When employees think about their coworkers, they likely envision the teammates with whom they collaborate on projects, exchange office banter, and attend the occasional happy hour. In the workplace of the future, however, the term “coworker” might have a different connotation—it might not necessarily mean another human.
“I’m a big believer that technology is just one of our colleagues,” says Muriel Clauson, emerging technologies researcher and founder of Oppticity, a startup documenting the “skills map” of the modern workforce. “It does not replace human workers—the biggest issue is that it can replace them if we’re not properly preparing people to be effective in ways that are [complementary] to tech.”
Training employees to adapt to a rapidly fluctuating enterprise technology stack—including platforms fueled by artificial intelligence (AI) and machine learning—is often referred to as “upskilling” or “reskilling.” But while many employers recognize the importance of this practice, few are actually deploying programs to accomplish it: According to a 2018 study from Accenture, 61 percent of business leaders expect an increase in the number of roles requiring collaboration with AI by 2021, yet just three percent are planning significant investment in training and reskilling programs.
“As far as enterprise-level AI adoption goes, a company should always strive to reskill as many of its current employees as possible. Employees who are currently successful, fit their culture, and serve as ambassadors of best practices can be highly valuable in another, reskilled role,” he says, noting that a “healthy balance” of talent also involves hiring new workers with fresh perspective.
As organizations strive to implement enterprise-level AI to boost day-to-day operations, they simultaneously face the task of making the technology a seamless, collaborative member of the team, infusing it into employees’ daily practices. Below are a handful of concrete steps employers can take to lay out a roadmap for reskilling current talent.
“When we’re talking about reskilling workers, there are so many levels we can think about: evidence-based education in traditional education models, apps that help workers craft their careers and think about next steps, and everything in between,” says Clauson.
But in order for any solution to be successful, she notes, companies must have a clear understanding of three elements: the “building blocks” of the work being done at their organization (i.e. the specific skills that human employees contribute), how technologies like AI might affect these processes, and the interplay between the two.
“I would argue that the biggest thing holding us back right now from successfully reskilling workers isn’t that we don’t understand technological change—it’s that we’re not doing a great job yet of modeling labor data and thinking about all of the components of work in [that way],” says Clauson.
Oppticity aims to address this pain point. The organization—which is still in beta, but currently working with multiple corporate partners on a trial basis—uses a combination of historical data and behavioral analysis to identify granular elements of an organization’s skills ecosystem.
“We try to quantify all of the little components of a job … then, we compare those components with the capabilities of technology today, in the near term and in the longer term. So, we can help the organization see, ‘Here’s the reality of your talent pool today, and here’s how that stacks up against technology.’”
Clauson hopes the process will help companies devise learning and development initiatives that go beyond vague advice such as “focus on honing soft skills”—a common refrain in the space, but one that can be hard to take action on. She believes Oppticity will help inform evidence-based programs to “develop the parts of workers that are the most human, which we really do need in the future alongside technology.”
Effective Reskilling Strategies
The idea that AI will enable employees to focus on higher-level functions of their jobs isn’t a new concept. In the book Human+Machine: Reimagining Work in the Age of AI, authors Paul R. Daugherty and H. James Wilson assert:
“A widespread misconception is that AI systems, including advanced robotics and digital bots, will gradually replace humans in one industry after another… That may be true for certain jobs, but what we’ve found in our research is that, although AI can be deployed to automate certain functions, the technology’s greater power is in complementing and augmenting human capabilities.”
The real-world application of this statement might look like this: Instead of being saddled with requests for order statuses—a task that an AI-driven chatbot can handle remotely and instantaneously—customer service representatives may spend more time developing customer retention strategies or devising new loyalty programs. Or, an HR manager might be freed from the tedium of constant paperwork in order to develop new learning and development programming—perhaps even courses with a dynamic approach to reskilling.
Weiting Liu, founder and CEO of Codementor, an on-demand marketplace for software developers, breaks down this skills segmentation as such: “Machines will handle information and data processing, whereas humans will spend more of their time on reasoning, coordinating, and decision making.”
But to get to this level of synergistic efficiency, employees first need to know how to work in tandem with AI systems—to regard them as colleagues versus simply tools or even threats. And the responsibility for encouraging this mindset shift falls to employers. “To prepare for this future, leaders must put in place sustainable training infrastructure and seek out partnerships with educational institutes or online learning platforms,” says Liu.
There are numerous avenues that companies can explore for equipping workers with the necessary skills to work alongside AI. “Learning marketplaces or networks are becoming more sophisticated, and the supply of highly-technical remote talent is growing more accessible,” says Liu. “Companies can now tap into technical expertise through networks like the Codementor platform, benefiting from the flexibility of scaling up or down quickly based on their needs.”
Clauson echoes the idea that Massive Open Online Courses (MOOCs) and platforms like Codementor may provide valuable resources for reskilling at scale. The beauty of these programs, she notes, is that they’re extremely accessible, even to employees who haven’t traditionally held technical roles.
“We don’t want just one type of person influencing something that touches everybody’s lives,” she says. “What I’m really excited about is [exposing] people who come from [diverse career backgrounds]—maybe they’re more artistic or they’re passionate about the environment—to ideas in AI, whether theoretical or applied. I really believe we’re going to have better and better AI the more we have different perspectives.”
The Road Ahead
Armendariz cites AT&T as an example of one large corporation committed to reskilling its employee population. The company’s Future Ready initiative, a $1 billion program, aims to train 100,000 employees by 2020, preparing them for new or redesigned roles created by the digital revolution. “While other companies have started training programs, this is an undertaking of massive proportions,” says Armendariz.
Such large-scale efforts are bound to experience obstacles—retraining employees who have been in their existing roles for decades and who have a fear of change or of the unknown, for example. Armendariz adds that cultural shifts may also occur, since many new jobs won’t require the degree of face-to-face interaction as manual roles did, potentially leading to tension or changing team dynamics.
To quell doubts and address these challenges, both Armendariz and Clauson cite corporate transparency as crucial.
“Extensive communication, planning, and strategic discussions on how their role will play a part in achieving the company’s goals are essential,” says Armendariz. “An employee in constant fear of having their role eliminated will not perform well, so setting a clear timeline and expectations goes a long way toward keeping employees happy and productive.”
Clauson calls the current moment a “critical juncture” for business leaders to help forge the workplace of the future—and to determine whether AI will find a welcome seat at the table. This starts, she says, with really getting to know employees and having genuine conversations with them about the trajectory of their roles.
In her work with companies and governments across four continents last year, Clauson says people—regardless of socioeconomic status or culture—see work as a big part of the human experience.
“It’s a big part of how we spend our time, no matter what your current circumstances are,” she says. “Today, we can make decisions to build a better future of work.”