I don't think AI is killing B2B SaaS so much as companies are finally reckoning with the immense costs of SaaS in a markably different environment than when SaaS exploded in popularity, and AI offers an off-ramp to some. Let's break it down camp-by-camp to show you what I mean:

1) The must-haves. These are your email and communication systems, the things you absolutely have to have up and available at all times to do business. While previously self-hosted (Exchange/Sendmail, IRC/Skype/Jabber, CallManager/UCS), the immense costs and complexities of managing systems ultimately built on archaic, monolithic, and otherwise difficult-to-scale technologies meant that SaaS made sense from a cost and a technical perspective. Let's face it, the fact nobody really hosts their own e-mail anymore in favor of Proton/Microsoft/Google/et al shows that self-hosting is the exception here, not the norm - and they're not going anywhere regardless of how bad the economy gets. These are the "housing stock" of business, and there's plenty of cheap stock always available to setup shop in without the need for technical talent.

2) The juggernauts. The, "we can do this ourselves, but the pain will be so immense that we really don't want to". This is the area where early SaaS solutions cornered and exploded in growth (O365, ServiceNow, Google Workspaces), because managing these things yourself - while feasible, even preferable - was just too cheap to pass up having someone else wrangle on your behalf with a reasonable SLA, freeing up your tech talent for all the other stuff. The problem is that once-focused products have become huge behemoths of complex features that most customers neither need nor use on a regular basis, at least after the initial pricey integration. Add in the ease of maintainability and scalability brought by containers or microservices, along with the availability and reliability of public cloud infrastructure, and suddenly there's more businesses re-evaluating their relationships with these products in the face of ever-rising prices. With AI tooling making data exfiltration and integration easier than ever from these sorts of products, I expect businesses to start consolidating into a single source of truth instead of using dozens of specific product suites - but not toppling any outright.

3) The nice-to-haves. The Figmas, the HubSpots, the myriad of niche-function-high-cost SaaS companies out there making up the bulk of the market. Those whose products lack self-hosted alternatives risk having vibe-coded alternatives be "good enough" for an Enterprise looking to slash costs without regard to long-term support or quality; those who compete with self-hosted alternatives are almost certainly cooked, to varying degrees. If AI tooling can crank out content similar in quality to Figma and the company has tech talent to refine it for long-term use, why bother paying for Figma? If AI tooling can crank out a CRUD UI for users that just executes standard REST API calls behind the scenes, then why bother paying for fancy frontends? While it's technically interesting and novel at how these startups solved issues around scaling, or databases, or tenancy, the reality is that a lot of these niche products or services could be handled in-house with a container manager, a Postgres instance, and a mid-level IT person to poke it when things go pear-shaped. The higher per-seat prices of a lot of these services make them ripe for replacement in businesses comfortable with leveraging AI for building solutions, and I expect that number to grow as the tools become more widely available and IT-friendly in terms of security.

Ultimately, the core promise of SaaS to business customers was all the functionality with none of the costs of self-hosting support. Nowadays, many of them have evolved into solutions that are more expensive than self-hosted options, and businesses that have shifted IT into public clouds or container-based systems have realized they can do the same thing for less themselves, at the cost of some UI/UX niceties in the process. Now that we (IT) can crank out integrations with local LLMs with little to no cost, we're finally able to merge datasets into singular pools or services - and I'm not talking about Snowflake or its "big data" ilk so much as just finally getting everything into Salesforce or ServiceNow without having to bring in consultants.

The must-haves and many of the juggernauts will remain - for now. It's the niche players that need to watch their moats.