Artificial intelligence (AI) can become a growth engine for German industry: By 2030, Germany's gross domestic product could be up to 4 percent, or the equivalent of €160 billion, higher than without the use of AI through the early and consistent use of intelligent robots and self-learning computers. This corresponds to an additional annual growth of 0.25 percentage points, or €10 billion.
This growth is driven by increased productivity combined with the creation of new, value-creating fields of activity. These are the key findings of a recent McKinsey study titled "Smartening up with Artificial Intelligence (AI) – What's in it for Germany and its Industrial Sector?" The study analyzed, among other things, the eight key application areas of artificial intelligence for German industry, which can serve as a starting point for companies to utilize AI.
Overcoming the demographic bottleneck with AI
“In view of demographic developments, increasing productivity through artificial intelligence is a decisive factor for the German economy,”
explained Harald Bauer, Senior Partner in McKinsey’s Frankfurt office.
"AI promises benefits not only from an economic perspective, but also from a business perspective: It gives employees the opportunity to delegate repetitive or dangerous work to computers and robots and concentrate on value-adding and interesting tasks."
In addition, AI opens up entirely new business areas for companies. The increasing use of artificial intelligence is based on breakthroughs in technology. Self-learning algorithms, for example, ensure that computers can recognize and classify images ever more effectively: While the error rate for computer-assisted image recognition was 28% in 2010, it was less than 5% in 2016; for speech recognition, the rate fell from 27% in 1997 to 6% last year.
Investment activities surrounding AI-focused companies have also increased at the same pace: While only 67 financing rounds for AI startups were completed worldwide in 2011, this number had risen to almost 400 by 2015. The global market for AI-based services, software, and hardware is growing by up to 251,000 million euros annually and is expected to reach 130 billion US dollars by 2025.
20% higher utilization, 30% less waste
“The use of artificial intelligence has particular potential in manufacturing industries with their high proportion of predictable activities,”
says Matthias Breunig, Partner in the Hamburg office of McKinsey.
“It is precisely the combination of artificial intelligence with the networking of machines – the Internet of Things – that is leading to new possibilities.”
According to the study, the following application areas are of particular importance for German industry:
- Production: Improved plant utilization is possible when, for example, AI performs maintenance work in a predictive manner ("predictive maintenance"). Likewise, increased productivity in individual work steps is possible through targeted collaboration between robots and employees. Furthermore, quality monitoring can be made more productive through AI—for example, through automatic visual defect detection in products. In certain areas, a reduction in scrap of up to 30% is possible.
- Business processes: Supply chain optimization—for example, through more accurate sales forecasts—can lead to a reduction in inventory costs of up to 50%. In research and development, cost reductions of 10 to 15% and shorter time-to-market of 10% are possible. In indirect business areas such as IT, artificial intelligence can take over 30% of the activities.
- Products and services: Artificial intelligence is one of the key prerequisites for self-driving cars. By 2030, up to 151,000 newly registered vehicles could be autonomous, with significant growth rates until 2040.
Five pragmatic recommendations for companies
“We are only at the beginning of an exciting development,”
says Matthias Breunig.
“The prerequisite for the meaningful use of artificial intelligence is an open debate about how and where humans and machines can work together meaningfully.”
To avoid missing out on the opportunities offered by AI, companies should:
- understand the opportunities of AI, define pilot projects for themselves and do not lose sight of the economic viability,
- build AI competencies internally, but also work with specialized third-party providers,
- Store granular data wherever possible – it is the fuel for AI applications,
- combine existing detailed knowledge of your own products and manufacturing processes with new AI applications,
- Get small tests up and running quickly; no huge investments are necessary, but agility is a prerequisite for success.
