Join a panel of compensation experts as they discuss how to harness AI to drive fairness, transparency, and smarter pay decisions.

1. How AI is
reshaping pay
decisions

2. Today’s Speakers
How AI is reshaping pay decisions
Chief Research Officer
Ben Eubanks
Lighthouse Research and Advisory Payscale ITX Corp
Senior Compensation Manager
Senior Director of Data Science
Sara Hillenmeyer, PhD Paulo Fava

3. AI is capable of taking over
70% of comp professionals’
current tasks today.

4. ● AI is Already Reshaping Compensation
● How AI Will Enhance Your Total Rewards Strategy
● The Skills to Develop in the Age of AI
● What Should You Do Next?
● Any Questions?
Agenda

5. AI is already
reshaping
compensation

6. 71% of
compensation
professionals are
feeling positive
about AI supporting
compensation
decisions
What best describes your sentiment around
leveraging AI/machine learning...
19%
24%
10%
48%
20%
21%
8%
51%
… for recommending
pay increases
… for market pricing
Totally on board Cautiously optimistic Undecided Against it

7. Let’s look at what AI can already do…
And where it's at right now is the worst it's ever going to be.
• Job descriptions
• Job architecture and organization
• Benchmarking
Filling in data gaps, mitigating bias

8. ChatGPT writes a job description
ChatGPT Job Descriptions.mp4
Prompt:
ChatGPT Job Description
Write a job summary and key
requirements for an advanced
level comp analyst. I need them
to have experience with modern
compensation data sources and
compensation tools.
Follow Up:
Add a CCP

9. DeepSeek.mp4
DeepSeek builds job levels
Prompt:
My company has 20 jobs, listed below. Organize
these jobs into normalized job titles, and assign each
job to both a career ladders and assign a level (these
could be separate for the different types of jobs, e.g.
P1, P2, P3, etc for ICs and M1,M2,M3, etc. for
management). Make sure it's clear which jobs are
from the same career ladder. Fill in any missing roles
or levels to provide complete career ladders. Make
sure that the levels are consistent between the
ladders.
Here are the jobs:
junior software engineer, software engineer, senior
software engineer, engineering manager, sr
engineering manager, Engineering director, CTO, Ai
scientist, sr ai scientist, sr Director, Data and AI,
junior analyst, sr analyst, data visualization specialist,
Customer Support analyst, VP, Engineering, VP, Data
and AI, Machine Learning Engineer, Data Engineer,
Senior Data Engineer, Front end developer, Back end
developer
Follow up:
It looks like the Director of engineering and the
Senior Director of Data and AI are at the same level.
Should they be? Add levels as needed

10. AI benchmarking tools, like Payscale Verse, fill in data gaps
and mitigate sampling bias

11. AI will be a
powerful partner
for comp
professionals
● Real-time benchmarking
● Automation in compensation reporting and planning
● Scenario planning (What if?)
● Salary Structure Analysis
● Budget Forecasting
● Job Matching Automation
● Skill-Based Pay Progression
● Pay-for-Performance Calibration
● Other use cases

12. How AI will
enhance your
Total Rewards
Strategy

13. AI strategies
for Total
Rewards

14. Benefits
• Benefits personalization engines
• Predictive modeling of benefits utilization to optimize
costs (e.g., medical, retirement)
• Chatbots for 24/7 employee benefits support and
education
Recognition
• AI-powered recognition platforms that recommend peer
or manager recognition opportunities
• Sentiment analysis on recognition programs
• Personalized rewards suggestions
Wellbeing
• Predictive wellbeing risk scoring
• Personalized wellness program recommendations using
engagement and health data
• Virtual wellbeing assistants
Career Growth & Development
• AI career pathing tools suggesting next best roles based
on skills, interests, and company needs.
• Personalized learning recommendations aligned to career
aspirations and organizational gaps
• Predictive modeling to forecast future skill needs and
match talent pipelines accordingly
AI for Total Rewards Strategies

15. How AI will transform total rewards
Personalized Employee Experiences: AI tailors compensation, benefits, and recognition based
on individual preferences, life stages, and performance.
Data-Driven Decision Making: AI analyzes massive amounts of employee and market data,
enabling more informed and precise decisions on pay, benefits, and career progression.
Real-Time Adjustments: AI models anticipate changing employee needs, allowing companies to
quickly adjust rewards strategies in response to market shifts, economic conditions, or workforce
dynamics.
Enhanced Employee Wellbeing: AI predicts wellbeing risks, and suggests targeted
interventions, creating a healthier, more productive workforce.
Scalable and Efficient Programs: AI automates routine tasks in Total Rewards, from benefits
administration to performance recognition.

