In the future, the economy will only be successful if it is sustainable. The question is not whether this will happen, but how quickly. Given the complexity of the problems ahead, we need to redefine innovation – and artificial intelligence, combined with other high technologies, plays a crucial role in this approach.

A study by the KTH Royal Institute of Technology in Stockholm shows the extent to which artificial intelligence can help on the path to a sustainable society. The researchers analyzed where artificial intelligence methods can effectively support the 169 individual goals from the 17 UN Sustainable Development Goals.

The result: 134 of the individual goals can be achieved either faster or in higher quality with the support of applications from the field of artificial intelligence.

Just to give one example: Artificial intelligence can help solve the problem of varying availability of renewable energy sources – by balancing supply and demand more efficiently in so-called smart grid systems. It can help to better identify raw materials in waste, perform complex simulations for analyzing life cycle scenarios of new products, and much more. 

When it comes to developing something new, the most important thing is to achieve the required specifications as quickly as possible while conserving resources. However, the devil is in the details, because developing the special properties of new products or materials often takes a very long time and requires a lot of engineering knowledge and experience. This is where artificial intelligence can bring decisive progress and dramatically accelerate development work, as the following example shows.

Artificial intelligence, the geysers for sustainable innovations

Mixtures of different metals are the magic potion in mechanical engineering. The soft tin gives copper significantly greater strength and hardness – much appreciated in the Bronze Age for weapons. Chromium and nickel turn iron into stainless steel. Modern superalloys can have the properties of glass or no longer resist electric current. Depending on the composition, entirely new properties are created. 

The whole thing has a catch: time. It takes a long time to produce a new alloy if certain properties have to be met in the process. The scientists calculate three months per iteration. 20 iterations to the desired good, new alloy then quickly add up to five years of development time. 

A novel robotic system combined with an AI model achieves the same output within 5 months. In this process, the metal powders are mixed by a robot and melted at the focus of a laser. This produces a millimeter-sized sample of the new alloy. An automated analysis system measures the chemical, physical and mechanical properties and feeds them into a virtual alloy database. 

The AI system can now analyze patterns and make the connection between properties of the alloys and their chemical composition. Finally, the AI system recommends the new iterations. According to the Norwegian research institute Sintef, individual process steps are speeded up by a factor of 1000. In addition, less energy and material is needed to produce the alloys.

Examples like this show how AI can make an immense contribution on the path to rapid problem solving and resource conservation. AI helps get to the root of complex problems faster and more efficiently. This understanding is important. Because according to the Massachussetts Institute of Technology, we are running out of time.

To solve the urgent problems of our time, innovation must be speeded up by at least a factor of 10. 

It´s high time to improve innovation on many levels. We need to make knowledge readily available and evaluable. We need to better understand the reasons for problems in order to develop sustainable, effective solutions. We need unconventional concepts more quickly in order to achieve technological breakthroughs. 

To achieve all this, we want to take innovation to a new level. This is one of the reasons why we have developed the AI Planner ( It is intended to help as many people as possible to gain access to the effective use of artificial intelligence, and it is supposed to lower the barriers to dealing with this topic at all.

The AI Toolbook

A book from INDEED for decision-makers, innovators, and doers.

Michael Leitl

Michael Leitl

Innovation & AI Strategy

After studying chemistry, being a long-time editor at “Harvard Business Manager”, a member of the innovation team at “Der Spiegel” and more: Michael brings a wealth of knowledge to the team and our partners.

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