Eaton Study: Legacy Tech No Longer Blocking Digital Progress
Legacy infrastructure constraints are no longer the primary obstacle to digital transformation, according to research from Eaton, the power management solutions provider.
Significantly, the percentage of companies citing legacy technology as a barrier to digitalisation has decreased from 33% to 23% over the past two years.
“This research shows how urgently businesses want to implement digital technologies that deliver the benefits of AI and ML.”
Such a stark shift comes as data centres expand their infrastructure to support artificial intelligence and machine learning (AI/ML) initiatives across multiple sectors. These technologies use computer systems to perform tasks that typically require human intelligence, such as pattern recognition and decision making.
Data centres leading in digital transformation
The research from Eaton indicates that 42.3% of data centre operators are upgrading facilities, while 38.6% are expanding capacity. Additionally, a further 32.8% are focusing on improving the utilisation of IT assets - the servers, storage and networking equipment that form the foundation of their operations.
"The data centre sector is clearly going to be instrumental in this shift because the utility, commercial building and manufacturing sectors will depend on data centres to underpin their AI journeys," says Mark Roces, Vice-President of Digital Offer Management at Eaton.
The timing of this transformation coincides with pressure on organisations to meet sustainability targets while optimising operations. In particular, the manufacturing sector demonstrates this dual focus, with 66% of manufacturers identifying AI as a tool for decarbonisation efforts and improving environmental, social and governance scores.
Sector-specific technology transformation
Cloud computing - the delivery of computing services over the internet - and cybersecurity implementation have seen the most growth over the past two years. According to Eaton, 29% of organisations are using or planning to implement predictive AI and ML systems, which use historical data to forecast future events.
- Only 23% of companies now view legacy technology as a barrier to digitalisation, down from 33% in 2022
- Data centres are focusing on facility upgrades (42.3%), capacity expansion (38.6%) and improving IT asset performance utilisation (32.8%)
- 66% of manufacturers believe AI could aid decarbonisation efforts and improve ESG scores
- Cloud and cybersecurity deployment have grown the most over the past two years in digital transformation efforts
Within the manufacturing sector in particular, 43% of companies are deploying these predictive technologies. The sector sees opportunities for AI in electrical energy monitoring and optimisation, with 55% of manufacturers planning implementation in these areas.
Alternatively, digital twin technology, which creates virtual replicas of physical systems, in addition to predictive maintenance, are expected to benefit 68% and 64% of manufacturers respectively.
Generative AI (Gen AI), is also being deployed or planned by 26% of respondents across all sectors surveyed. Similarly, computer vision technology is planned or deployed by 21% of respondents. Designed to enable machines to interpret visual information, this technology has applications in manufacturing for quality control operations.
Supporting sustainability goals with infrastructure
Eaton also reveals that utilities face particular challenges, with 55% identifying outdated infrastructure as their main concern. These findings come at the same time as the data centre sector in particular anticipating grid capacity requirements to increase by up to 49% over the next decade.
In order to stay ahead and not put too much pressure on the grid, operators are starting to incorporate digital transformation into their sustainability strategies more frequently. According to Eaton, 46% are focusing on this area, which aligns with broader industry trends towards environmental responsibility and operational efficiency.
Eaton is also working on its own capabilities to support greater digital transformation. The company’s Brightlayer software platform combines a range of AI, machine learning and data processing technologies with power management expertise to support decision-making across industries.
This integration supports real-time decision-making for optimised power management across a broad range of industries.
"This research shows how urgently businesses want to implement digital technologies that deliver the benefits of AI and ML," Mark notes.
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