16. While AI can automate
many compensation tasks,
we still need human
insight and judgment.

17. The skills to
develop in
the age of AI

18. How to know when AI
or humans should be
doing the work
● Variables
● Feedback loops
● Outcomes and parameters

19. Can AI improve pay conversations?

20. AI’s future in compensation
• AI has entered the ”inner circle” in
C-suite decision-making
• Don’t turn your brain off
• Future roles of compensation

21. What should
you do next?

22. How to prepare: Try these publicly available tools tomorrow
Role Descriptions ● Draft a job description or ask for comparisons between two different jobs using ChatGPT.
● Upload several job descriptions to ChatGPT and identify job descriptions that are nearly duplicates. Ask ChatGPT to standardize the
description and highlight any areas of divergence.
Benchmarking ● Ask ChatGPT for other common names for a role in order to improve ability to find relevant market data.
Job Architecture ● Use a reasoning model (like ChatGPT Deep Research or DeepSeek) to generate a proposed job architecture.
Total Rewards ● Use ChatGPT to evaluate your total rewards offerings for competitiveness, completeness, and fairness.
● Ask ChatGPT to help you with phrasing and copy that will support pay transparency communications both directly from comp as well
as manager support tools.
Make sure to only include non-private data in public endpoints– treat them as if you were
posting on social media. Check with your Legal Department if unsure.

23. How to prepare: Set up for ongoing success
Privacy/Security ● Stand up an internal endpoint for a general-purpose AI tool like ChatGPT so that you can safely include more sensitive information
in your prompts
● Develop AI tool/vendor evaluation framework to assess data security and privacy
Innovation ● Create an AI committee of champions
● Experiment with task- or domain-specific AI tools within comfortable privacy/security limitations
Value/ROI ● Build a suite of test cases, with quantitative ways to measure the utility of AI suggestions from a given tool
Resources ● https://www.nist.gov/artificial-intelligence has excellent best-practice advice about how to assess data privacy, model accuracy, bias,
and overall risk

24. AI-Driven
Compensation
Management in
Payscale's
Products

25. The OpenAI maturity model for compensation
Systems with
conversational language
capabilities.
Chatbots
Capable of human-level
problem solving.
Reasoners
Systems that take
action based on
human instruction.
Agents
AI that can aid in
the direction of new
tools or ideas.
Innovators
1 2 3 4
AI that works
across teams and
systems.
Organizations
5

26. AI generated
job summaries
AI assisted support
(launching soon)
Chatbots
Payscale Verse
Payscale Pulse
Explore
Confidence scoring
Reasoners
Smart price (launching
soon)
Peer auto match
AI match suggestions
for surveys, pricing and
pricing at scale
Agents Innovators
Anticipating change &
architecting solutions
Intent-based workflows
Organizations
Anticipating change &
architecting solutions
Focused research
The OpenAI maturity model for compensation

27. Payscale’s AI Match Model
Easily and intelligently match your jobs to any data source you choose.
Now available!
Survey Year-Over-Year update Workflow in Payfactors
AI-match Suggestions in Marketpay
11.7 hours
saved per client on average
88%
of recommended matchers were accepted
30 seconds
is all it takes for the model to update job mismatches
Coming soon!
Price at scale in Payfactors & Marketpay
Smart Price in Payfactors

28. Peer Auto-Match
Participating in Peer can now be completely hands-off.
“The Peer Auto-Match functionality is awesome!
It effortlessly auto-matches jobs for us based on
multiple factors and has definitely been a time
saver for our team. The tool is especially helpful for
those of us who love working in compensation but
find the job matching process tedious.”
Shirley Rawson, Senior Compensation
Analyst, VF Corporation
Now available in Payfactors!
“ “

29. Job Description Manager can generate job
summaries using generative AI. This means you
can review and revise a solid draft and focus more
on collaborating with managers to ensure the job
description is accurate and the pay is right.
AI Job Summaries
Drafting job descriptions is now a breeze.
Now available in Payfactors JDM!

30. Introducing Explore—a groundbreaking
experience in Payfactors that brings
together the freshest market data and
powerful, tailored insights, transforming
how you interact with real-time
compensation information.
Explore +
Payscale Verse
Access intelligent insights at your fingertips.
Now available in Payfactors!

31. Now available in Payfactors!
Payscale Verse delivers intelligent
compensation insights at the click
of a button.
Explore +
Payscale Verse
Access intelligent insights
at your fingertips.

32. Questions?
Feel free to ask any questions in the
Q&A section of your dashboard!
Interested in a demo of
Payscale’s compensation
management solutions and data?
Let us know in the poll currently
open in the polling tab and the team
will be in touch!