As a long-time Airtable user and an enthusiast for AI-enhanced workflows, I was thrilled to discover AITable. The concept of combining the versatility of a table-based database with AI features sounded like the perfect solution, especially for users like me who rely heavily on custom automation and data manipulation. However, after diving into the software, I’m left feeling like it hasn’t quite lived up to its potential—yet.

While AITable has a lot of promise, it seems to miss the point of its name: empowering users with AI-driven capabilities. The biggest disappointment for me is their decision to restrict AI functionality to their in-house implementation. Unlike Airtable, which has always been somewhat rigid about how it integrates new features, I had high hopes that AITable would break the mold and offer true flexibility. Specifically, I hoped for the ability to use my own API keys and models, enabling advanced use cases like filling fields dynamically with AI formulas and customizing workflows at a granular level.

Unfortunately, this is not on their roadmap, as confirmed by their team. The refusal to allow users to bring their own AI keys (BYOAK) or choose their preferred models feels like a step backward. It places unnecessary limitations on what could be a game-changing platform for power users and innovators. Instead of focusing on flexibility, AITable appears to be taking a similar approach to Airtable by gating the AI functionality within their ecosystem.

This lack of openness is disappointing. I invested in AITable hoping it would someday cater to advanced workflows, but their current direction seems to mirror the frustrating limitations of other platforms. While the software has potential and could be a great tool for more basic use cases, it’s not the solution for those who want true AI integration without being locked into proprietary systems.

I’ll continue to watch their development, but for now, it feels like a missed opportunity to truly redefine what AI-enhanced tables could be.