In this article
- HPE surveyed members of various industrial verticals to learn what effect AI has in the industrial sector today and is expected to have by 2030
- AI is a key component of the 4th industrial revolution, driving the transition from automation to autonomy
- Of 858 respondents, 61% stated that they were already engaged with AI
- Companies expect AI to grow revenues by 11.6% while simultaneously increasing margins by 10.4%
The fourth industrial revolution is firmly upon us and it is one that will provide customers with a greater range of customized products and a better service experience, while allowing manufacturers to transition towards predictive and adaptive processes and machinery. Artificial intelligence (AI) is not a peripheral component of this industry change; it is at the heart of the fourth industrial revolution, a key enabler to take the step from automation to autonomy, creating growth and competitive advantage.
Together with Industry of Things World, Europe’s leading Industrial IoT conference, HPE surveyed 858 predominantly European professionals and executives from various industrial verticals to find out what effect AI has in the industrial sector today and is expected to have by 2030. Their responses show that the European industrial sector has clearly understood and embraced the strategic power of AI—but it also reveals that there are some key challenges that have to be overcome to fully unleash its potential.
Let’s start with the really good news. European industrial companies expect AI to cut costs by improving efficiencies while at the same time increasing revenue streams and improving differentiation through new products and customization. In fact, on average, respondents expect to grow their revenues 11.6 percent by 2030 as a result of AI adoption, while simultaneously increasing margins by 10.4 percent.
This expectation is also fueled by the high success rates of completed AI projects: 95 percent of respondents that have implemented AI in their company say they achieved, overachieved or significantly over-achieved their goals. Accordingly, survey participants plan to invest an average of 0.48 percent of their revenue in AI in the next 12 months—a significant amount considering that the average overall IT budget is 1.95 percent of revenue in the manufacturing industry.
In line with this positive outlook, two thirds of respondents expect that new jobs created by AI will balance or outweigh the number of jobs made redundant by AI.
With all the optimism, it could appear a little underwhelming that ‘only’ 11% of those surveyed have actually implemented an AI solution to date, even in proof-of-concept form. But that number needs two very strong caveats attached to it: firstly, we are talking about an emerging technology, so the pick-up rate is actually quite high; secondly, when we add in the 50% of respondents who are actively considering AI solutions or even planning to roll out in the next 12 months, we reach a staggering 61% who are engaged in AI.
The reasons these companies are attracted to AI also show a matured understanding of the benefits. It’s not just cost cutting that is driving interest in AI. While the goal “increasing efficiency in operations, maintenance and supply chain” received most votes (57 percent), many respondents also pursue goals like “improve customer experience” (45), “enhance products and services by adding new features” (41) and “quickly and automatically adapt to changing conditions” (37). Fast, efficient manufacturing is important, but it can be improved measurably by applying AI to increase the flexibility of industrial processes and better serve customers with customized products and value-added services identified through trends in mass data.
The results clearly show that industrial companies in Europe understand the value and importance of AI technologies, but there are still stumbling blocks that stop companies from scaling AI adoption across the value chain. Data is the main issue for many businesses, with 47% stating that “lack of data quantity and quality to feed AI models” was a problem and 34% citing “lack of data governance and enterprise data architecture” as key challenge for AI adoption. Industrial companies realize that their AI solution can only be as good as the information it is fed. That means setting up data-capturing infrastructure, along data governance and architecture, to provide plenty of standardized, labelled, clean data and give an AI the best chance of bringing business value.
Another key challenge for broad AI adoption is the “lack of AI/analytics skills and knowledge” (42 percent). To overcome this, the majority (55 percent) of respondents employ a mix of internal and external expertise. A third primarily focus on building internal expertise by hiring from outside the company, and by training and developing their own employees, while 12 percent primarily focus on sourcing external AI experts. HPE offers guided transformation services to companies looking to AI solutions, including the HPE Artificial Intelligence Transformation Workshop that helps customers get started with AI, evolve their strategic data and analytics initiatives and prioritize AI use cases.
In general, the survey paints a very positive picture of the attitude towards AI in European industry. However, there are no shortcuts when it comes to implementing AI in the industrial enterprise to create competitive advantage. Firms must define their AI strategy, identify promising use cases, source the data, buy and build technologies, and put the right people and processes in place. But, as the survey proves, the businesses that take that journey are seeing the results they hoped for—or even better. And other businesses are taking note and are getting ready to follow suit.
858 respondents (managers, directors, C-suite executives) from verticals including manufacturing, IT, transportation, chemicals, energy and consumer products participated in the survey “The Present and Future of AI in the Industrial Sector” via an online questionnaire between August 1 and September 20, 2018. 61 percent of respondents were based in Western Europe, 22 percent in Central/Eastern Europe, 7 percent in North America, 5 percent in Asia/Pacific, 3 percent in South America, and 1 percent in the Middle East and Africa.