The use of artificial intelligence is not as difficult as imagined. You can get started with fairly raw data. The required workloads are also reasonable, although it requires an attitude that deviates from the norm.
In artificial intelligence projects, data is utilised differently than before, often in completely unprecedented ways. Starting with projects, no one can be sure what the end result will be, when it will be ready (or will it ever be finished), and what it costs.
This uncertainty slows down the use of artificial intelligence, especially in organisations that do not want to let go of the old ways of working, predetermined plans, business cases and fixed price offers. Now is the time to dare: The longer you wait, the more data accumulates in your organisation in vain.
1. You cannot define the outcome in the beginning
Problems that have not been solved before can often be solved with the help of artificial intelligence. I myself have been involved in solving problems which were not even known to exist at the start of the project.
So how do you know how to utilise AI? Who can tell you where you should apply it? From nowhere. Nobody. At least if you do not dare to start.
You will have to decide to start. You need to clear space for the exploration and exploitation of AI. You need to give your organisation an opportunity for something new and unspecified.
2. Keep an open mind for learning
In artificial intelligence projects, rather than technology, most important is the willingness and ability to create something new. An artificial intelligence project can begin to streamline an existing process, but there is much greater potential in new innovations. LED lights were not born out of making candles!
3. AI creates bridges over silos
A broad understanding of opportunities is needed because AI solutions should, under no circumstances, be utilised solely for traditional point-to-point profit centre development. This is exactly where the potential of AI lies. You can use it to combine source data from across the organisation – data that could not previously be combined. For this reason, it is very typical that the most valuable findings come as if by accident.
Don’t let the assumptions stop you
False assumptions can obstruct the path of artificial intelligence. Perhaps the most common of these are prejudices related to data protection and law, and the assumption that the quality of one’s own data is not enough.
Fairly raw data is enough to get started. Values, anonymisation, and pseudonymisation enable closed and secure applications in a closed environment. In an enclosed environment, anonymity does not break because unlimited data sharing is not possible. In many organisations, the settings are reasonably good.
Many processes have already been digitalised; data on important processes and customers can be found. Also, awareness of the potential of artificial intelligence is steadily spreading. Take the opportunity to provide your organisation with valuable personal experiences of what artificial intelligence really is and what can be realistically achieved with its help.
Begin today. You don’t gain anything by waiting!