A new study by GlobalLogic, a Hitachi Group company, in partnership with HFS Research, reveals a widening divide between industrial enterprises’ ambitions and their real-world readiness for AI, sustainability, and workforce transformation. Despite strong executive push towards modernization, skills shortages, legacy systems, and misaligned priorities continue to stall progress across key industrial segments.
Released today, the research draws insights from more than 100 senior leaders from billion-dollar enterprises across automotive, aerospace, chemicals, energy and utilities, and construction. The findings lay bare the scale of transition ahead: while industries recognize AI and sustainability as foundational for future competitiveness, a lack of talent and weak integration strategies are slowing measurable impact.
“Industrial leaders see AI, sustainability, and talent as top priorities, yet struggle to convert these ambitions into tangible results,” said Srini Shankar, President and CEO at GlobalLogic. “Many are deploying advanced technologies without the necessary skills, governance frameworks, or transition models that connect today’s efficiency pressures with tomorrow’s strategic goals.”
Shankar noted that as onshoring accelerates in the US, demand for high-end industrial capabilities is rising sharply — but specialized talent remains scarce and costly. In this environment, enterprises are increasingly turning to AI-driven ecosystems, using automation, embedded systems, edge intelligence, and next-generation connectivity to modernize operations. GlobalLogic, backed by Hitachi’s expertise in operational technologies and industrial products, is working with clients to advance “Physical AI” journeys, enabling capabilities such as servitization, digital twins, automation, predictive maintenance, and frontline worker augmentation.
A sector caught between ambition and capability
The study highlights a set of structural challenges that hinder industrial modernization:
• Skills shortages are worsening.
A majority (51%) of enterprises say talent gaps are the top reason AI and advanced tech initiatives fail. Yet many lack structured upskilling programs, while nearly half struggle to source digital and AI skills. With experienced workers retiring and fewer new entrants choosing industrial careers, the talent gap is widening.
• Legacy systems are blocking transformation.
Nearly half (49%) of respondents said integrating new technologies with decades-old systems is their biggest barrier. Technical debt is preventing industrial companies from adopting more intelligent, connected operating models needed for agentic AI and real-time decision-making.
• Priorities are shifting toward AI.
Although operational cost reduction is the top priority today, the study finds that within two years, AI adoption and operational optimization will dominate executive focus. The industrial sector is preparing for a shift from incremental improvements to deep automation and intelligence-led models.
• Perceptions of the sector are hurting talent pipelines.
Over 58% of leaders believe industrial careers are perceived as having limited mobility, while nearly half say the sector lacks an innovative image and struggles to match compensation standards of adjacent industries — a combination that intensifies the talent crisis.
“Enterprises need to embed sustainability, talent, and technology transitions into both strategy and day-to-day operations,” said Josh Matthews, HFS Research. “Clear outcomes and messaging are essential to show current and future workforces that industrial organizations are shaping — not chasing — the sustainable, tech-driven future.”
Recommendations for the next phase of industrial reinvention
The report outlines strategic actions to help enterprises overcome persistent roadblocks and accelerate transformation:
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Build integrated transformation roadmaps that link short-term operational efficiency with long-term strategic goals.
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Prioritize talent development, human-AI collaboration frameworks, and continuous upskilling.
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Modernize system architectures instead of patching legacy infrastructure.
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Create transparent metrics and career pathways that highlight the sector’s innovation trajectory.
The bottom line
Industrial enterprises sit at a critical inflection point. The pressures of sustainability, workforce evolution, and AI adoption are not slowing — and leaders must find ways to run operations efficiently while simultaneously reinventing the business. The companies that build the structures to execute both tracks in parallel will define the next era of industrial competitiveness.
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