Jobs That AI Can’t Replace: The Impact of Automation on Workforce
In this article, we discover the impact of AI automation on workforce and discuss how companies can prepare for AI-ready talent scarcity.
While replacing human labor with robotics is not a new phenomenon, AI takes this notion to a new level.
Previously, industrial machines were meant to augment humans’ physical abilities, but AI-driven automation is now poised to augment our cognitive abilities. Experts are convinced that the idea of a completely self-operated facility driven by manufacturing AI or medical self-diagnostics with the help of cognitive assistants will inevitably become real. While organizations are turning to AI consulting to cut costs, increase efficiency, and streamline decision-making, some of service sector employees will need to learn new skills or find another job.
The Impact of AI on the Future Workforce
First of all, there is a big difference between AI augmenting our workflows and completely replacing them. Currently, AI mostly nudge the decision-making vector in the right direction, which results in shorter time-to-action and higher decision accuracy.
For example, computer vision applications enable magnetic resonance imaging (MRI) tools to detect issues in soft tissues hundreds of times faster than human professionals. In this case, AI doesn’t make the surgeon’s skills obsolete but helps medics achieve the same results more efficiently. In finance, AI can simulate a market situation for humans to test different scenarios. Being a naturally more accurate mechanism than a human brain, it reduces error risks and cuts the time spent on analysis, insight generation, and taking action.
Such examples are prevalent across the majority of industries that are currently in the midst of AI disruption. Sectors like finance or healthcare are simply getting enhanced by streamlined AI-supported data analysis. In such cases, workers will only need to have a mild additional training to onboard new AI tools without losing their jobs. However, as AI will get more mature, it will have a much more significant impact on workforce depending on the nature of a job in question.
Most products we can’t imagine our lives without require hours of workers routinely performing the same set of tasks. In this case, regardless of human expertise, AI-enabled robots will achieve better results faster, with fewer resources. This is why jobs in sectors like manufacturing and transportation are the most threatened by automation in the long term. This includes crane operators, assemblers, service laborers, inspectional professionals, machinists, and electrical technicians.
According to the McKinsey research titled The Future of Mobility Is at Our Doorstep, autonomous vehicles will make up 40% of new vehicle sales in 2040. This means that many tasks, including physical allocation of resources in construction or remote control of emergency vehicles, can be completely automated, thus redefining fleet management development as we know it.
In the recent EY report Rethinking the Oil and Gas Workforce in 2040, researchers claim that 60% of equipment operators in Canada’s oil and gas sector will most likely be replaced by AI-enabled robots.
According to IDTechEX, more than 100K autonomous forklifts and trucks will be sold by 2030. Considering that more than 95% of forklifts are operated by humans and the ROI is achieved within 18 months on average, those kinds of navigational skills will become mostly obsolete in about 20 years.
It’s worth noting that regardless of the AI advancement level, industries that rely on people-to-people interaction won’t ever be completely automated. For example, the expertise of education professionals is measured more by social intelligence and empathy than any technical skills. Sales and marketing sectors require a granular understanding of people’s background and outspokenness — features that AI naturally can’t excel at. Human contribution is fundamental for many industries to operate.
AI-ready Talent Scarcity: What to Do?
Job losses from AI-enabled automation will mostly be compensated by the creation of new jobs that require AI-specific skills. According to LinkedIn, the hiring growth for artificial intelligence specialists has reached an astounding 74% in the past four years. At the start of 2020, a LinkedIn search for AI-related jobs could yield more than 230,000 worldwide openings. According to the 2020 World Economic Forum report on the future of jobs, 97 million new roles may emerge as a result of AI disruption by 2025.
However, even today the global AI talent demand doesn’t meet its supply. As the technology proliferates, AI-related jobs will be created at a faster pace than people can adapt. This will make already highly demanded AI specialists even more sought-out.
If we take a closer look at the future job market, attracting a high number of new talent will be economically feasible only for industry giants. This is why it’s crucial for existing organizations to develop new strategies that will help their employees to reskill and upskill.
In cases when companies need to build very specific, highly customized AI-enabled solutions, the attraction of new talent is inevitable. However, the type of professional background needed for operating and interacting with these systems can usually be found in existing staff. By putting extra focus on augmenting and retraining current employees, organizations will not only solve the ethical dilemma but also reap significant economic benefits. This is a win-win situation for both employees and their companies.
