Industrial companies expect to grow in the coming years mainly through artificial intelligence (AI). AI offers them opportunities for greater efficiency, flexibility and differentiation. This is according to research among 858 industrial sector professionals and executives conducted by Hewlett Packard Enterprise (HPE) and Industry of Things World, Europe's largest industrial IoT conference. Inadequate quantitative and qualitative data, as well as a lack of AI expertise, are seen as the biggest challenges to further AI adoption, according to Executive People.
European industrial companies surveyed expect AI to reduce costs while providing more sales and improving differentiation through new products and customisation. On average, those surveyed think that AI will grow sales by 11.6 per cent and reduce margins by 10.4 per cent.
This expectation stems partly from the successes entrepreneurs have already achieved through artificial intelligence. As many as 95 per cent of those surveyed said they have achieved their goals much faster through artificial intelligence. Most underwriters plan to invest 0.48 per cent of their turnover in AI over the next 12 months. That's a lot when you consider that the average overall budget for IT is 1.95 per cent in the manufacturing industry.
Benefits
With all this optimism, it is somewhat disappointing that 'only' 11% of those surveyed have implemented an AI solution to date, even in the form of a proof-of-concept. But that number needs two very strong caveats, according to the researchers: first, we are talking about an emerging technology, so taking that into account, it is being picked up pretty quickly. Secondly, if we include the 50 per cent of respondents who are currently actively considering or even already planning AI solutions, we arrive at 61 per cent of companies that have implemented AI.
The reasons companies are interested in AI also show a growing understanding of the benefits of AI. This is not just about cost savings. Entrepreneurs also consider it important to improve the customer experience, enrich products and services by adding new features and adapt quickly and automatically to changing circumstances.
Doubts
However, there are still plenty of reasons why industrial companies are hesitant about scaling up AI in their value chain. Data is the main stumbling block. Many entrepreneurs cite a lack of data and quality to fill AI models. Industry companies realise that their AI solutions can only be as good as the information given to them. This means that a full data infrastructure often needs to be set up in addition to AI. Many entrepreneurs (42 per cent) also fear that their company lacks analytical knowledge and skills.
In short, there is positive thinking when it comes to implementing AI, but most companies still need quite a few steps to implement good AI solutions. "Artificial intelligence is at the heart of the fourth industrial revolution. It is a key element in moving from automation to autonomy, but also in creating growth and competitive advantage," Volkhard Bregulla, Vice President Global Manufacturing, Automotive and IoT at HPE told Executive People. "Our research shows that the European manufacturing sector has understood and embraced the strategic power of AI, but also shows the essence of closing the gap between data and skills to unleash its full potential."
Executive People also wrote up some other key findings from the survey:
- The use cases in which respondents use AI are spread across the entire value chain, including research and development (38 per cent), demand forecasting (21 per cent), production planning (18 per cent), operations (32 per cent), maintenance (34 per cent), sales (20 per cent) and services (29 per cent).
- Core goals of AI implementations include increasing efficiency in operations, maintenance and value chains (57 per cent), improving customer experience (45 per cent), improving products and services by adding new features (41 per cent), adapting quickly and automatically to changing conditions (37 per cent), creating new business models (34 per cent) and better matching supply and demand with improved forecasting and planning (32 per cent).
- Research findings suggest hybrid AI architectures will become norm in the coming years. By 2030, 55 per cent of deployments are expected to use data centres and/or cloud, while 52 per cent will be via 'the edge'.
Source: HPE/Executive People
Photo: Unsplash/Kevin Ku.
