Tania de Decker, Managing Director—Global Strategic Accounts, Randstad Enterprise Group09.25.23
Artificial intelligence (AI) may be one of the most important developments in the world of work. As manufacturers implement new technologies and tools, how work gets done will be transformed. Rote and low-value activities currently performed by people may be potentially taken over by machines and algorithms, driving greater efficiencies and cost savings. AI also has the potential to accelerate the innovation and commercialization of medical devices since it can help people innovate and commercialize faster—that is, only if companies have skills to make use of it.
Generative AI is expected to grow faster in healthcare than any other sector, according to Boston Consulting Group (BCG).1 In fact, it’s expected to expand 85% annually by 2027 to reach a total market size of $22 billion. The BCG authors outlined more than 60 use cases that will transform how medical manufacturers perform work. With such a bright future, the medtech industry will surely be impacted from growing demand and work reorganization.
However, is the industry ready for a new world of work? Do OEMs and their suppliers have the ability to take advantage of such growth prospects with a workforce ready and skilled for the age of AI? It’s not at all clear they can overcome the talent shortage that currently plagues the industry, let alone overcome the requirements for new skills around AI. In fact, new research from Randstad shows a glaring gap in the desire of workers for AI training and how much they actually receive at work, despite a considerable number of people already using this technology at work.
Most (52%) believe AI will lead to their own career growth and promotion rather than losing their job. This is evidenced by a surge in job postings seeking AI skills.2 Randstad’s own tracking of such postings indicates an increase of 2,000% since March alone.
Even though AI is clearly proliferating in the medtech industry, the research is exposing gaps in the response of employers. Overall, 22% of all workers said they desired more training around AI, but just 13% have received it during the past 12 months. Among manufacturing workers, about one-quarter (24%) wanted this kind of skills development, but only 13% have been provided access through their jobs.
As medical device makers implement more AI-powered tools and workflows, training their people to make the best use of such tools is critical to successful adoption. AI in all its forms—machine learning, deep learning, natural language processing, and generative—hold great promise but it must be tamed and managed to do its best work. This requires organizations to consider guidelines and practices on when it is appropriate to leverage AI, ethical implications, compliance with applicable regulations, and a learning and development curriculum for workers.
To best do this, device makers need to focus on several factors.
References
Tania de Decker is the managing director of global strategic accounts for Randstad Enterprise Group. She works with Fortune 500 companies to develop and implement processes that improve and drive recruitment and retention solutions. de Decker has more than 28 years of recruitment experience and has worked more than 18 years with life sciences companies. The emphasis has always been improving the quality of her clients’ talent acquisition.
Generative AI is expected to grow faster in healthcare than any other sector, according to Boston Consulting Group (BCG).1 In fact, it’s expected to expand 85% annually by 2027 to reach a total market size of $22 billion. The BCG authors outlined more than 60 use cases that will transform how medical manufacturers perform work. With such a bright future, the medtech industry will surely be impacted from growing demand and work reorganization.
However, is the industry ready for a new world of work? Do OEMs and their suppliers have the ability to take advantage of such growth prospects with a workforce ready and skilled for the age of AI? It’s not at all clear they can overcome the talent shortage that currently plagues the industry, let alone overcome the requirements for new skills around AI. In fact, new research from Randstad shows a glaring gap in the desire of workers for AI training and how much they actually receive at work, despite a considerable number of people already using this technology at work.
Gap in AI Training Is Concerning
The 2023 Q3 Workmonitor research, a survey of 7,100 workers conducted in five countries in August, found AI utilization varied from as much as 56% in India to 24% in Germany and the U.K. Excitement about the prospect of using AI also varied, from 74% in India to 36% in Germany. Another notable finding showed that among the five markets—Germany, the U.S., U.K., Australia, and India—more than half (55%) think AI will affect their role and industry.Most (52%) believe AI will lead to their own career growth and promotion rather than losing their job. This is evidenced by a surge in job postings seeking AI skills.2 Randstad’s own tracking of such postings indicates an increase of 2,000% since March alone.
Even though AI is clearly proliferating in the medtech industry, the research is exposing gaps in the response of employers. Overall, 22% of all workers said they desired more training around AI, but just 13% have received it during the past 12 months. Among manufacturing workers, about one-quarter (24%) wanted this kind of skills development, but only 13% have been provided access through their jobs.
As medical device makers implement more AI-powered tools and workflows, training their people to make the best use of such tools is critical to successful adoption. AI in all its forms—machine learning, deep learning, natural language processing, and generative—hold great promise but it must be tamed and managed to do its best work. This requires organizations to consider guidelines and practices on when it is appropriate to leverage AI, ethical implications, compliance with applicable regulations, and a learning and development curriculum for workers.
Supporting People Through the Transition
Furthermore, AI is a disruptive force that companies need to calculate into their talent strategy. It will both create jobs and eliminate them—although according to the World Economic Forum, technology, including AI, will lead to a net gain of jobs.3 Even so, there will be millions of people who will be displaced during the transition, so employers need to consider how they can minimize the impact on people. This will require continuous upskilling of workers and providing career transition services for those who cannot be redeployed within their companies.To best do this, device makers need to focus on several factors.
- Prioritize change management: Technology adoption requires putting people at ease, giving them clarity on job paths, and providing them the resources to adapt. The learning curve, job loss concerns, and pressure to be more productive are challenges requiring a thoughtful approach. Start by communicating the benefits of automation—greater efficiency, giving people time back, and achieving superior quality—to gain buy in. Set clear expectations and goals so no surprises come up.
- Re- and upskilling is pivotal: As our research shows, there is a tremendous appetite to learn how to use AI in the workplace, but employers have been slow in offering this to their workers. Business leaders need to recognize the opportunity technology offers for growing their business through better customer engagement, more innovation, and reduced time to market. To do this, workers must receive the proper skilling resources and the time to learn. Success is only assured when the people using the skills have the knowledge and expertise to effectively leverage AI.
- Workforce feedback: Because AI is still new to many organizations, decision makers must continuously listen and change according to the people using these tools. There are many concerns about the use of AI—ethical, practical, and costs among them. The best way to address shortcomings or misuse is to survey the workforce on the effectiveness and outcomes of this class of technology. For instance, if AI is deployed to source and screen candidates, does it do so without bias that may be inadvertently introduced? Seasoned recruiters may be able to detect such biases and help correct problems with algorithms or data.
References
Tania de Decker is the managing director of global strategic accounts for Randstad Enterprise Group. She works with Fortune 500 companies to develop and implement processes that improve and drive recruitment and retention solutions. de Decker has more than 28 years of recruitment experience and has worked more than 18 years with life sciences companies. The emphasis has always been improving the quality of her clients’ talent acquisition.