Contrary to popular opinion, AI automation is not meant to cut costs by reducing headcount. In the majority of cases, it augments existing human capabilities and frees up workers’ time to focus on more creative tasks. From a business standpoint, organizations that view AI as just a way of process optimization will most likely miss on the opportunity to realize the technology’s full potential. The approach to AI adoption should revolve around bringing more value through a powerful symbiosis of human judgment and computer intelligence.
However, regardless of how hard companies will try to prepare their workers for the AI revolution, there will be people left with no relevant skills. To mitigate potential unemployment, governments should also take an active role in balancing out the economic destabilization caused by automation. For example, many experts call for universal basic income schemes as a method of maintaining the wellbeing of people affected by automation and digitization.
Tips for Business Leaders
Essentially, in the wake of mass AI adoption, the race for scarce AI talent will accelerate. Putting the right amount of resources into retraining will most likely differentiate leaders from the rest in this race. Here are the steps companies should consider when preparing for AI transformation in terms of workforce adaptation.
- Plan for the long term but set short-term objectives
This will help you understand how specialized your AI needs are. Given that AI adoption is a continuous process, your AI talent demands will vary over time. By having a clear implementation roadmap, you can estimate how many workers you need to be retrained and how many you’ll need to attract from outside.
- Evaluate your workforce’s skillsets
Basically, you need to find out who can be upskilled or retrained among your employees. Undeniably, some projects require building sophisticated AI models from the ground up, which calls for hiring competent AI and data engineers. For other projects, helping your business users learn how to utilize pre-built AI tools can be sufficient.
- Work out a change management strategy
Given that AI is likely to be the most impactful technology this generation of workers will ever experience, their reluctance to change is not surprising. This is why it’s important to involve business leaders and opinion makers as early as possible.
The reasons for AI integration should be transparently stated and discussed with exactly those people who will be the most affected. Leaders should highlight career development opportunities and provide a clear vision for assisting displaced employees if that’s the case. Moreover, AI usually implies more collaboration between different departments. By encouraging teamwork early on, it’s possible to maximize the cross-functional chemistry of different departments and facilitate their AI onboarding.
- Involve end users into AI development
Companies need to do their best to create intuitive and user-friendly tools while also demonstrating the reasoning logic behind AI decisions. This is especially important for such sensitive industries as healthcare and banking, where practitioners need to rest assured that machine learning challenges are resolved in the process. Instilling confidence comes down not only to employees’ emotional reassurance but to technically proving that tools they are going to use can be trusted.
- Educate beyond upskilling
Let’s take healthcare as an example. As life expectancy is increasing, healthcare has to deal with more and more patients having complex chronic problems that require a proactive approach. With a growing number of AI applications proving helpful in this regard, we will need more practitioners being knowledgeable about using them. Basically, by 2030 an average clinician will need to be well-versed not only in their standard medical areas but also in AI and machine learning. This calls for a complete rethinking of healthcare education, where areas like medicine and IT intersect. Creating centers of excellence or comprehensive training programs focused on AI-centric education should become a new standard in the next decade.
AI-enabled automation will inevitably change the nature of many jobs as well as displace some completely. While headlines tend to make it look as dramatic as possible, the current pace of AI adoption leaves enough time for employers and their workforce to get ready. Generally speaking, to minimize the negative impact of AI disruption on workforce, we need everyone, from employees to business leaders to policymakers, to take part.
Workers in sectors like transportation and manufacturing need to become more flexible in their learning and be ready to adopt AI to stay relevant in the jobs market. While personal drive should be at the core of any upskilling initiatives, they also need to be encouraged and incentivized by their respective employers as well as governmental and educational organizations.
Companies need to retrain their existing workforce as much as it’s feasible and resort to attracting new talent only when it’s absolutely needed. AI should be culturally embraced and trusted, but this can happen only when all economic actors work in collaboration.
It is suggested that job losses from automation will be balanced out by the creation of a whole new specter of AI-related jobs. In the long term, the wealthier economy created by the introduction of AI will also help offset the negative impact on the labor market.
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