Getting started with AI-enabled rewards? Start here 

Start by demystifying AI for your team. It can be intimidating for people who are unfamiliar. Training sessions should cover the basics of how AI works, where it can add value and how it integrates with your existing processes. For example, your team might attend Mercer’s AI Essentials for HR  to become more acclimatised in the technology. The goal is to make AI feel less like a black box and more like a helpful teammate. 

AI is evolving rapidly, which means your team’s knowledge needs to keep up. Encourage ongoing learning through workshops, webinars and even certifications. Create an environment where team members can experiment, learn and become more confident in their own AI literacy. Consider designating a team member — or an entire role — to focus specifically on staying ahead of AI advancements.

Focus on tasks and challenges that are time intensive, repetitive or prone to human error. These are ideal opportunities for AI to lend a hand. Start with areas that deliver immediate impact, and scale from there.

Not all AI tools are created equal, so take the time to do your research. What problems are you trying to solve? What outcomes are you hoping to achieve? Look for applications that align with your organisation’s goals and that incorporate features like predictive analytics, skills insights or automated performance tracking.

The good news is you might not need to start from scratch. Many HR platforms already have built-in AI functionalities. Start there — it’s a great way to dip your toes into AI without committing to a massive tech overhaul. If this feels overwhelming, an expert from Mercer’s Data Analytics team can help you prioritise, select and get up to speed on solutions. 

One thing AI excels at is helping you connect with employees in more meaningful ways. For instance, AI-driven tools can be used to simplify HR policies and respond to frontline employee questions, making the employee experience less one-size-fits-all and more tailored to employees’ unique needs.

The trick here is to prioritise areas where AI can add immediate value. If your team is constantly swamped by manual processes or struggling to make sense of mountains of data, those are good places to start. This will help you get some quick wins under your belt before tackling the bigger stuff. You can always reach out to your Mercer team to identify the best starting point and strategy for your organisation.  

As you experiment within your sandbox, document learnings, identify gaps in your data, iterate based on feedback and gradually expand your initiatives. This approach not only minimises risk but also builds a strong foundation for scaling AI’s impact across your organisation. By starting small and methodically, you will create a practical and agile strategy that evolves with your team’s needs and capabilities.

Once you have your sandbox established and have started to build a track record of success, you can expand it to focus on broader AI use cases. Below is a list of ways AI can lend a helping hand in rewards.

• Benefits administration: Streamline enrolment processes, manage routine enquiries and ensure compliance with changing regulations.
• Compensation analysis: Identify pay gaps, optimise salary structures and predict future compensation trends.
• Manage compensation adjustments: Leverage AI to drive more consistency in salary levels for new hires and streamline decision-making across your employee population for the annual salary adjustment process. For example, Mercer offers Pay AI and Merit Co-Pilot solutions to help teams leverage AI for better compensation decisions.
• Pay equity audits: Detect and address disparities in pay to ensure fairness and compliance with transparency regulations.
• Performance management: Automate performance tracking, identify high performers and align rewards with contributions.
• Job description optimisation: Generate or refine job descriptions to ensure alignment with organisational needs and skills frameworks.
• Personalised employee rewards: Tailor benefits and recognition programmes to individual preferences based on data-driven insights.
• Retention and turnover analysis: Use predictive analytics to identify at-risk employees and proactively address their concerns.
• Workforce planning: Forecast future talent needs, and align rewards strategies with long-term business goals.
• Employee sentiment analysis: Analyse feedback to gauge employee satisfaction with total rewards programmes and identify areas for improvement.

AI governance isn’t something rewards teams can tackle alone. Bring together a cross-functional team that includes HR, IT and legal experts to create a balanced approach. Each group brings a unique perspective, from ensuring compliance with data privacy laws to managing technical risks.

Even the best AI tools can reflect or amplify unfairness if left unchecked. That’s why continuous monitoring is essential. Build in mechanisms to ensure objectivity in your AI models, whether through regular audits or by leveraging external experts.

Choose a specific area or project for your pilot — something manageable but impactful. For example, you might start with streamlining your job descriptions or by using AI to analyse pay trends and identify pay gaps.

During the pilot, collect feedback from both your team and employees. Are there gaps in your data? Is your team missing key knowledge or skill? Are the tools easy to use and delivering the expected insights or efficiencies? Use this feedback to fine-tune your approach before expanding.

Regularly review the impact of AI on your rewards processes. Are you saving time? Improving accuracy? Enhancing employee satisfaction? The more you measure, the better you can optimise.

AI and workforce dynamics are constantly evolving. Be prepared to adapt to new technologies, methodologies and employee needs. The organisations that succeed with AI are the ones that stay flexible and open to change.