To benefit from AI we need "AI for everyone"
One of the most popular topics in information technology is artificial intelligence. But does that also mean that every company and thus also the associated employees use AI beneficially?
Technical capabilities have improved
The technical capabilities for implementing AI solutions with little effort have improved massively in recent years with the increasing spread of cloud offers. In addition to provisioning pure infrastructure components, powerful AI services are now also provided via the cloud. Furthermore, in-house developments can be implemented quickly using a large number of established open-source frameworks. Due to these technical possibilities, one could conclude that this technology will be used across the board in every company in a very short time or that this is already the case. However, it is not that simple.
Many AI projects fail
The technical aspects described above are one of the main reasons why many companies are experimenting with AI. Unfortunately, however, AI projects often fail because they do not offer any real added value for the business, be it for the company's employees or the actual customers. Despite all the technical simplifications, implementing AI involves considerable effort.
A lot of work must be put in data engineering (acquisition, storage, cleansing, enrichment of data) before AI algorithms can begin working on this data. It is therefore even more important that AI experts and representatives from the business units get together before a project and discuss the possibilities of using AI. On the one hand, not every idea is technically feasible; on the other hand, not every feasible solution creates added value for the business. And this added value for the business is the main reason for dealing with AI in the first place. Hence, it is also clear that the ideas for useful AI solutions must come from the business units.
How to implement AI successfully
For a company to be able to implement AI successfully in the long term, it is essential that all employees have a basic understanding of AI as a technology. How does AI work? What possible uses are conceivable? Where are the limits? There are also some concerns and fears associated with the use of AI. These topics can be addressed and usually resolved through easily understandable and accessible training courses.
Ideally, a company should set up a dedicated team that is responsible for providing these courses. Such a team promotes awareness of the topic AI in the organization. Lectures and workshops under a title such as "AI for everyone", will clarify the topic and encourage discussions. The main goal is to give employees the ability to think openly about the use of artificial intelligence in their everyday work. Where could an AI solution support me? How could tiresome work steps be made easier, faster, or perhaps even be improved in quality? Where could real added value be created through AI, which may also provide additional benefits for our customers?
Equipped with this intellectual openness, potential use cases for AI can be easily identified, which can then be implemented and tested in prototypes, for example. A good use case generates added value (for the business units or customers), can be implemented technically and will also be economically beneficial in the combination of these two aspects. It is therefore obvious to put such AI use cases into production in the next step.
In summary, it can be said that the technical capabilities of implementing AI solutions with little effort are better today than ever before. However, to create real added value for the organization, the right use cases must be implemented, which requires a broad understanding of AI technology in the company. For AI to be able to bring benefits to everyone, everyone must be qualified accordingly. This is the core concept of "AI for everyone".
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