New technologies aren't just changing the way we get work done – they are changing the types of work we do. As we march into the future, some positions will be phased out or replaced by technology solutions, while new types of jobs we haven't seen before will began emerging in the job market.
In fact, that's happening already. What's most surprising is that some of these brand new jobs aren't even technology-related – which may be a relief to those of us who worry we'll be replaced by robots in the near future.
The top 20 emerging jobs in the United States represent a solid mix of specialized high-tech roles and non-tech customer experience roles, according to LinkedIn's "2017 U.S. Emerging Jobs Report."
Customer-facing roles such as licensed realtor, guest experience associate, and personal loan consultant all made the list of the top 20 emerging jobs, alongside more tech-focused roles like machine learning engineer and data scientist. There are some roles where a computer just can't replace the human touch.
The Digital Talent Gap
Regardless of the composition of the emerging jobs list, Silicon Valley and the wider tech sector still face a widening skills gap. STEM skills may be in high demand, but they're also hard to come by. It is up to recruiters to develop creative ways to source this in-demand talent.
"We are in an era of talent intelligence where companies are turning to data solutions and artificial intelligence to identify new talent pools," says Dan Shapero, LinkedIn's vice president of talent solutions, careers, and learning. "Recruiters and hiring managers will have to shift from simply looking at where a candidate went to school or their last job and asses if the candidate has skills that can be transformed to fit the role."
"The Digital Talent Gap," a survey from LinkedIn and Capgemini, found that 51 percent of companies feel their employees don't have the hard skills to fill valuable digital roles.
There are plenty of tech-minded workers who could fit new roles with the right training. Unfortunately, many of these workers find themselves cast back onto the job market with outdated skills as newer technologies cannibalize older ones.
"Jobs specializing in older technology systems, such as Flash or Java, are losing steam and being replaced by more comprehensive skill sets," Shapero says. "We also found that four of the five fastest-growing skills in software didn't exist five years ago, which means anyone who left school before 2011 had no formal education in any of them."
Rather than casting aside employees once their skills become outdated, Shapero recommends supporting these employees so that they can develop the skills they'll need to fill the roles opening in your organization.
"Consider providing current employees or talented candidates in other fields with training materials to upskill," Shapero says. "You'll empower a new group of tech professionals to [fill] the growing need."
What's on the Horizon
While it's possible to see where your skills may lead you in the near future, looking at career options for the next generation becomes fuzzier. Sixty-five percent of children entering primary school now will end up working jobs that don't yet exist, according to LinkedIn's emerging jobs report.
"It's incredibly hard to predict the skills of 2030, but we can spot new skills just as they are emerging so that professionals can prepare for the future," Shapero says. "With the right data, you can get answers to the types of questions that will help inform your future talent decisions and shape the path of your company."
Whatever your career path, you'll likely need to pursue some type of continuing education to stay relevant in your field. Even roles considered non-tech will likely incorporate some tech component in the years ahead, and workers who are ahead of the game will find themselves securely employed.
"Future-proofing your career is twofold," Shapero says. "First, commit to learning, and staying on top of the new skills in your field. Second, consider how current skills might translate into newer roles. For example, people who have moved into these newer machine learning roles started with skills like research, algorithms, software, and deep learning."