Artificial intelligence: Why machines won’t make us unemployed.

“Those who immediately associate AI with ‘man versus machine’ often lack the necessary background information. Awareness-raising is the only way to counter this,” says Joachim Göller, Head of the Center of Analytics of the EOS Group. He and his team are working on AI solutions that help EOS with receivables management. “With the support of artificial intelligence, people will drastically reduce the error rate in receivables management. In any case, this is also what 30 percent of the financial executives from the survey think.”

By using AI properly, a company will ideally become more competitive and can allow its staff to take on more interesting tasks. At EOS, for example, collection teams use artificial intelligence for routine cases, so that they can focus on those customers whose cases are more complex. Other sectors are also relieving their specialist personnel of standard processes. Finnish software company Basware, for example, has developed a virtual assistant that answers everyday queries in the procurement department.  And Swedish bank SEB reduces the workload of its IT support with Ipsoft’s smart virtual assistant Amelia.

“First of all the company has to produce an overview: Where exactly can AI be used to automate simple tasks? Where can it make complex processes more user-friendly?”, says Goossens. It is at this stage that many companies realize that they lack the most important basis for introducing self-learning systems, i.e. the necessary quality and volume of data to feed the algorithms. “Generally, most companies don’t have data engineers,” says Goossens – i.e. those experts that ensure that all data are clearly structured and stored in one place. This is a challenge for companies where departments are still working with different IT systems and separate databases.