There may be more AI in the apps on your mobile than in all your business applications.
Non-intelligent IT products were provided with an AI label. What my colleague Ron Tolido calls “fake AI.” Amazon web services have been able to respond effectively to the big AI promise since 2005. But is the underlying technology true AI?
No wonder that there are IT experts saying that it is all a hype and that it is soon over. But too many successes have been achieved. Yes, the imitation of human intelligence is still (very) far away. But the application of machine-intelligence and machine-based learning is already happening. Both inside and outside the laboratory.
AI is now used for specific applications for specific business situations. Examples are chatbots, knowledge systems, speech and image recognition.
We can, of course, wait for the product suppliers to incorporate genuine Artificial Intelligence into their products. But this is a lazy form of innovation that doesn’t make us competitive. And it should be made clear whether these ready-to-use products actually add value.
AI costs more than a few clicks to take it into use. After all, you must also teach the machine the subject matter. But if you really go for it, you can automate (routine) work so that your real productivity improvements are possible. For example, IBM Watson can read Watson’s 500 gigabytes of information (equivalent to one million books) per second. No human can do that.
Artificial Intelligence will stay. And the AI frameworks and micro apps are mature enough to start building applications. Not only to make steps in a process more efficient but really to look at what AI can do for your processes and data. How can we gain real improvements? Or do things that have never been done before?
But there are no ready-made solutions for every business situation (yet). Capgemini has therefore opted to explore new technologies for internal use and for and with its customers. By actively working on an ecosystem and development methods whereby product suppliers and customers can be brought together and new solutions can be created. Which may fail. In order to build knowledge and experience about Artificial Intelligence.