Riccardo Liguori The results emerging from the survey show a decrease in concerns related to legacy technologies and a strong interest in process optimization and risk reduction.
@Canva
Artificial Intelligence (AI) and Machine Learning (ML) are no longer seen as an impediment but opportunities. As per a new study headed by Eaton, an energy management focus Dublin-headquartered U.S.-based multinational company, companies are quickly changing their approach towards these technologies and accelerating their digitalization process.
The research, conducted by S&P Global Market Intelligence on behalf of Eaton, surveyed 1,381 business leaders across eight countries. The managers interviewed are actively involved in the digitalization processes of companies that work in strategic markets such as data centers, utilities, building management, and manufacturing. The results of the research were published in the second edition of the Eaton Brightlayer® Research Report, titled “Adoption, Execution, and Expansion in the Wake of AI.”
A shift in mindset at its core
One telling statistic illustrates the shift in mindset: only 23% of companies cite legacy tech as a holdback on digitalization. This is a huge reversal from 33% in 2022, a reduction of 10 points in less than two years. This shift reflects greater understanding of the transformational power of AI and ML.
Optimization and risk minimization: the business’s utmost concerns
What are the motivations to invest in these technologies? In the Eaton study, two main motivations are process optimization (51%) and risk reduction (49%). Companies are looking to streamline operations, enhance regulatory compliance, improve security, and protect data. Data security and privacy, however, remain a major concern for 40% of the respondents.
Eaton, in a statement underscored the extent to which companies have had to embrace digital technologies in order to achieve the full potential of AI and ML. The data center sector will be a key contributor to this transformation, as key infrastructure enabling AI adoption across industries from utilities to manufacturing. Digitalization is also seen as a way to meet decarbonization targets in accordance with regulation and the Net Zero 2050 target.
AI in all its guises: a changing landscape
The Eaton study also provides a snapshot of how different AI-based technologies are being used. 29% of the firms report that they are using or will use AI and ML for predictive purposes. In manufacturing, it rises to 43%, where machine learning is being used to automate production lines and optimize maintenance.
Generative AI, however, is either currently used or planned to be used by 26% of organizations, with no significant variations between industries. This technology, capable of potentially creating autonomous virtual agents, has the potential to be a powerful change driver when combined with AI/ML.
Computer vision is envisaged or implemented by 21% of respondents with relatively balanced uptake in various sectors. Within manufacturing, there are immediate applications in quality checking and sorting operations.
Sectors under the microscope: challenges and opportunities
The digitalization dynamics within four major sectors with specific challenges and opportunities were also analyzed by Eaton.
- Data centers: This market is concerned with expanding its capacity in order to address expanding demand, with most looking to upgrade facilities (42.3%), increase capacity (38.6%), and make better use of IT resources (32.8%).
- Utilities: Utilities are struggling with aging infrastructure (55%) and having to expand network capacity in the next 10 years, with up to 49% growth being estimated.
- Manufacturing: During the manufacturing process, AI is seen as a tool to drive decarbonization and ESG objectives (66%), improve energy efficiency (55%), and enable digital twin (68%) and predictive maintenance (64%).
- Building management: Building administrators are addressing digitalization to reach sustainability targets (46%), and the lion’s share of major property holders (54%) will install new management systems to optimize energy consumption. AI is also on the table as a method to predict space occupation (66%).
In this context, Eaton’s Brightlayer software is guaranteed as a way to optimize digitalization and increase operational efficiency, merging sector expertise with AI, ML, and big data.
