If we look back at the beginnings of the Internet, one key thing stands out when we compare this to the introduction to AI-ML. During the early Internet days, we lacked the kinds of technologies to truly make the Internet a high value platform. As an example, a lot of companies created websites introducing their organizations, product lines and or services. However, there were a lot of back-office people manually taking product inquiries and product orders and entering orders into their ERPs or order entry systems.

Yet one of the uniqueness with the introduction of AI-ML when compared to the Internet beginnings is that businesses also have access to Structured AI-ML Design platforms complimented with Generative AI (provided the platform is solid and well designed) and immediately develop more comprehensive business and corporate strategies for their organizations. 

In addition, business leaders can quickly gain access to internal and external knowledge and align existing knowledge and its wisdom into the business and its planning process, core capabilities, competency sets, and products/services. Companies can immediately advance their productivity. Companies also increased their capabilities to uncover incongruities and achieve comprehensive innovation. 

Yet the challenge for any organization is the concern for the current cognitive learning gap. If a business wants to build enterprise AI-ML platforms they will need to develop an understanding of all the kinds of thinking behaviors and models people use every day. They will need to learn how to incorporate these thinking behaviors into their business and system architecture as they design new solutions. The other concern in some cases is you have a lot of don't know don't know advising the don't know don't know......and this is going to be an issue.  Click on link below to read the white paper.

Adapting to Generative AI, Advancing the Business in a Smart Connecting World