Artificial intelligence (AI) is no longer a futuristic concept; it’s a reality. It's becoming a practical tool for HR teams when strategizing compliance and compensation. For professionals navigating pay transparency laws, shifting employee expectations and tight labor markets, AI offers both opportunities and questions.

• How can AI support more equitable, strategic compensation decisions?
• How do we ensure that automation complements, rather than replaces, human insight?

This post explores how AI is changing compensation practices, with a focus on actionable use cases, ethical considerations and tools that balance innovation with accountability.

Moving from Manual to Intelligent Compensation Planning

Historically, compensation programs have relied heavily on spreadsheets, static benchmarking data and manual calculations. While these methods have served HR well, they lack agility, especially when responding to real-time labor market changes or tightening compliance standards.

AI can enhance compensation planning by using algorithms to detect patterns, automate modeling, and suggest adjustments based on real-time data inputs. For instance, some platforms use AI to analyze compensation by role, geography, tenure and performance to flag potential pay gaps or outliers, allowing HR to course-correct before decisions are finalized.

In New England, where states like Massachusetts and Connecticut have strong equal pay laws, this kind of real-time visibility is particularly valuable.

AI’s Role in Fairness, Not Just Efficiency

While automation can speed up routine tasks, AI's true value in compensation lies in fairness and foresight.

Equity Monitoring: AI-powered tools can continuously monitor for pay inequities across demographics, job levels and departments. This is critical as more states adopt or strengthen pay transparency requirements. AI models can surface patterns early, giving HR time to address them with targeted reviews and policy updates.

Market Benchmarking: Modern AI tools can digest vast external datasets to help HR compare salaries by role and region. For example, AI systems trained on public salary databases and job postings can suggest competitive salary bands based on real-time market conditions.

Scenario Planning: When preparing for budget season or merit cycles, AI-driven simulations can project the financial impact of various pay scenarios, allowing HR leaders to balance fairness, performance and cost-effectiveness without endless spreadsheet revisions.

Total Rewards Communication: Some platforms use generative AI to craft personalized total rewards summaries, helping employees better understand the full value of their compensation beyond just salary. This fosters transparency and boosts retention.

Proceeding Responsibly: AI and Ethical Guardrails

With all its benefits, AI in compensation requires careful oversight to avoid human error. If left unchecked, AI models can perpetuate historical bias, especially if trained on outdated or non-inclusive data sets.

Key practices for responsible AI use include:

• Transparent decision-making: Make it clear how data is used and how models arrive at recommendations
• Regular audits: Continually test AI tools for unintended bias or drift
• Inclusive data sources: Use diverse, high-quality datasets that reflect your workforce demographics
• Human oversight: Always include people in the loop for final decision-making, especially for sensitive areas like pay
• Data privacy and security: Treat pay data with the highest level of confidentiality, ensuring compliance with data protection laws and implementing safeguards against unauthorized access

At its core, AI should be a co-pilot, not a replacement for thoughtful HR leadership.

Real-World Application: Tools That Support Smart Compensation

Implementing AI doesn’t require a massive tech overhaul. Many organizations begin with modular tools that support specific use cases, like equity analysis or scenario modeling, before expanding adoption.

Some platforms offer embedded analytics and compliance tools that simplify compensation planning while keeping people at the center of decision-making. These types of systems can support HR teams in navigating complexity without overwhelming them.

The broader takeaway is this: choose tools that emphasize clarity, ethics and usability.

Looking Ahead: AI as a Strategic Advantage

For HR professionals in New England and beyond, AI presents an opportunity to elevate compensation from a tactical task to a strategic differentiator. In a labor market where transparency, trust and equity are top priorities, the ability to make fast, fair and data-informed decisions is a competitive advantage.

But technology alone isn’t enough. The future of compensation will belong to HR teams that combine intelligent systems with human empathy and a clear commitment to fairness.

 Reannah Gilenson, Sr. Director, Solution Strategy, isolved 

Reannah Gilenson is the Senior Director of Solution Strategy at isolved, where she spearheads product marketing, go-to-market execution, and solution evangelism across the company’s HCM portfolio. With more than 20 years of experience—including over a decade focused on HR and benefits technology—Reannah is passionate about helping organizations turn complex innovation into practical solutions that truly support people and performance. She specializes in crafting go-to-market strategies that connect with real-world HR challenges, drive adoption, and elevate the employee experience. Reannah is also a dedicated mentor and coach, known for building inclusive teams, supporting emerging leaders, and championing equity at every stage of the employee journey. A longtime advocate for thoughtful, human-centered work cultures, Reannah brings both strategic insight and hands-on experience to every conversation—making her a trusted voice for those navigating the evolving world of work and benefits.