In today’s labor and economic climate, enterprises cannot afford to make poor hiring decisions. And with 47.5% of an organization’s workforce comprised of contingent workers, per Ardent Partners and Future of Work Exchange research, an extended worker hire is just as critical operationally as a permanent employee. The ramifications of a hiring mistake — whether it’s an extended or permanent role — can cost businesses 30 percent of the employee’s first-year earnings, according to the U.S. Department of Labor. However, artificial intelligence is now shaping the future of contingent workforce management (CWM) to help avoid those employment missteps.
CWM Optimization Through Artificial Intelligence
Through artificial intelligence, enterprises can harness the value of structured and unstructured data to streamline contingent workforce management decision-making. AI also opens the door to new user experiences to better attract, acquire, and retain top-performing talent and improve operational execution — all leading to cost savings. Using prescriptive analytics for CWM optimization is an evolving but critical piece of AI strategy. While artificial intelligence has existed for a decade or more, the wider scope of its capabilities is only now being utilized.
The rest of this article is available by subscription only.
Introducing a New Subscription Model from the Future of Work Exchange.
To continue providing valuable insights and resources on the future of work and extended workforce management, we’re transitioning our site to a paid subscription model. While some posts will remain free, subscribing will grant you exclusive access to in-depth analysis, market research, expert interviews, and actionable strategies that will help improve your business. Solution providers and practitioners are invited to join today and gain a competitive edge by tracking the industry’s important innovations, emerging trends, and best practices.
