WHY THIS MATTERS IN BRIEF
Software as a Service is the bedrock of the global software industry, and AI Agents could change it dramatically.
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Over the holidays, an excerpt from an interview with Microsoft CEO Satya Nadella went viral in which Nadella allegedly predicted the “Death of Software-as-a-Service” (SaaS) because of the emergence of ever smarter Artificial Intelligence (AI) agents who will work together to build new kinds of software and deliver new services and capabilities very differently to the way they’re built and delivered today.
But Nadella did not at all speak about the “death of SaaS apps.” He repeatedly referred to business apps as “canvases” for writing, calculation, or other business functions.
Still, it is clear that the way how business users interact with apps will change dramatically as AI agents become the primary interface to SaaS apps for many users.
An AI agent might for example proactively identify customers for a specific seasonal upsale based on information in your CRM, draft and send a sales E-Mail using your mail service, register a purchase on your website and trigger the shipment of the product in your E-Commerce platform, monitor complaints through your customer support platform, and feed back all this information into your main CRM.
Looking at the complexity of these so called agentic workflows, it seems unlikely that a single AI system will be able to integrate all of these activities in one single piece of software in the near future – and that at this point, the agent will essentially have become a SaaS product itself.
In the interview, Nadella also seems to suggest that certain elements of a software, such as a spreadsheet, could be created “on the fly” by a Large Language Model (LLM). But it is doubtful whether this would be economical. While it is nice to be able to create a minimum viable product in an AI chat bot, it would not make sense to re-invent the wheel every time someone makes a certain standard query.
The Future of Artificial Intelligence Keynote, by Futurist Matthew Griffin
The current pace of technological progress is extremely fast, but as these technologies meet legacy technologies, there will be all kinds of unforeseen challenges to unlocking the full potential of AI. Organisations and societies naturally change at a slower pace than start-ups do.
In his essay “Machines of Loving Grace”, Anthropic co-founder Dario Amodei introduces the concept of a “compressed 21st century”1 because advanced AI is likely to allow us to make discoveries in health and biology in a time span of five to ten years that would require 50 to 100 years of research without AI.
In the same essay, Amodei however also acknowledges that existing regulations may significantly slow down the impact that new technologies can have. It is therefore not surprising that it may take decades until we see the economic impact of AI – I actually think it’s more one decade than two because of the emergence companies built on AI but in any case, it will be more than two to three years.
There is also an alternative scenario to the one outlined by Satya Nadella where AI accelerates the release of new software. This scenario was described most eloquently by Scott Belsky in his newsletter “Implications”:
“DIY software will revolutionize apps for consumers and the enterprise. There has been much discussion of AI code reviews, GitHub co-pilot, and no-code application builders for the enterprise, but what are the implications of agent-assisted software development for consumers? Quick apps for your home or family were too hard to build until now. I think we’ll see some pretty remarkable and super niche software applications emerge in 2025, by and for consumers. And in the enterprise, the cost calculation of building your own internal tools and Generative Apps will start to merit AI-made homegrown solutions to workflows and enterprise functions – and increasingly agents will replace these functions, per the last forecast on the list as opposed to the usual “find a SaaS product to solve every need.””
In this scenario, AI agents trigger a surge of custom-made apps that are built with just one customer in mind.
While it is hard to predict how the market for software will develop, it is easy to see that the change will be significant: If AI agents become the primary point of interaction with users, developers will have to reimagine the architecture of their software and tailor them specifically to AI agents. Expenses for example may be filed easily just by taking a photo of a bill without the user having to open an app.
This however means that certain parts of a software business will become less relevant. As Azeem Azar puts it in a recent episode of “Exponential View”:
“I think that you’ve got a classic innovator’s dilemma if you are a traditional SaaS company, because the way in which you build, the way in which your products work, the way in which your teams are organized doesn’t necessarily sit nicely with an AI model,” he says.
On the other hand, larger SaaS firms will double down on their investments in well-designed user interfaces – let’s face it, the chat interface it not the end of UX design for AI. And many SaaS firms have already done a pretty good job in integrating AI and will continue doing so.
But what does this mean for the European Commission’s political agenda? AI agents will play a large role in closing the productivity gap between the US and the EU. At a time where talent is scarce, AI bots will allow companies to build a “limitless workforce”, according to Salesforce CEO Marc Benioff. But in order to do so, they will need to understand how AI agents fit into the existing digital rulebook of the EU.
In his interview, Nadella already pointed out some of the regulatory issues related to AI agents: Maintaining cybersecurity is naturally a key concern, shortly followed by questions around how access to these various apps by an AI agent should be governed. Should a company be allowed to restrict access for agents that for example are not build by them? If they do, could this be considered anti-competitive behaviour?
The Future of AI Agentic Cybersecurity Keynote, by Futurist Matthew Griffin
On a related note, it remains to be seen whether the emergence of AI agents shifts where value is created in the software market and how this shapes market dynamics in the software industry.
The more complex questions will resolve around how the deployment of AI agents will interact with existing laws such as the GDPR, cybersecurity regulations or the Product Liability Directive. Without a doubt, the software value chain will become more complex and it will become more difficult to assign responsibilities to individual economic actors.
Finally, while the Data Act mostly does not cover SaaS, its main idea of making data accessible is highly relevant for agentic AI. The law, however, only comes into force later this year and it remains to be seen whether it is even fit for purpose for the Internet of Things for which the law was originally created for.
Reducing regulatory complexity will be crucial for the Commission’s goal to increase the uptake of advanced technologies such as AI agents. Next week, the Commission plans to announce its “Competitiveness Compass.” This will be indication of how serious the new Commission is about streamlining the proliferation of digital rules.
