This is the second in a series on AI transforming the workplace. Read the first piece here.
Despite the pandemic continuing to spread, it may not be too soon for HR decision-makers to look ahead toward its eventual end.
When that day comes, HR leaders and employers around the globe will be back to, among other issues, figuring out exactly how AI-based technology can continue to drive success in the newly reopened world of work.
Seth Earley—CEO of Earley Information Science and author of The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster and More Profitable—says the massive workplace changes brought on by the pandemic are sure to continue. And AI will play a key role.
He predicts many organizations will continue to allow remote work even post-pandemic, and, thus “will have to be more aware about what this change means for recruitment, job satisfaction, performance and retention.” In fact, tech giant Google said in late July it will continue its remote work strategy until at least the middle of 2021. No doubt other employers will follow suit.
Earley says greater use of remote teams means that work culture will be more fluid and, by design, will need to be less dependent on physical cues that in-person communication provides. At the same time, he adds, measuring and maintaining employee engagement will require heightened integration of HR and day-to-day collaboration tools. This need will arise, Earley explains, because many HR applications are legacy-based, on-premise and siloed, making it harder to read signals of disengagement across multiple systems.
“AI-powered, integrated cloud solutions will enable aggregation of analytics and flag low-engagement employees and employees likely to leave,” Earley says. He adds that the rapid deployment of remote work and new collaboration technologies means that data, architecture and user experience functions were likely cut in the rush to adapt during the pandemic.
“These tools will need to be reconciled, rationalized, standardized and correctly re-architected to improve rather than detract from productivity,” he adds.
According to Earley, fewer in-office interactions will increase dependency on knowledge bases and improved information access and usability. For example, the days of asking a colleague for routine information because it is too difficult to locate on the intranet “will, by necessity, be behind us.”
Plus, he says, employees who have to use multiple systems to accomplish their work (or who have to adapt to a different team’s preferred technology) will be less satisfied due to the overhead and inefficiency such disconnected environments cause. Using AI tools to integrate and bridge the gaps—including through chatbots for answering routine or team- and project-specific questions, semantic search and better knowledge architecture—will improve job satisfaction and increase productivity.
“Many elements of the post-pandemic workplace will change dramatically, such as the role of serendipitous in-person interactions,” Early says. “Intelligent collaboration systems can help fill this gap.”
According to Earley, fixing the foundation of the employee experience, in part through AI-based applications, needs to be the priority across all market segments.
“This will be a challenge in the post-pandemic era, but those who do not do it will lose talent, customers and market share to the ones that do,” Earley says.
Ken Lazarus, the former CEO of Scout Exchange, which was recently acquired by Aquent, expects to see an increase in AI use post-pandemic, as employers have become more sophisticated in their use of the technology, especially in regards to attracting and retaining talent—which will be even more competitive in the years ahead.
“AI started with bots for simple communication,” Lazarus says. “What I’m beginning to see in many different use cases—from screening applicants and job candidates and scheduling them for interviews to internal talent mobility—is a greater use of ‘conversational’ AI.”
“You can even throw it some curveballs and have that be all conducted with software and artificial intelligence, rather than a human being,” he says.
According to Lazarus, other future trends driving more AI-based solutions include:
- Work locations totally decoupled from where employees live;
- The need to use more AI and matching by marketplace recruiters; and
- Performance-based matching, which entails a large marketplace and much fewer geographic constraints, enabling employers to use AI to optimize for specific talent objectives, including the quantity of hire, quality of hire, diversity, cost and time-to-fill.
Check back soon for part three.