Is generative AI really ready for the enterprise?

penAI released ChatGPT just a few short months ago, and it’s fair to say that it took the world by storm: It has over 100 million active users already. No wonder, when it can generate human-like, grammatically correct responses. Related technologies can also produce artwork and code by entering a description of what you want, and the tech produces it.

You can even interact with the AI after your initial question, so if you don’t like the output you got or need clarification, you can ask additional questions or make adjustments to your picture or code, so it more closely matches your vision. All of this happens instantly without the help of a subject expert, an artist or a coder.

But none of this comes without issues, which include the sourcing of the data used to train the underlying AI model, the currency of that training data, a lack of permissions to use the source data, bias in the model and, perhaps most importantly, the accuracy of the responses, which are sometimes laughably wrong.

None of this has stopped enterprise software companies from taking the generative AI plunge. These companies see massive commercial potential and a lot of enthusiasm from users and they clearly don’t want to get left behind.

Salesforce, Forethought and Thoughtspot all recently announced betas of their own flavors of generative AI. Salesforce is adding generative AI across the platform. Forethought is aiming at chatbots and Thoughtspot wants to use AI for data querying. Each company took the base technology and added some algorithmic boosters to tune the tech for their platform’s unique requirements.

Microsoft also announced that its OpenAI service aimed at enterprise users on Azure is generally available as a managed service.

Throughout this year you can expect to see many more companies joining in, but the limitations are real, which makes us wonder: Is the technology — as early and raw as it is, no matter how cool it looks on its face — really enterprise ready?

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