Back in 2018, research experts PWC predicted a bifurcation of the automotive industry. They visualized a future where two factory types emerged: some producing custom vehicles and others mass-producing largely autonomous options.
Nearly a decade later, the mass adoption of self-driving vehicles is still likely to be several years away.
However, there is a type of bifurcation occurring in the automotive industry, specifically in workforce strategies. Traditional manufacturing roles are starting to give way to data specialists and AI experts, as manufacturers seek out new ways to advance innovation and enhance production. Understanding these changes in the future of automotive jobs could help recruiters enhance their workforce planning strategies.
Embracing Automation and Digitalization
Automation in manufacturing is nothing new. Robots have been in use by firms like General Motors since the 1960s. But emerging technologies like AI and machine learning are transforming the application of automation, from design to predictive maintenance. AI in automotive industry facilities can be used at an internal level, for sensors like LiDAR and features like collision avoidance. Within facilities, AI is more likely to be utilized for quality control and defect detection.
Digitalization in automotive sectors is also something manufacturers need to embrace. For example, many factory floor sensors can now be monitored remotely, using the Internet of Things (IoT). Digital tools can be used to remotely monitor maintenance requirements, temperature, humidity, and other factors that impact the efficiency of automotive manufacturing equipment. Resisting the implementation of these tools and failing to hire the relevant experts will inevitably cause vehicle manufacturers to get left behind.
Demand for Specialized Skills in the EV Era
The rise of electric vehicles (EVs) is also impacting how manufacturers hire. EV-focused personnel need expertise in high-voltage systems, software integration, and the application of machine learning algorithms for safety and automation. Manufacturers may end up with a fully split talent acquisition strategy, with one recruitment team looking for EV specialists while another looks for more traditional mechanical or electrical engineers.
EV manufacturing challenges include designing and building batteries that deliver in line with demands for increased range and performance. Research shows that there is a vastly underutilized opportunity for the use of AI and machine learning to reduce energy consumption in the automotive industry. A smart EV manufacturer could work with recruiters to hire the experts to unlock those insights, resulting in cost savings but also a more sustainable and eco-friendly approach to vehicle manufacture.
Implications for Workforce Planning and Talent Acquisition
This split in the types of personnel required for designing and building vehicles means that talent acquisition in manufacturing is becoming more complex every day. If firms want experts in AI and digital transformation, they have to ensure those skills are included in role descriptions. They also have to retarget their recruitment strategies, looking at more diverse talent pools.
Working with educational establishments to create direct pipelines from relevant courses to workplace opportunities could represent a win. Students may be more incentivized to excel in their courses if they know there is a lucrative job waiting for them at the end of their academic journey.
Partnering with expert talent solutions with access to data-savvy candidates is also a smart choice, particularly when these partners have a proven track record of results. Third-party recruitment specialists can offer advice on the skills to advertise for and what types of personnel could give an organization a competitive advantage.
Another option is investing in upskilling manufacturing employees. While this can take them away from the factory floor or back office for some time, the long-term results could represent a smart investment. McKinsey suggests reframing AI upskilling as a “change imperative” for any organization wanting to strengthen its competitiveness in its market.
Hiring for Emerging Skills: Proven Successes
Successful manufacturers are likely to see these types of workforce transformation as opportunities rather than challenges. Rather than taking a “split” approach and hiring both traditional and data-smart personnel, savvy recruiters will veer toward candidates who can demonstrate a range of relevant skills.
Examples of success in automotive manufacturing via embracing emerging skills include:
- Enhanced EV battery efficiency via the application of AI
- Granular temperature data from within electrical motors
- AI-powered simulations for higher quality OEMs
The German manufacturing company ZF recently developed TempAI, an AI-powered system that provides 15% more accurate temperature control, resulting in shorter development times. The right recruitment strategies can lead to more critical innovations along these lines.
Navigating Manufacturing Workforce Transformation
From electric vehicle production to the application of AI to make traditional automotive manufacturing more efficient, technology is changing the way vehicles are made. Smart manufacturers need to hire for the future, prioritizing a balance of manufacturing skills and data savviness to ensure their workforce has the skills to navigate a rapidly transforming industry.
Many organizations are investing in hybrid engineers, who have software skills as well as mechanical and electrical talents. Personnel with this wider range of skills can move across various areas of a facility and lend their experience to multiple aspects of manufacturing.
Others are working with recruitment solutions experts who understand the changing nature of Industry 4.0 and can source candidates from diverse talent pools. Outsourcing recruitment to specialists who can hire faster and smarter could be a cost-effective way to build loyal, productive teams.
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