Companies are panicking in the face of AI!

Overwhelmed by technological announcements, many players are struggling to understand how to integrate artificial intelligence without putting themselves at risk. By Xavier Comtesse

An article available in AGEFI: https://agefi.com/actualites/opinions/face-a-lia-les-entreprises-paniquent

A wave of panic is sweeping through Swiss companies in the face of the artificial intelligence (AI) onslaught. What are the risks? Will my data be stolen? Should we adopt AI? How do we go about it? The questions are flying thick and fast. The answers are numerous but far from clear.

In fact, the problem lies both in the avalanche of announcements from tech giants (which raises questions) and in the need for business continuity (which creates paralysis). No one wants to abandon their IT systems. ERP, CRM, and other standard software work. Why change them? And above all, destroy them to build what? In short, no one has a clear vision! So how do we move forward? It's simple if we understand two things.

1. The data

Since the 1960s, business digitization has been carried out using structured data. This data was entered into predefined memory locations, or fields, as computer scientists called them. It was an assembly of simple numbers and letters, represented in binary.

This first wave focused on organizing and automating transactional information and business processes. Data was primarily used to manage the company with IT tools such as ERP (Enterprise Resource Planning) or CRM (Customer Relationship Management) systems. The data was stored in databases. The goal was to replace manual processes (paper, filing cabinets) with digital systems to make the company more efficient.

With artificial intelligence, we've been able, for over a decade, to process unstructured data such as images, video, audio, emails, all kinds of documents, blogs, social media, and so on. This represents more than 90% of the information in the real world. It's a significant change in scale, but also in capability, because we can now discover patterns in tons of data that we couldn't see before. Large Language Models (LLMs) are a fascinating example of this, as are computer vision (like the Waymo taxis in San Francisco) and predictive machine maintenance.

2. The second digitization

With the introduction of AI in businesses, we can now speak of a second wave of digitalization, given how much things are changing with unstructured data. It's a tipping point between an old and a new world.

However, it is absolutely essential to keep new developments separate from the core of traditional IT systems, for example by storing this data on new platforms—a sort of second skin. The goal is to maintain "business as usual" while continuing to innovate. This second wave of digitalization is not a rewrite of the first; it should be understood as an extension, or even a surpassing, of that.

This will allow us to develop new ways to create value for customers, particularly through a deep understanding of their needs. It involves analyzing customer behavior and sentiment, implementing predictive maintenance, and automating complex cognitive tasks to increase customer productivity. That's what AI is: an extraordinary ability to understand what was previously hidden in inaccessible data.

By Xavier Comtesse