Most of these organizations are looking for customizations that B2B SaaS struggles to provide since they have to walk a line of catering to a market segment broadly then building customization for specific clients.
I've seen a huge surge in organizations investing in small software development teams to do internal builds for things that they just aren't getting from these tools. Technology is not the value center for these companies.
I work in healthcare, so my perspective is heavily contextualized by that, but I'm seeing providers (especially specialty providers) build internal engineering teams to create ancillary systems that sit on top of their EHR. They are doing this instead of buying similar modules that might be up sold by the EHR.
Anyway, I just feel like these market trends are deeper than what this article implies.
2. A suspicious number of "It's not X, it's Y" in this piece.
1. My cousin who works for an enterprise real estate SaaS company. He said their main product has iirc 10-20,000 database tables.
2. Evernote users had famously little overlap in which features they used. Everyone use a slightly different subset of Evernote tools.
I wonder if you could create a 2x2 grid of these two scenarios to determine a SaaS tool's likelihood of being replaced with AI.
- Complex Data Model + High feature adoption: Low risk of AI
- Complex Data Model + Low feature adoption: Medium risk short term. High long term.
- Simple data model + High feature adoption: High long term risk risk, but limited ability to grow accouts
- Simple data + low feature adoption: Very high risk