The term is often abbreviated AI after the English designation Artificial Intelligence, rather than the Danish abbreviation KI.

Artificial intelligence is here to stay. There are already many more things than we think, e.g. Netflix and Amazon, which use algorithms to recommend programs and products to you.

Ai can, for example, used to find out what characterizes a good beer or who would be the ideal candidate for a given position. But by training the AI with training data in the right quantity and quality, the algorithm can learn to recognize good beers or employees. It obviously saves companies a lot of work if an algorithm, based on a CV or other data, can with a high probability appoint the company's next sales manager.

They are therefore plenty of reasons to investigate whether AI is a technology that makes sense in your company. Here are 5 advantages.

5 advantages of artificial intelligence

1. Reduction of human error. It's human to err, but computers don't make those kinds of mistakes if they're programmed properly.
2. Assumes the risk instead of people. In dangerous situations, robots can take over and handle the dangerous tasks.
3. Available around the clock. Robots need neither sleep nor a lunch break.
4. Completes routine tasks. Robots don't get bored and don't lose concentration, and computers are even faster than humans for this type of task.
5. Make faster decisions. AI and computers are not hindered by having to consider emotional or practical solutions, but only work from its programming, which means much faster results than humans.

But don't rush into it headlong. As we wrote in the introduction, the use of AI is not without problems. Companies should think twice before plunging into artificial intelligence.

What should you be aware of before getting started with artificial intelligence?

Below we describe 8 pitfalls you must be aware of before you open the door to artificial intelligence.

8 pitfalls you must be aware of before you get started with artificial intelligence

1. The result is not known. Artificial intelligence is an iterative process and you don't know the answer in advance. Perhaps the result will be that it cannot be used for anything. This is something you have to be aware of from the start and a risk you have to be willing to take before you dive into working with artificial intelligence.
2. Algorithms with bias. AI can, for example, use for employment, where you teach the computer to recognize "the ideal employee". But if the data set is prejudiced (or what is called biased in English), the artificial intelligence will also be biased. Because artificial intelligence is no better than the data it is trained on. It shows us, so to speak, a mirror image of ourselves. That's why there are more examples on artificial intelligence that had bias based on e.g. skin color or gender. Eg. Amazon's hiring algorithm that taught itself that male candidates were preferable. Defies the intent of the automation. However, it must be remembered that we everyone is biased, and that it is more difficult to 'unlearn' human bias than it is to ensure that an algorithm is unbiased. So, applied correctly, AI can actually solve the task with less prejudice than in traditional employment situations.
3. Lack of transparency. Telling users how your data is generated is important, but sharing too much data can also be a problem. You can e.g. need to keep some trade secrets but want openness to avoid bias. Called the transparency paradox.
4. GDPR. Artificial intelligence deals with data. And with access to data comes responsibility and rules. It is important to have both the GDPR legislation as well as ethical and moral considerations in mind when automating processes, so that sensitive personal data and privacy are protected.
5. Ethical considerations. How much responsibility should an artificial intelligence have? Should it have as much responsibility as e.g. a doctor whose mistakes could be worse potentially fatal?
6. Loss aversion. It can be difficult to stop a project, even if it no longer produces the results you set as a goal. The AI project can also take hold and become far larger and more complex than the company is ready to handle.
7. Risk of error. Because processes are being automated, you will experience errors. Artificial intelligence requires that both data input and output are monitored.
8. When working with data, there is a risk of cyber attacks, where hackers gain access to your data. And threatens to delete or manipulate training data so that your results are incorrect.

Is artificial intelligence right for your business?

Despite its many possibilities, artificial intelligence is still a new technology with great development potential. If you want to take advantage of the many opportunities for efficiencies that digitization offers, it may be a good idea to investigate whether artificial intelligence is something that makes sense to implement in your company.