Industrial firms face AI growth drag from talent gaps

Industrial companies are struggling to scale artificial intelligence and digital initiatives because of talent shortages, legacy technology and misaligned priorities, according to new research from GlobalLogic and HFS Research.

The study finds that skills gaps and outdated systems are holding back growth and sustainability goals in sectors such as automotive, aerospace, chemicals, energy and utilities, and construction.

Researchers surveyed more than 100 C-level and senior executives at industrial firms with annual revenues above USD $1 billion. Respondents described a widening gap between leadership ambitions and the practical ability to deliver AI, sustainability and workforce transformation at scale.

Across the sample, 51% of organisations say skills gaps are the main reason AI and other advanced technology projects fail or underperform. Many executives report a lack of structured training and difficulty in hiring people with digital and AI expertise.

Nearly 70% of industrial leaders see AI talent shortages as their biggest growth barrier. Respondents also point to rising hiring costs and competition for specialist roles.

“We undertook this research to understand why industrial leaders see AI, sustainability, and talent as top priorities yet struggle to turn them into measurable results,” said Srini Shankar, President and CEO at GlobalLogic. “We found many are trying to deploy advanced technologies without the talent, the clear AI governance frameworks, and without transition plans that link today's efficiency pressures to tomorrow's strategic goals. As onshoring accelerates in the United States, leaders face rising domestic demand but scarce and costly specialised talent.

At GlobalLogic, we're moving beyond experimentation to deliver AI-driven industrial ecosystems that create measurable value today. By combining our deep heritage in embedded systems, Edge AI, IT-OT convergence, OT cybersecurity, Industrial IoT, and next-generation connectivity, such as 5G/6G, GlobalLogic delivers the core capabilities industrial clients need to advance their Physical AI journeys. When combined with Hitachi's proven OT and product excellence, we are empowering organisations to modernise faster, operate smarter, and accelerate their transformation across sustainability, productivity, and talent. Together with our industrial clients, we are advancing next-generation capabilities in servitization, digital twins, industrial automation, predictive maintenance, and frontline worker productivity and safety-helping them unlock new revenue models while driving meaningful gains in operational efficiency and performance."

The report highlights a growing reliance on existing staff because of shortages of specialist AI and digital workers. It notes that 51% of companies say skills gaps hinder AI and advanced technology initiatives, yet half of respondents lack structured upskilling programmes.

In addition, 42% of executives say they struggle to find digital and AI talent. Many firms face an ageing workforce and fewer new candidates entering traditional industrial roles.

The study identifies legacy systems as a major obstacle for industrial transformation. These systems create technical debt and limit the deployment of newer connected and intelligent operating models.

Nearly half of respondents, 49%, say integrating new technologies with legacy systems is their greatest barrier when they deploy advanced digital tools. Many companies continue to run core operations on ageing platforms that are difficult to modernise.

The report states that this integration challenge reduces the value of AI and automation investments. It also absorbs budgets that might otherwise support new digital solutions.

Researchers note that some firms are moving away from patching legacy infrastructure. These firms are investing in modern systems that can support new operating models such as agentic AI and wider industrial automation.

The survey also tracks changing priorities among industrial leaders. At present, 46% of executives put reducing operational costs in their top three concerns.

Respondents expect this focus to shift during the next two years. They predict that AI adoption and operational optimisation will move into the top position in priority lists.

The report links this change to growing expectations around data-driven decision making and predictive maintenance. It notes that firms are looking for ways to standardise AI use across plants and business units.

The research finds a deepening image problem for industrial employers. 58% of executives believe potential recruits see limited career mobility in manufacturing.

Almost half, 48%, think the sector suffers from a perception of low innovation. A further 46% acknowledge that their organisations underpay compared with other industries.

These perceptions feed the talent shortage that affects AI and digital initiatives. They also create risks for long-term operational resilience as experienced workers retire.

HFS Research says companies need clearer narratives about the role of industrial work in a digital and low-carbon future.

“Industry executives must immediately embed their sustainability, talent, and technology transitions in both strategy and daily operations,” said Josh Matthews, HFS Research. “Clear outcomes and messaging must show the current and future workforce that an enterprise is part of the sustainable and technology-based future, not reacting to those who lead it.”

The study notes that enterprises that integrate sustainability into their technology strategies are twice as likely to scale new solutions. It states that these companies link climate targets, workforce plans and AI investments under shared metrics.

Researchers set out several recommendations for industrial organisations. They call for integrated plans that connect short-term efficiency measures with long-term growth strategies.

The report urges immediate investment in talent development and human-AI working models. It also highlights the need to modernise systems in ways that support new operating models instead of layering more tools on legacy platforms.

It recommends clear performance indicators and defined career paths to show that industrial roles offer progression in digital and sustainable business. It states that firms that balance day-to-day operational demands with structured transformation programmes are more likely to succeed at scale.