Eaton: How New Tech is Impacting Digitalisation Efforts

The latest global study from Eaton shatters long-held assumptions about the relationship between legacy infrastructure and innovation, revealing a remarkable shift in how organisations are navigating their journey toward AI and ML adoption.

This transformation comes at an important juncture in the global technology environment.

For decades, legacy systems have been viewed as the primary obstacle to digital modernisation, particularly in industries heavily dependent on established infrastructure.

However, the study reveals a reversal of this narrative, with only 23% of companies now citing legacy technology as a barrier to digitalisation – a significant drop from 33% just two years ago.

The timing of this shift is particularly significant given the convergence of several major technological and environmental imperatives.

As organisations face mounting pressure to achieve ambitious sustainability targets, optimise operations and leverage the transformative potential of AI and ML, the diminishing impact of legacy constraints represents a crucial turning point in their ability to embrace innovation.

Legacy technology no longer a major hurdle

Eaton indicates that fewer companies now view legacy technology as a barrier to digitalisation.

This 10% decrease of surveyed companies cited legacy technology as an obstacle in less than two years suggests a growing openness to embracing new digital tools, particularly AI and ML applications.

The study emerges against a backdrop of unprecedented investment in digital infrastructure, particularly in the data centre sector, which stands at the forefront of enabling AI initiatives across industries.

Digital infrastructure investment in data centres

Data centres stand at the forefront of enabling AI initiatives across industries.

“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”, Mark Roces, Vice-President of Digital Offer Management at Eaton says.

This surge in capability and capacity isn't just about technological advancement – it represents a fundamental shift in how organisations view their digital future, with legacy systems increasingly seen not as barriers but as foundations for innovation.

This evolution in perspective coincides with a growing recognition of AI and ML's potential to address critical business and environmental challenges.

As Mark points out: “This research shows how urgently businesses want to implement digital technologies that deliver the benefits of AI and ML.”

From manufacturers leveraging AI for decarbonisation efforts to utilities preparing for massive grid capacity expansion, Eaton reveals a business landscape where digital transformation has moved from aspiration to imperative and where legacy technology is no longer standing in the way.

Sector-specific findings and AI applications

Eaton also provides insights into how different sectors are approaching digital transformation and AI adoption:

Data centres

Data centres are focusing on facility upgrades (42.3%), capacity expansion (38.6%) and improving IT asset performance utilisation (32.8%).

These efforts are aimed at meeting the growing demand for AI-powered services.

Utilities

In the utilities sector, 55% of respondents identified outdated infrastructure as their biggest challenge.
However, 40% anticipate significant increases in grid capacity requirements over the next decade, with predictions of up to 49% additional capacity needed.

Manufacturing

Manufacturers also see potential in AI for various applications. 
According to the study, 66% believe AI could aid in decarbonisation efforts and improve their environmental, social and governance (ESG) scores.
Additionally, 55% see opportunities for AI in electrical energy monitoring and optimisation, while 68% and 64% respectively anticipate benefits in digital twin technology and predictive maintenance.

Construction

Furthermore, building operators are leveraging digital transformation to achieve sustainability targets, with over 46% focusing on this area.
The study reveals that 54% of large building owners plan to install building management systems within the next year to optimise energy use and that 66% view AI as a future tool for predicting space utilisation.

The digital toolbox expands

Technologies and tools organisations use to implement digital transformation are also evolving and expanding quickly.

Cloud and cybersecurity

Cloud and cybersecurity deployment have grown the most over the past two years, cementing these two critical technologies as lynchpins of digital transformation.

AI and ML

The study found that AI/ML Predictive is most in-use, in deployment, or planned for use by 29% of respondents.
The manufacturing sector leads in this area, with 43% of respondents deploying the technology.

Gen AI

Gen AI is in deployment or planned by 26% of respondents, deployed in relatively equal measures across the four sectors surveyed.
This technology has the potential to be an even bigger change-agent when coupled with AI/ML, building agents that can act autonomously with intelligence.

Computer vision

Computer vision is also planned or deployed by 21% of respondents, with applications across various sectors, particularly in manufacturing for sorting and quality control operations.

Eaton's Brightlayer software

Finally, Eaton's Brightlayer software aims to facilitate this digital transformation by combining the company's domain expertise with AI, ML and big data processing capabilities.
This integration supports real-time decision-making for optimised power management across various industries.

“This research shows how urgently businesses want to implement digital technologies that deliver the benefits of AI and ML”, Mark concludes.

“Digitalisation will also help these sectors deliver on the decarbonisation strategies required by regulations, many of which have been introduced in support of the UN’s 2050 net zero target.”

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