Even in households without them, virtual assistants such as Amazon’s Alexa and Apple’s Siri have become familiar forms of artificial intelligence (AI). But more and more, the technology is working behind the scenes at the workplace — to the benefit of both employers and employees.
That’s because AI-based tools are saving companies impressive amounts of time and money while helping employees grow. “The key driver for a company to select an AI platform for learning and development is to personalize the learning process and link learning to business strategies of the organization,” says Jeanne Meister, partner at human resources advisory and research firm Future Workplace and co-author of The Future Workplace Experience.
When AI makes the skill matches, it’s also helping a company to eliminate the inherent bias that often occurs in the resource allocation process.
The powerful algorithms of AI-driven tools analyze skill gaps among new employees, allow employees to speed through the onboarding process and merge employee pools during acquisitions. On-the-job training and skill development now involve highly personalized and more engaging learning programs that adapt to the user. And personal assistants in the form of chatbots and voice-enabled virtual assistants substantially boost employee productivity and output.
Here’s a look at how AI is swiftly transforming learning and development in the workplace.
In June 2018, Vancouver, Canada–based SkyHive released an AI-driven platform that significantly speeds up the onboarding process by instantly performing the usual tasks, such as matching the highest-skilled individuals in an organization to new employees needing training in particular competencies. One SkyHive client — a large private company undergoing an acquisition — was able to drastically compress the time of integrating the two companies and completing the onboarding process thanks to the platform, which quickly inventoried the skills of the acquired team to understand where those employees could be best positioned in the parent company. It also identified those who required additional training.
When AI makes the skill matches, it’s also helping a company eliminate the inherent bias that often occurs in the resource allocation process. “Regardless of gender, language, age, educational or work background, a skill is a skill, and most are largely transferable,” says Sean Hinton, SkyHive CEO and co-founder.
AI also offers a new perspective: real-time data. By looking in real time at changes that happen to jobs, SkyHive’s recommendations for onboarding, training and development become adaptive, “meaning that someone is not going to waste their time learning a skill or competency that will fall out of importance for the employer in two years,” Hinton says. “Instead, people can focus more on progressing in the workforce and making sure they remain relevant as things change.”
Together with data analysis, adaptive learning can help map out career trajectories based on the employee’s personality and way of learning.
Companies are struggling to fill growing skill gaps. “Five years ago in a survey by PricewaterhouseCoopers, 58 percent of CEOs said they were concerned that a lack of critical skills was threatening their business,” Meister says. “Now, 80 percent say it’s a risk, so there is a huge interest in how to best deliver learning that meets the needs of both the learner and the business strategy of the organization.”
With AI-enabled adaptive learning, companies can train employees more efficiently, zeroing in on the specific skills they need and lack. Because an adaptive learning platform literally adapts to the employee’s ability to understand the material, repetitive exercises are eliminated for those who demonstrate ability, while those who need more practice will receive it. Together with data analysis, adaptive learning can help map out career trajectories based on the employee’s personality and way of learning.
In early 2017, Detroit-based watch brand Shinola launched Shinola University in partnership with Danish adaptive learning company Area9. Instead of tallying correct and incorrect answers, the cloud-based online platform measures employees’ levels of confidence with the material and provides additional content and training as needed. For the second phase, Shinola plans to use the platform to help employees learn to interpret customer behavior and nonverbal language.
By 2021, more than 50 percent of companies will spend more on developing bots and chatbots than on traditional mobile apps. That’s because chatbots — both text-based and voice-enabled — are not only for customers. The tools are also rapidly enhancing employees’ abilities to gather and process information, and collaborate in teams, whether during the onboarding process, a complex project or required training.
In 2017, Vodafone introduced its employees to Zap, a chatbot from Oviedo, Spain–based start-up Zapiens. When an employee has a question, Zap finds the answer, no matter how high up the corporate hierarchy it needs to search. “Zapiens is the internal Siri of the company,” says Rebeca Navarro, head of selection, talent, diversity and learning at Vodafone.
The Royal Bank of Scotland (RBS) deployed a similar tactic in 2017 with Ask Archie, an IBM Watson–powered chatbot developed in house that has quickly boosted employee engagement and productivity. By efficiently resolving more than 5,000 employee queries a month — about half the total queries usually handled by HR — the chatbot has saved the company almost 2,000 worker hours per year, RBS estimates.
IBM Watson is being put to work as a career coach, too. In late 2018, workforce information firm Kronos began using a Watson–powered, mobile-based chatbot to provide hourly workers with personalized advice on topics such as recommended trainings and getting promotions. Although the service does not replace human career management, it may prove to be an effective complement, especially for companies with large numbers of hourly workers.
ILLUSTRATION by Greg Mably