A research produced by
Self-learning machines are the essence of artificial intelligence (AI). While concepts already date back more than 50 years, only recently have technological advances enabled successful implementation at industrial scale. According to the McKinsey Global Institute (MGI), at least 30% of activities in 62% of German occupations can be automated, which is at a similar level as the US2. Freed-up capacity can and needs to be put to new use in value-adding activities to support the health of Germany’s economy. AI has proven to be the core enabler of this automation based on advances in such fields as natural language processing or visual object recognition.
Highly developed economies, like Germany, with a high GDP per capita and challenges such as a quickly aging population will increasingly need to rely on automation based on AI to achieve its GDP targets. About one-third of Germany’s GDP aspiration for 2030 depends on productivity gains. Automation fueled by AI is one of the most significant sources of productivity. By becoming one of the earliest adopters of AI, Germany could even exceed its 2030 GDP target by 4%3. However, if the country adopts AI more slowly – and productivity is not increased by any other means – it could lag behind its 2030 GDP target by up to one-third.
AI is expected to lift performance across all industries and especially in those with a high share of predictable tasks such as Germany’s industrial sector. AI-enabled work could raise productivity in Germany by 0.8 to 1.4% annually.
We selected eight use cases covering three essential business areas, (products and services, manufacturing operations, and business processes) to highlight AI’s great potential in the industrial sector.
Source : McKinsey Global Institute
