level of immediacy that surpasses early SaaS offerings.

Strategies for Leveraging AI Agents

Businesses and entrepreneurs can capitalize on this trend through several strategies:

• Building Custom AI Agents: Platforms like Okara.ai offer no-code solutions, enabling users to define an AI agent’s purpose, choose from models like OpenAI, Claude, DeepSeek, or Tulu, and customize behavior. Users can launch for free or monetize with fixed monthly pricing, making it accessible for startups and individuals.
• Integration into Existing Products: Businesses can enhance existing products with AI capabilities using agents, such as adding AI-powered chatbots to customer support systems or analytics tools to data platforms. This can add value and differentiate offerings in competitive markets.
• Developing AI agents Platforms: For those with technical expertise, creating platforms that enable others to build AI agents can be lucrative.
• Investing in AI Talent and Infrastructure: As AI agents grow, there’s a need for talent to develop and maintain them. Investing in AI education and building proprietary models or securing partnerships with AI providers ensures sustainability.

Challenges

Despite their potential, AI agents face challenges:

• Differentiation: Many agents rely on the same underlying models, making it hard to stand out. Businesses must focus on unique user experiences, additional features, or specialized knowledge.
• Sustainability: Reliance on third-party models poses risks, such as pricing changes or API availability. Strategies like developing proprietary models or long-term partnerships are crucial.
• Ethical and Legal Considerations: AI agents must address data privacy, bias, and compliance with regulations, especially given the sensitivity of AI applications in areas like healthcare or finance.

Market Trends and Examples

The market for AI agents is booming, with examples like PDF.ai and Chatbase demonstrating success by solving specific problems. The shift from per-user/seat licensing to consumption-based models, like OpenAI services billed on tokens, reflects broader industry changes as well.

Conclusion