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KNOWLEDGE HUB

A study by the Capgemini Research Institute claims that in Europe, 51% of top global manufacturers use at least one element of Artificial Intelligence (AI) within their operations. While China and America currently lead the world in AI research, it is actually Europe that is leading the implementation process, particularly in the manufacturing sector.

According to the CapGemini, report, ‘Scaling AI in manufacturing operations: A practitioners’ perspective’, 51% of European manufacturers utilise AI, with Germany emerging as the pioneer in this practice as 69% of German manufacturing firms were found to have implemented AI practices in their factories. This number is far ahead of the next closest countries – France and the UK – where 47% and 33% of manufacturers respectively, use AI in their operations.

Supporting this finding, an Oxford Insights Government Artificial Intelligence Readiness Index 2019 which examines the AI efforts of 194 countries’ progress in AI activities relating to governance; infrastructure and data; skills and education; and government and public services – identified Germany as among the leaders of AI implementation. As such, the study gave Germany an ‘AI readiness index’ of 8.81, ranking it third behind Singapore and the UK. Germany was also found to be one of the top three producers of published AI research papers and AI patents between 2015 and 2018.

AI technologies are forecast to add $15 trillion to the global economy by 2030, and AI applications within the manufacturing sector are likely to become a key driver in achieving this figure. For manufacturers, AI can help to reduce operating costs, enhance quality, and improve marketing attribution and supply chain analysis by facilitating more efficient utilisation of the reams of data each factory generates.

Indeed, according to analysis by Industry Week, AI could enable up to 20% cost savings for manufacturers using AI to streamline predictive maintenance methods and 20% savings in materials using improved production yield analytics. AI can also enhance R&D by significantly speeding up the research process. For example, it was found that using AI to develop new metal-glass hybrids was up to 200 times faster than testing the technology without using it.

Such is the potential of AI in manufacturing that according to McKinsey, AI-enabled work could raise productivity in Germany alone, by 0.8 to 1.4% annually. This is crucial as Germany is a prime example of an advanced economy with a rapidly aging population that is forcing systematic change of industry.

In just a few decades, Germany will simply not have enough workers to maintain GDP projections per capita without productivity gains through automation and therefore, AI can provide the productivity boost required to achieve, or even overachieve, Germany’s productivity target. Indeed, the country is currently on a trajectory to exceed its 2030 GDP aspiration by 4% due to its emerging position as an early adopter of AI technology. However, if the country adopts AI more slowly, it could lag behind this target by up to one-third.

Germany’s 2018 AI strategy, jointly developed by the Federal Ministry of Education and Research, the Federal Ministry for Economic Affairs and Energy, and the Federal Ministry of Labour and Social Affairs was a clear signal about how seriously the Federal Government takes the potential of AI and its ambitions to ensure Germany is leading the way. The government have ear-marked $3bn of investment available for AI research and development initiatives and progress is beginning to be made.

The potential of AI and accompanying technologies will only be realised if manufacturers focus their efforts on AI solutions that can be driven to scale, and the creation of a robust data governance framework that protects the generation, management, and analysis of data.

The impact of AI will change how we make and produce goods, globally, but there will be some countries that define this shift. Germany, for example, is becoming increasingly important in the AI ‘arms race’, because whilst the US and China dominate the sector, it is those that are hot on their heels that are forcing change to governance standards, scalability and driving costs down to improve the inclusivity of AI technology all around the world.

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