Beyond AI Adoption: Why Workforce Upskilling is the Real Competitive Advantage 

By Michael Wade and Amit Joshi 

A large insurance company planned to roll out AI tools for their employees, including models for churn reduction, customer service and risk management. However, a lack of consistent consistent training across users resulted in several of these systems gathering dust. In contrast, an Asian bank dedicated resources specifically to upskilling its entire workforce simultaneous with their AI rollout, leading to impressive gains in customer acquisition, retention and operational efficiency. 

As these examples demonstrate, assuming that employees will “figure out” AI on their own is proving to be a costly miscalculation. Instead, upskilling employees at scale is quickly becoming a must win battle for legacy organizations. But can this turn into an actual competitive advantage? 

Democratization of AI  

AI is not new. Indeed ‘traditional’ AI, more correctly Machine Learning, has been around for decades. Till recently though, there wasn’t much discussion of AI training for all employees. So, what changed? 

The answer to this question is something that happened on Nov 30, 2022. A till then unknown startup called OpenAI launched ChatGPT, and overnight, AI went from being something that needed extensive expertise and access to cutting tools to use, to something that was freely available to anyone with an internet connection. This sudden democratization is rapidly changing how AI is used across organizations. It has gone from being a top-down system that needed careful planning, vast resources and phased rollouts, to something that is bottom up. It promises to change the operating models of companies overnight. 

Of course, none of this is possible unless employees understand this technology, including its limitations and downsides. Savvy organizations have quickly understood this and are treating upskilling as a strategic initiative. But the focus of these companies is not only training employees on AI usage. There is a critical change management element to it as well.  

Will AI take my job? 

Companies are discovering that effective AI upskilling extends beyond technical training. It also addresses the fear and uncertainty employees feel about AI’s impact on their professional future. 

“It is not just about providing knowledge,” explains David De Cremer, founder of the Centre on AI Technology for Humankind at NUS Business School. “It’s about demystifying AI and transforming fear into enthusiasm. When employees understand how AI can enhance rather than replace their work, adoption accelerates dramatically.” 

Comprehensive upskilling programs that focus on both technical competencies and emotional barriers lead to significantly better adoption rates than purely technical approaches. By fostering psychological safety around AI, organizations can transform resistance into innovation. 

Smart Firms are Upskilling 

The demand for AI-related skills is growing exponentially. A 2024 report from McKinsey found that 47% of employees expect to use AI for at least 30% of their daily work within a year, yet only 20% of executives believe their workforce is prepared. This discrepancy underscores the urgent need for upskilling initiatives to close the gap and ensure AI investments generate maximum value. 

The financial case for AI upskilling is compelling. Organizations worldwide are projected to spend over $300 billion on AI technologies by 2026. However, many will see disappointing returns without corresponding investments in human capital. 

The equation is straightforward: An AI platform costing millions delivers little value if employees underutilize it, misapply it, or avoid it altogether. Conversely, our research from the IMD Business School indicates that organizations investing in upskilling realize significantly better returns from AI investments, often more than covering the costs of training. 

The Mayo Clinic provides a compelling example of AI upskilling success. Initially, AI was deployed to streamline administrative tasks and operational efficiencies. However, after investing in comprehensive AI training for their clinical staff, Mayo Clinic expanded AI use to diagnostics and personalized medicine. Their AI-enabled ECG system, for example, can detect heart weaknesses undetectable to human readers, delivering far greater value than their initial efficiency-driven applications. 

AI Upskilling Best Practices 

Given the scale and scope of impact that this technology will have over the coming years, firms need to be careful not to treat AI upskilling like other similar programs in the past, such as ERP trainings. Instead, we recommend the following steps. 

1. Start with the basics: Ensure that concepts like AI, ML and Generative AI are demystified for all employees 
2. Create customized learning pathways by roles and divisions: Different job roles and divisions require different AI skills and levels of expertise. Ensure that these differences are accounted for in the trainings. 
3. Practical learning is a must: Effective programs combine conceptual understanding with hands-on application, given how user friendly and accessible these tools are becoming. 
4. Create sand boxes for experimentation: Employees need opportunities to test AI tools without fear of failure. 
5. Identify ‘AI champions’ within business units and functions who can support learning in local environments.  
6. Establish learning communities that can support the needs of employees on an ongoing basis.  
7. Build continuous learning structures: AI evolves rapidly, necessitating ongoing education rather than one-time training. This includes a sharing of best practices as well as failures.

A Competitive Necessity 

As AI reshapes industries, upskilling is no longer optional; it is a strategic imperative. Organizations that treat workforce development as an afterthought will struggle to realize AI’s full potential. Those that recognize human capability as the linchpin of AI success will not only maximize their technology investments but will also build workforces equipped to drive innovation in an AI-augmented future. 

AI upskilling isn’t just a good HR policy; it drives higher employee engagement, maximizes AI adoption, and ensures a competitive edge in an evolving market. It’s the most strategic investment a forward-thinking company can make.

About the Authors 

Michael Wade is TONOMUS Professor of Digital and AI Transformation at IMD Business School in Switzerland.

Amit Joshi is Professor of AI, Analytics, and Marketing Strategy also at IMD Business School. They are co-authors of new book, GAIN: Demystifying GenAI for office and home.