AI won’t kill SaaS

opinion Sep 8, 20267 mins SaaS companies that allow customers to use AI for customizations increase customer interest in the original SaaS product. Nvidia CEO Jensen Huang argues it’s the “most illogical thing in the world” to believe AI will kill SaaS, and says the markets “got it wrong” in sending SaaS stocks tumbling. Why “illogical”? Because, as analyst Benedict Evans stresses, the fact that everyone can now easily spin up code actually doesn’t solve any SaaS problems, because creating code and tools is the easy part: “The hard part is knowing that you need a tool for this in the first place and then knowing what the tool should do.” If that’s true, then what Shopify is doing with Sidekick is potentially revolutionary by embracing and extending the traditional SaaS model. In December, Shopify introduced custom app generation through Sidekick. A merchant (Shopify customer) describes a tool, and Sidekick writes the code, using Shopify’s interface components and connecting to its Admin API. It’s a cool option and has been very popular. Shopify says merchants created almost 4,000 custom apps in the first three weeks following the release. This isn’t surprising: Shopify is delivering the customization customers have long wanted from enterprise SaaS while ensuring they still enjoy the comfort of ongoing support and platform stability. I suspect we’ll see more enterprise SaaS like this, despite silly predictions that AI would kill SaaS. Cheaper code gives customers a way to fix the things they dislike about an application without replacing everything they do like. For a vendor willing to accommodate that, AI could make its product considerably more useful and, hence, much “stickier.” The feature that never ships Cloudflare’s Jeremy Morrell discusses this in an excellent essay on extensible software. “In the past year, your users have suddenly acquired the ability to speak code into existence,” he writes, allowing for “markets of one.” His argument is that software should let customers put that ability to work, building additions around an established core. Morrell has a commercial interest here, which he discloses: He works at Cloudflare and thinks its infrastructure is well suited to running those additions. He’s not wrong. But it’s the general opportunity to match customizability with stability that matters so much. There are really (really) good reasons why vendors haven’t allowed customizability of their core products. Enterprise software companies limit deep customization to prevent high maintenance costs, security risks, and broken system updates. Oh, and to prevent their products from becoming convoluted bloatware. No matter how much you may want feature X, that feature would likely be irrelevant to almost everyone else, so adding it would complicate the product for the majority. No one wants that. Customers have long paid consultants to customize software or they’ve hired developers to do it themselves (all while taking care not to violate their vendor licenses). Morrell points to Salesforce, which has spent years letting businesses build their own logic into its platform. In other words, AI didn’t invent extensibility. No, AI just makes it incredibly cheap. There’s a meaningful opportunity here for customers who can describe the change they need but have never been able to get it built. Some will save money on software or customizations they previously bought, while others will finally get software that nobody could profitably sell them. Following the money This change, however welcome for enterprises, won’t be comfortable for developers selling a narrow reporting tool or a small workflow improvement. Their customers may decide that an LLM-generated extension is good enough. An AI-built customization needn’t match every feature of the commercial product. It only has to do the job that the customer was paying for. The platform underneath that extension has a different calculation. Every useful tool built against its data and APIs gives the customer another reason to stay. AI can make an individual feature less valuable to sell while making the product that hosts it more valuable to own. (Yet another reason to tsk-tsk foolish eulogies for SaaS companies.) Ultimately, this should benefit anyone who both knows the business and can build more efficiently for that business. Benedict Evans makes this point in his newsletter, arguing that cheaper coding doesn’t solve the problem of discovering what software ought to do or persuading an organization to use it. A useful idea that spans several departments still needs those departments to agree. Even excellent code can’t sign off on a new way of running accounts payable. Evans also describes how improvised tools eventually become important enough to need formal ownership and support. Anyone betting that companies will happily maintain everything they can generate should spend some time with the person who inherited the last departmental spreadsheet. Silicon Valley folks with little knowledge of real-world enterprises might think enterprises will vibe code all their software now, but they won’t. That’s not how software works because it’s not how people work. This cuts both ways for established software vendors. Customers may continue to need their expertise while becoming less willing to accept a product’s limitations. A vendor that makes customization easy can benefit from that impatience, while one that blocks it has given the customer a new reason to investigate alternatives. The difficult decisions will come when customization interferes with what the vendor already sells. I wrote in 2022 about Microsoft’s complicated relationship with open source, and how a company’s broad commitment to openness can collide with a division’s revenue targets. The same tension applies here. A CEO can be excited about letting customers build anything. The executive responsible for selling the premium reporting package may be less enthusiastic. Resolving that disagreement will determine what customers actually get to build, however capable the AI becomes. Getting comfortable Customers have their own calculations to make. An application shaped around the way your company works can be wonderful, but it can also be a pain to leave. There are limits to what Shopify’s generated apps can do today. They are admin tools, not storefront or checkout extensions. Shopify also tells merchants to test them before installation because they can change customer-facing data. A generated app can be wrong, and running it inside a familiar product doesn’t relieve the merchant of checking its work. Shopify lets merchants inspect and edit the generated code and restore an earlier version. That’s useful, but code written for Shopify’s Admin API still depends on Shopify. Having the source doesn’t give you another company ready to run it unchanged. AI might eventually make moving those extensions easier, too. But recreating a screen is one thing; reproducing the behavior it relies on throughout a business is a considerably bigger undertaking. That includes the assumptions about records and transactions that the custom code gets to take for granted while it runs on the original platform. None of this makes customization a bad deal. Customers can gain more control over their daily work while, somewhat ironically, becoming more dependent on a supplier. For SaaS vendors, that’s a good commercial reason to let customers finish the bits their developers will never get around to building, even when it costs them an add-on sale (and potentially some support headaches, depending on how they’re architected for extensibility). The customer is doing work that makes the underlying product more valuable. AI, in short, has the potential to make SaaS dramatically more valuable, not extinct. Matt Asay runs developer marketing at Oracle. Previously Asay ran developer relations at MongoDB, and before that he was a Principal at Amazon Web Services and Head of Developer Ecosystem for Adobe. Prior to Adobe, Asay held a range of roles at open source companies: VP of business development, marketing, and community at MongoDB; VP of business development at real-time analytics company Nodeable (acquired by Appcelerator); VP of business development and interim CEO at mobile HTML5 start-up Strobe (acquired by Facebook); COO at Canonical, the Ubuntu Linux company; and head of the Americas at Alfresco, a content management startup. Asay is an emeritus board member of the Open Source Initiative (OSI) and holds a JD from Stanford, where he focused on open source and other IP licensing issues. The views expressed in Matt’s posts are Matt’s, and don’t represent the views of his employer. More from this author Show me more