These days, business managers are under increasing pressure to use generative AI (GenAI) as a business management tool, and there are high expectations regarding improved productivity at lower cost. In order for GenAI to really provide the kind of fully informed picture of the business, however, it must have access to complete, high quality, and consistent data from across the enterprise. Sadly, these days, most business databases are stuck in departmental or business function dependent siloes.

The solution to this problem, and what’s needed to achieve the dream of making AI at least a junior partner in business management, is to make comprehensive access to data along with the metadata necessary to make the meaning and context of the data clear. In short, what’s called for is an Enterprise Data Platform.

AI is the current darling of the IT world. Some people expect that it will eliminate millions of jobs and make the remaining jobs far easier and more productive. Perhaps. But we must also be realistic about what AI can do for us. The term seems to imply actual intelligence that is produced artificially, rather than by humans. In this document, I suggest that it is really a facilitator of intelligence and has some of the external characteristics of intelligent behavior but may be better labeled “synthetic intelligence”.

I have found that there are many who believe that having systems that can answer questions posed in human language with human language responses means that structured data is somehow passe. Nothing could be further from the truth. AI, driven by very large sets of text such as scanned Internet content can only give approximate answers to questions because the source of information is approximate. In fact, sometimes the patterns in the source text are so inconsistent that the resulting answer provided by the GenAI system can be unintentionally comical.