TRAINING & SKILLS
intuitive assistant. Manufacturers can use GenAI tools to query databases and get support using natural language, which is helping to reduce the barrier to entry and speed up AI adoption amongst the workforce. Manufacturers can apply personal AI experiences, such as prompting image generators or using chatbots, to industrial settings. This invites creativity by enabling workers to co-create solutions with AI and explore "what-if" scenarios in real-time. Manufacturing workers can use GenAI on the factory floor to test out new production approaches or workflows.
THE AGE OF THE SUPERAGENCY D
espite substantial growth in recent years, the manufacturing industry is amid a skills crisis. According to Make UK’s latest research, over a third of vacancies in manufacturing are proving hard-to-fill as applicants lack the appropriate skills, qualifications, or experience. This is 10% higher than the average rate across all other industries. But a new wave of industrial applications driven by GenAI technologies have the power to alleviate the industry’s chronic skills shortage, and attract the younger generation. So, are manufacturers ready to take the Industrial AI plunge and embrace the Age of Superagency between AI agents and human workers? Aging workforces, a lack of suitable apprenticeships, and waning interest from younger generations entering the job market has made filling open positions and keeping them filled a top concern for manufacturers. Against this backdrop, GenAI is already delivering substantial returns, estimated at 3.7 times the investment per dollar spent, and for top leaders that are using GenAI, the returns are even higher with an average ROI of £7.70. And there’s more. GenAI tools are also having a transformative effect on the existing manufacturing workforce. McKinsey in its “Superagency in the workplace” report, finds that 62% of millennial workers, between 35- to 44-years-old, report high levels of expertise with AI. We’re in the age of Superagency and it’s providing an opportunity the
manufacturing industry cannot afford to miss. At the moment, AI adoption in the manufacturing industry is still in the early-
30 JUNE 2025 | PROCESS & CONTROL THE AGE OF THE SUPERAGENCY
stages and varies widely depending on company size, culture, leadership mindset, and data quality. There’s a growing need for explainability and trust in GenAI, with manufacturers requiring intuitive tools and proof of ROI. So, where can manufacturers expect to see the biggest Industrial AI gains? 1) A knowledge transfer bridge for new and experienced workers
Manufacturing training, especially when onboarding new workers, can be a lengthy and resource-intensive process. But with GenAI technologies to hand, it doesn’t have to be. GenAI can capture tacit knowledge from experienced workers and turn it into digestible, digital formats that build up an organisation’s collective knowledge base. New workers can learn processes through intuitive bite-sized videos, interactive guides, and AI agents, all while on the factory floor. This readily available intelligence enables faster onboarding and reduces dependency on long apprenticeship programmes.
Where GenAI meets Gen Z Manufacturers that equip their workforce with familiar digital tools are also more likely to enhance engagement and improve productivity amongst digitally-native workers. Gen Z for example, largely prefer YouTube video tutorials over reading instruction manuals, so manufacturing technology that mirrors their digital experiences will help companies attract younger talent.
2) A democratising force for all, no coding required
AI is moving from being a specialist tool to an
3) Here’s the sweet spot – level up on the job with AI-enabled learning and development
Maggie Slowik and Andrew Burton, Global Industry Directors for Manufacturing at IFS, make the case for GenAI’s potential to accelerate skills training, elevate job responsibilities, and make the industry more attractive to Gen Z workers, changing how employees learn and work
To combat the ongoing skills gap, manufacturers need to prioritise reskilling existing workers and focus on in-house training initiatives. Connected worker tools such as Poka for instance, are making training interactive and personalised.
In fact, workers don’t even need to know they’re interacting with GenAI as it can be embedded seamlessly into their workflows. For instance, digital work instructions on tablets can provide a digital record of tasks completions and career progression based on what videos the worker has watched and what they’ve read. This helps supervisors see where employees might be struggling and require additional training. This approach also fosters more worker autonomy.
4) Say goodbye to pen pushing as AI does the heavy lifting
AI has the potential to elevate existing job roles by automating the routine and repetitive tasks such as quality checks and forecasting, also known as the 80/20 decisions. This not only shares the workload but also frees up time for manufacturers to focus on higher-value tasks that can foster creativity and encourage more worker initiative. As frontline manufacturers become more comfortable with AI, true human augmentation can become a reality through Agentic AI. Unlike GenAI, Agentic AI goes beyond output generation. It’s a goal-oriented, autonomously acting system that can make decisions, sequence tasks, and learn from feedback.
IFS
www.ifs.com
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