From AI hype to the new normal

Discussions about artificial intelligence have so far moved from theory to practice. New applications, especially ChatGPT, make AI accessible to a broad public through radical user-friendliness similar to Google.

It’s only about an aha experience at first. For millions of users, ChatGPT became a daily practice in no time.

Thus begins a cascade of changes that should be grappled with by virtually anyone not wanting to miss a historic opportunity.

Aug 1981 IBM launches the first personal computer
Sep 1998 Google launches its search engine
June 2007 Apple launches the first iPhone
November 2022 open.ai publishes ChatGPT

Artificial neural network technology has been known since the 1950s. Only with the availability of cloud platforms could they be scaled to a size that yielded useful results.

Goolge’s BERT and IBM’s Watson also work with artificial neural networks, but ChatGPT has obviously reached a critical mass that opens up a broader business-relevant field of application.

ChatGPT is still a long way from being the omniscient, error-free “computer brain” that we know from movies. But if you look at the development from GPT-2 (Feb 2019), through GPT-3 (June 2020) to GPT 3.5, as it is now the basis of ChatGPT, you can expect further rapid improvement.

As always, journalists and other media representatives have been working on the weaknesses and oddities in order to generate the attention that belongs to your business model.

As a business manager, however, you have to deal objectively with opportunities and risks. Just imagine if your employees had been banned from using Google for the past few years.

In addition to the generative Transformer models such as ChatGPT, there is a whole range of technologies such as Robotic Process Automation (RPA), Machine Learning, Natural Language Processing (NLP), and Computer Vision that require professional management on a permanent basis.

Therefore, the following agenda is recommended for every responsible business manager:

make your own experiences
assign the topic to an area of ​​responsibility
set up an AI CoE analogous to the Cloud Center of Excellence (CCoE), the Lean-Agile Center of Excellence (LACE), which institutionalizes the discussion of the topic
Carry out governance, risk, and compliance assessments ( EU AI Act )
Conduct briefings with managers
Identify use cases across the enterprise

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