October 9, 2026 Why AI Fluency in Manufacturing Takes More Than Skills

How to blend hard and soft skills to strengthen AI in the industrial workplace.

By Bruno Szarf, Global Chief Human Resources Officer at Stefanini Group

Industrial manufacturing, like just about every other industry, knows that adopting a strategy of AI integration is an inevitability. If these companies want to maintain a competitive advantage and future-proof for the next ten or twenty years, optimization through AI is what is going to get them there – if they don’t overlook the need to blend hard and soft skills within the workforce.

Understanding soft versus hard skills in AI

When the C-suite is talking about what proper AI integration looks like, there tends to be an outsized focus on the hard skills needed for effective implementation. That’s not a surprise, with the World Economic Forum reporting that 63% of employers see a skills gap as a major barrier to business transformation. What models, training and data will drive the AI? What security or governance measures must be considered before deployment? These are all crucial and valid concerns. However, for industries like manufacturing that want to achieve true AI-fluency within their organizations, there are several key softer skills – or rather semi-firm skills that blend both hard and soft AI skills – that must be of equal importance.

While hard AI skills allow employees to focus on optimizing the work itself, redefining workflows and eventually, hopefully, increasing a business’ bottom line, soft AI skills allow employees to have a smoother experience within the organization and use AI to transform their teams for the better.

The most successful organizations will emphasize a blending of these skills to create a third set of capabilities, semi-firm skills. Think of this new category as what skills are needed to apply human judgement to AI.

As AI executes increasingly complex work and higher workloads, employees need maximum proficiency in skills like self-directed learning, critical thinking and practical judgements that can be applied to the technology that they’re being asked to use. 

Self-directed learning within AI training programs

Manufacturing organizations must create opportunities for self-directed learning when implementing AI, allowing employees to understand where they can expand their skillset on their own terms and determining what unique value they can bring to the workplace.

Skillsoft’s recent survey of 2,500 full-time employees across the US, UK, Germany and India reported that 35% of respondents lacked confidence that they had the skills required to succeed in their roles. This is especially concerning given 74% of the workers who said AI/ML represented their biggest skills gap rated their organization’s AI training programs as “average to poor.” If an organization’s training programs can’t keep up the needs of its employees being asked to utilize AI, there is a fundamental flaw in the entire system.

There must be clear opportunities for self-directed learning to fill these gaps, trusting employees to figure out how AI can positively impact their work and letting them drive what programs need to be prioritized within a manufacturing environment – one size won’t fit all. Manufacturing companies can look to Microsoft, for example, on how to structure self-directed learning programs within their organizations.

The company has been particularly forthcoming in how it’s helping employees develop AI skills in low pressure environments, including providing them with dedicated time just for self-directed learning and a depth of tools and experiences to choose from that fit their needs. Employees can access skills development by role, take a structured path if they want or simply tackle something of interest for both personal and professional growth.

Layering AI literacy & critical thinking on top of AI deployments

Many organizations are challenging senior leaders to use AI to reimagine the way they and their team members work. However, these are nuanced situations and it’s not nearly as simple as plugging those scenarios into AI and getting a fully formed answer as one wants to think it is. It’s essential that today’s manufacturing workforces are cultivating an environment that favors critical thinking alongside AI, instead of taking a generated answer at face value.

Deloitte’s survey of UK consumers found that 11 million people had tried generative AI for work, with 40% of them believing it always provides an accurate response. That is an alarming number of potential employees within organizations right now that are not thinking beyond a linear AI experience. They are asking generative AI a question and making a decision based on that response alone. Think about the implications of that kind of limited thinking for something like drug manufacturing.

Companies like J&J have reported more than 56,000 workers have taken a generative AI training course, something that is required before an employee is authorized to even use it. Merck & Co. launched its internal AI initiative, GPTeal, to bring generative AI into its pharma R&D processes.

Through its interface, Merck researchers can interact with advanced AI models like ChatGPT or Claude. This has the potential to streamline some of the most time-consuming tasks needed when bringing a new drug to market. In Merck’s case, the platform was developed with oversight by medical writers and started being used simply to draft emails and memos before the company scaled it up to tasks like first drafts of clinical study reports.

Given the sheer amount of documentation needed in drug manufacturing at these types of organizations, it’s no surprise seeing them take a coordinated approach to ensure generative AI isn’t being incorporated without the added education on applying critical thinking to the prompt and response actions.

Practical judgement & empowered decision making in the moment

At the end of the day, if the manufacturing industry wants to see a bottom-line impact from investing in AI, it has to empower the actual people using AI and help them to make practical judgements in the moment – not every question can be plugged into an LLM and produce an answer. On the manufacturing floor, workers may need AI to tell them everything from the temperature of a machine to its latest inspection date to make a judgement call at a moment’s notice. It’s on the organization to ensure those touch points are being properly collected and reported by AI.

For example, Bosch’s Shopfloor Agent is an agentic AI software that helps to restart production facilities more quickly after breakdowns. The AI was built in part to help preserve crucial historical operation information that was dispersed across channels, including sometimes just in a long-term employee’s head. With the agentic AI, documents, errors, sources and solutions are all stored and used by employees to solve problems and get production back on track.

AI has the potential to accelerate the pace of transformation within the manufacturing industry dramatically. But, regardless of the size of an organization, if the rollout is done with a focus on hard skills only then the potential impact on the bottom line will never be realized. Employees will be quick to give up trying to learn new skills and crucial errors that require human intervention will be overlooked. With emphasis on semi-firm skills like self-directed learning, AI literacy and critical thinking and practical problem solving, manufacturers can future-proof their business for the AI-era.

About the Author:
Bruno Szarf is the Global Chief Human Resources Officer at Stefanini Group, leading the company’s human resources, finance, transformation, marketing and performance areas. Bruno has helped to spearhead Stefanini Group’s introduction of AI into HR functions like recruiting, as well as initiatives designed to accelerate internal adoption of AI and reduce the knowledge gap between teams. Bruno began his career as an electrical engineer before moving into HR in 2016 after being recognized for his knack in connecting strategy, operations and people management. Bruno was recognized by Forbes as one of the best CHROs in Brazil in 2026.

Subscribe to Industry Today