Onofrio Pirrotta is a senior vice president and managing partner at Kyndryl and leads the US manufacturing and energy market for technology companies. The opinion is by the author himself.
Artificial intelligence is no longer a futuristic concept for manufacturers. From predictive maintenance to intelligent automation, it is embedded in operations.
According to Kyndryl's People Readiness Report95% of manufacturing organizations already use AI in various areas of their business. However, despite this widespread adoption, a significant gap remains. 71% of manufacturers said the workforce is not ready to effectively utilize AI.
This cutting between technology investment and workforce preparation is more than growing pains, a strategic risk. If not addressed, it could halt innovation, limit return on investment, and widen the competitive gap between AI pacesetters and those who are still struggling to keep people aligned with progress.
Preparation paradox
The manufacturing sector is undergoing deep transformation. AI, edge computing and digital twins rebuild factory floors, enabling real-time decision-making and operational agility.
So why do 14% of the manufacturing organizations surveyed incorporate AI into their customer-facing products and services?
The answer lies in the “preparation paradox.” Manufacturers are investing in AI tools and platforms, but not in the people who use them. As a result, employees are wary of the impact on AI's roles, and many leaders don't know how to guide their teams through the transition. More than half of manufacturers cite a lack of skilled talent for managing AI, and fear of job movements has influenced employee engagement. The result is a labour that is technically surrounded but not actually ready.
AI Pacesetters do things differently
Paceset companies, which account for just 14% of the business and technology leaders in the eight markets surveyed, coordinate their employees, technology and growth strategies. They see measurable benefits in productivity, innovation and employee engagement by using AI using the following approach:
- Strategic Change Management: Just over 60% are likely to have implemented an overall AI adoption strategy and have a change management plan. They treat AI as a major, well-supported transformation, rather than a quick fix.
- Trust building measures: Employees are more likely to accept AI if they are involved in implementing it and developing ethical guidelines. It is also important to maintain transparency around AI goals.
- Active Skill Development: Pacesetters invest in upskills, mentorship and external accreditation, and are more likely to stock up on current skills and implement tools to identify gaps. This provides a clearer roadmap for workforce development and a head start for future preparation.
Best Practices
So how can manufacturers bridge the AI skill gap and coordinate innovation with workforce development by adding pacesetter ranks?
Make workforce preparation a priority in meeting rooms
AI strategies should not live exclusively in the IT department. This should be a sensual initiative that includes HR, manipulation, and C suite.
However, studies show amputation. CEOs are 28% more likely than top technicians to say that an organization is in the early stages of AI implementation and are more likely to support opening up current employees and hiring external talent. This inconsistency slows progress.
Manufacturers need unified leadership around a shared vision of AI and workforce transformation.
Establishing a cross-functional AI steering committee that includes frontline supervisors also ensures alignment between technology and talent strategies. Connecting AI preparation to business KPIs such as productivity, quality and innovation metrics and conducting regular workforce capabilities audits is even more important by predicting strategic planning and future needs based on the AI roadmap.
Build a culture of trust and transparency
Fear is a powerful inhibitor. When employees worry that AI will replace them, they are less likely to be involved in it. Leaders need to address these concerns directly. It means that employees are involved in the pilot program and openly communicate how AI is used, showing how it can be augmented rather than replacing its role.
By implementing layered AI education programs, launching employee enablement campaigns and providing access to AI-powered tools, it will help bring a workforce of manufacturers along the AI journey. Like the frontline, hosting AI town halls where employees in the supervisory role can ask questions and share their concerns is another way of building engagement. Worker trust can also be strengthened through the development of internal AI ethics policies and governance committees.
Invest in scalable, personalized learning
Training programs need to evolve with technology. The traditional, one-size fit approach doesn't cut it. Manufacturers should provide modular, role-specific learning paths, including hands-on experiences of AI tools, especially during onboarding and job changes. Partnering with external experts and providing certifications can also increase your reliability and motivation. Soft skills prioritization is also important. As AI takes over routine tasks, human skills such as critical thinking, adaptability, and collaboration become even more valuable.
Looking ahead
The future of manufacturing is intelligent, connected and moving fast. But technology alone doesn't allow us to get there. We need people ready, willing and capable of harnessing that power.
To align AI innovation with workforce development, manufacturers can unlock new levels of productivity, creativity and resilience. They can turn the preparation paradox into the preparation benefits. Success in the age of AI belongs to people who place people at the heart of transformation.
