Meet AI in Vendor Management Systems

Over the last several years, a mix of traditional and generative AI (GenAI) have made their way into vendor management solutions and changed how contingent labor and service workers are engaged and managed.

This started with the adoption of traditional AI, which is now common to almost every VMS tool that enters the market. GenAI has more recently begun to appear in newer VMS tools through large language Models (LLMs), providing the creation of outputs not seen with traditional AI. So, what do we mean when we say traditional AI and GenAI? Here is a brief overview:

Traditional AI focuses on task-specific automation, predictive analytics and data-driven decision making with predefined rules and algorithms. For example, a VMS solution may use traditional AI for candidate matching, predictive analytics for workforce planning or automated sourcing based on predefined criteria.
On the other hand, generative AI introduces a level of creativity, adaptability and flexibility by generating new content, simulating scenarios and learning from diverse data sources. In the VMS context, generative AI could create personalized candidate experiences, generate synthetic data for training machine learning models or simulate workforce scenarios for strategic planning.

Almost all major VMS providers have adopted some degree of traditional AI, with GenAI applications beginning to make appearances in more niche and purpose-built VMS offerings. Both AI approaches have their strengths and can complement each other in enhancing contingent labor management and statement of work (SOW) processes, but the current VMS marketspace is more heavily dominated by traditional AI capabilities.

Through AI-powered platforms, businesses can source, screen and manage contingent workers, matching them with the right roles based on skills, experience and availability. AI-powered platforms can also assist in the writing, negotiation and finalization of a SOW while providing key analytics on the performance tied to the SOW. With the introduction of traditional AI in VMS solutions, and now GenAI, vast amounts of data are being used to identify trends, predict demand, optimize workforce planning, digitally create job descriptions, personalize training and provide conversational support.

This article explores the current state of AI in the VMS marketspace, including a capabilities overview, a high-level market overview and an introduction to the emerging field of GenAI in VMS platforms.