WTW brings AI-powered job matching to Rewards AI
Key Highlights
- ➤WTW launches AI-powered job matching within Rewards AI
- ➤Rewards AI recommends job disciplines, career bands and levels
- ➤Capability explains matching rationale while retaining human final decisions
- ➤Tool uses WTW proprietary job content, rewards data and methodology
Expert Statements
Sambhav Rakyan, Global Rewards Data Intelligence Leader, WTW
“A job title may stay the same even when the work is changing. A software engineer role, for example, may now include responsibilities related to generative AI, agentic systems or workflow automation that did not exist a few years ago. That can change how the role should be understood, leveled and benchmarked.”
Sambhav Rakyan, Global Rewards Data Intelligence Leader, WTW
“As roles evolve, compensation teams need more than a list of possible matches. They need to understand why a match fits and apply a consistent methodology, while retaining the professional judgment required to make the final decision.”
Sambhav Rakyan, Global Rewards Data Intelligence Leader, WTW
“Organizations have more workforce data than ever before, but the challenge is turning that information into better decisions”
Sambhav Rakyan, Global Rewards Data Intelligence Leader, WTW
“By combining trusted rewards data, proven methodology and AI-driven conversational experiences, we're helping compensation teams spend less time searching for answers and more time taking action.”
NEW YORK, Oct. 13, 2026 (GLOBE NEWSWIRE) -- WTW (NASDAQ: WTW), a leading global advisory, broking and solutions company, has introduced AI-powered job matching capability to Rewards AI, helping compensation teams keep pace with evolving jobs and skills through faster, more consistent job matching.
Using Rewards AI for Job Matching, compensation professionals can enter a job title or describe a role in everyday language and receive recommended job disciplines, career bands and career levels based on WTW job content and survey methodology. The job-matching capability explains the rationale behind each recommendation, allowing users to review the options and make the final decision.
Get started
Create a free account to read the full story.