Racing to unify thousands of inconsistent job descriptions on a strict timeline, a healthcare system deployed an AI-driven approach to standardize roles, bring clarity to talent data and build a scalable workforce framework.
As a healthcare system expanded through acquisitions, its growth created complexity at scale.
It had accumulated thousands of job descriptions that were duplicative, inconsistent and uneven in quality. What should have supported workforce strategy had become a source of risk.
The organization needed to standardize more than 8,000 job descriptions for Human Resources Information System (HRIS) integration as part of a Workday implementation — and it had 90 days to do it to avoid substandard data being rolled into the new system.
The stakes were high. Inconsistent job descriptions could create compliance concerns, hiring confusion and operational friction across a complex, multi-state organization. This was more than a cleanup project. It was a race to bring order to a mountain of workforce data before the HRIS window closed.
Segal’s approach was to combine workforce expertise with AI in a way that could scale.
We brought together experts from our Compensation and Career Strategies (CCS) and Administration & Technology Consulting (ATC) practices, with support from our Healthcare team, to collaborate on an efficient solution that was human first and AI forward.
First, the CCS team established clear parameters for structure, tone, content and level of detail so job descriptions would feel consistent across roles and locations. Then Segal tested the approach on a subset of jobs, refining the output with client feedback before scaling it.
Next, ATC developed a custom-built AI agent to streamline high-volume processing. That AI-driven solution enabled thousands of job descriptions to be consolidated, rewritten and standardized much faster than a manual approach could deliver.
Finally, the AI-generated job descriptions were reviewed for accuracy and consistency, ensuring the speed of automation was balanced by human judgment.
AI accelerated the work. Segal made it actionable.
By combining deep expertise in job architecture and scalable workforce design with a custom-built AI agent, Segal helped the client complete a massive standardization effort in just 90 days — a pace viewed as virtually unattainable by manual methods alone.
The hard-dollar impact was substantial. The AI-driven approach reduced client costs by $400,000, turning what could have been an expensive, labor-intensive manual project into a far more efficient solution.
AI eliminated a remarkable amount of manual work. The organization estimated that the effort saved 2,000+ hours of human labor, freeing the team from an enormous rewrite exercise and enabling the project to move forward on schedule.
Speed was only part of the impact — the job descriptions were clear, consistent and ready to use.
The standardized job descriptions were loaded into a tracking tool so managers could review and refine them, positioning the content for seamless integration into Workday. The result: a proven, AI-powered approach to solving complex workforce challenges faster, more efficiently and at enterprise scale.
Segal’s experts can help you use AI to standardize roles, improve workforce data and accelerate results.
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