Here’s what’s on our plate today:

• 🤖 Agents vs SaaS—who owns your workflow next?

• 📰 Arts groups push back on AI training of Australian content.

• ⚖️ xAI’s legal chief steps down after a whirlwind year.

• 📺 Google TV’s ad puzzle: more screens, murky revenue.

Let’s dive in. No floaties needed…

The Laboratory

AI agents vs. SaaS: The business model showdown

Artificial Intelligence is the biggest platform shift the world has seen in decades. And the race for dominance in this new arena is heating up. The race set off by the release of ChatGPT to the public has further intensified with OpenAI launching its new GPT-5 model. Between the early GPT models in 2018 and today’s GPT-5, perceptions of AI have shifted drastically.. Whether or not it, and to what extent, people understand the future implications of AI is open to debate.

But one thing is certain: The rapid leaps in generative AI that have made AI agents possible now have people in tech circles wondering if this transformative technology will spell the end of traditional Software as-a-Service (SaaS) as a business model.

While some have already made up their mind, Dave Park, co-founder and CEO of Narada AI, told TechCrunch that “SaaS is going away.” And that he believed the future would be just databases and AI agents that would get the job done. Meanwhile, others view AI as a transitional force that will not lead to the extinction of SaaS but will lead to transformation, adaptation, and eventual coexistence.

Before delving deeper, it helps to define software as a service (SaaS) and why AI agents threaten its current form.

What is SaaS?

In simple terms, SaaS is a cloud-based software delivery model.

Software as a service (SaaS) lets organizations access applications over the internet. Vendors host, update, and secure the software, and customers pay subscriptions instead of maintaining local infrastructure. The model is great for enterprises as it reduces the cost of updating the local computer hardware capable of running applications locally. Additionally, the cost of updating and maintaining the application is also drastically reduced.

For SaaS providers, it allows them to serve the same application to multiple customers, optimizing resources and reducing costs.

Some of the most common uses of SaaS applications are business management and operations, collaboration and communication, and data analytics and business intelligence. However, with AI agents bursting onto the scene, the business model that SaaS platforms like Adobe, Salesforce, and NetSuite are feeling the heat.

The threat posed by AI agents

AI agents are capable of carrying out complex tasks using their virtual machines. AI agents are backed by reasoning and can perform actions based on instructions provided by the end-user, which allows them to outperform SaaS as a model for workflow tools by improving productivity gains and allowing easier implementation of structural changes in software.

Since productivity gains are one of the major factors that drive growth, enterprises are transitioning towards agentic AI as a replacement for SaaS models. However, early experiments have not always been smooth.

Klarna, a financial technology company, replaced Salesforce with AI. The company later reversed course and rehired human agents through a remote, on-demand model. Similar moves are expected from other companies as better AI models are launched.

Productivity gains through AI may allow companies to cut their workforce and streamline workflows, potentially eliminating the need for entire software suites, further threatening the SaaS business model.

The impact of AI is also being felt in how startups approach profitability and where they focus their efforts.

Startups are pivoting to AI faster than SaaS

According to a report published by TechCrunch, payment giant Stripe revealed that it was witnessing an AI boom with artificial intelligence startups growing more rapidly than traditional SaaS companies.

According to Stripe, the top 100 AI companies by revenue were able to achieve an annualized revenue of $5 million in 24 months, compared to the 37 months in 2018,  taken by SaaS companies. The data from Stripe also pointed to the rapid growth of AI-powered coding assistant Cursor, which exceeded $100 million in revenue, Lovable hitting $17 million in ARR in just 3 months, and Bolt achieving $20 million in ARR in two months, as examples of this AI boom.

And while businesses look to improve productivity, and startups shift focus to AI, investors are also betting on AI rather than SaaS at the moment.

Investors bet on AI

Investors are betting on GPUs that power AI rather than CPUs. The stunning rise of Nvidia to become the first publicly traded company valued at $4 trillion underscores its massive importance to the AI chipmaker's stock market.

Investors are favoring GPUs over CPUs as AI demand accelerates. Dell’Oro Group forecasts AI data-center spending could grow at about a 24% CAGR through 2028.

Baron Fung, senior research director at Dell’Oro Group, said, ‘AI has the potential to generate more than $1 trillion in AI-related infrastructure spending in cloud and enterprise data centers over the next five years.’

However, not everyone believes that AI agents will replace SaaS as a business model. In an interview with Fortune, Salesforce CEO Marc Benioff agreed with the productivity gains brought in by agents. However, he also pointed to the shortcomings of AI, stating humans will have to be kept in the loop in workflows to ensure accuracy.

What will it be: Replacement, coexistence, or both?

While SaaS is a business model that is still doing relatively well and continues to be a dominant force in the software industry, no one denies that the AI wave will impact its revenue.

SaaS platforms are increasingly incorporating AI and machine learning to offer more personalized and efficient solutions to businesses. There is also a shift towards value-based software delivery rather than the traditional per-seat revenue model. However, whether this shift will be enough or not, only time will tell.

In the meantime, one needs to remember that when the iPhone was launched in 2007, it did not instantly lead to the collapse of Research in Motion (RIM), the company that made the BlackBerry handsets. Even in 2011, RIM was alive and kicking.

AI agents are relatively new, and their true impact is yet to be felt. And while SaaS platforms may work on integrating AI in their systems to offer more value to their customers. In the long run, if AI agents manage most workflows and organizations reduce SaaS seats, buyers may be less willing to pay for large, bundled software suites. However, on the flip side, the iPhone did not replace the traditional PC and paved the way for a more integrated world.

Whatever the case, for the SaaS business model, the future seems to be a transformative one, regardless of whether it transitions to AI agents or works in tandem with the transformative tech.

Bite-Sized Brains

• Aussie Creators Push Back On AI Scraping: Arts and media groups urged the Labor government to take a stand against the ‘rampant theft’ of Australian content for AI training.

• xAI’s Top Lawyer Exits: After a whirlwind year of lawsuits, policy flare-ups, and rapid model releases, the legal chief has stepped down.

• Google TV’s Ad Math Gets Messy: OEMs, app partners, and Google are wrestling over who gets paid as homescreen video ads and FAST channels expand.

Roko Pro-Tip

Quick Poll

Meme Of The Day

Rate This Edition