Despite all the disruption and challenge that total rewards leaders have experienced globally in recent years, their fundamental goals haven’t changed. These leaders remain steadfast in their ambition to use total rewards — pay, benefits, wellbeing and careers — to create value for their organizations.
Yet, in today’s environment, many total rewards teams are finding it difficult to deliver on this ambition. They are waist-deep in sorting through compliance requirements and employee escalations, and they’re feeling more pressure to prove returns for even incremental investments in strategic priorities.
So, we ask, “Can recent advancements in artificial intelligence (AI) materially impact the total rewards functions and help them achieve their strategic ambitions? And if so, how and when will we see progress?” There are some obvious opportunities, such as chatbots for responding to employees’ queries and copilot-like tools that make everyday jobs a bit more efficient. But what else is there?
AI in total rewards: Uncovering the opportunities
We see three principal ways AI could radically change the landscape of total rewards and create value for businesses:
- Enhancing the employee experience by ensuring employees know and understand available programs and how to use them more effectively
- Creating relevant and intelligent insights to make informed cost/benefit decisions regarding the design, financing and delivery of total rewards programs
- Improving operational efficiencies to optimize your resources
AI in total rewards: Enhancing the employee experience
Fostering the physical, financial and emotional resilience of the workforce makes good business sense. Meeting that goal requires going beyond offering programs that suit the diverse needs of an increasingly diverse workforce. Employees also must be reassured that they’re treated fairly and equitably. And they must effectively engage with their total rewards programs.
AI can enhance the employee experience by:
- Offering clarity and transparency on employees’ total compensation and accessible career pathways best suited to their skillsets and improving employee awareness, understanding and appreciation of benefits programs (using hyper-personalized content — which can be more easily created with generative AI — and chatbots)
- Guiding employees through complex decisions such as which benefits programs to choose and how to make the right career choices. Using hyper-personalized data-driven prompts and nudges, total rewards leaders can help employees make the most of the offering and accommodate employees’ changing needs throughout their career and different life events
- Helping employees effectively navigate change with personalized content and proactive navigation touchpoints
- Supporting managers in efficiently and accurately addressing employees’ questions and challenges. Chatbots specifically tailored for managers can help minimize individual biases and reduce the amount of time they spend on administrative tasks. Machine learning can help streamline performance and pay recommendations
AI in total rewards: Creating relevant and intelligent cost/benefit insights
Given the significant amount of investment total rewards budgets require, leaders must ensure money is spent wisely. Recent capabilities in AI to analyze vast amounts of data to provide more meaningful insights (e.g., extracting and analyzing content from an unstructured document at scale) can significantly enhance strategic decision making in total rewards. For example:
- As employees become better consumers of employment in an age of greater transparency and social media, perceived values matter just as much as the economic value of programs. Using insights from publicly available data (e.g., social media) and employee-specific data (e.g., open-ended comments in engagement surveys), companies will be able to align total rewards spend on what matters to employees
- AI-enabled to/from talent flow analysis can help total rewards leaders improve the accuracy of peer groups for benchmarking and redirect costs to programs that affect attraction and retention
- Companies now can ingest and process large data sets (structured and unstructured) along with predictive models. This will help companies analyze employees’ choices, behaviors, outcomes and, more importantly, take targeted remedial actions (e.g., redesign programs and communications) leading to lower costs and better overall health and workforce resilience
AI in total rewards: Optimizing your resources
Total rewards teams often expend significant resources on administrative tasks such as responding to employees’ queries, collecting data and producing reports. Beyond the obvious, such as content creation, companies now have the opportunity to use technology and automation to achieve a better balance between the strategic and administrative. Such opportunities include:
- Significantly reducing the number of hours leaders spend reading, reviewing and extracting information from complex documents. AI can provide summaries of relevant information, such as key plan/policy provisions, eligibility, coverage, inclusions/exclusions and rules and regulations
- Responding to most employee and manager queries with generative AI, using both internal and external data sets
- Consistently applying standardized approaches for routine processes and activities (e.g., creation of job descriptions and updates to skills libraries and inventories), reducing routine tasks and freeing time for strategic thinking
What’s next?
While the promise for AI to deliver on the above ambitions in total rewards is exciting, many who are already using these advanced technologies have faced several challenges, including:
- The output from AI and advanced technologies can be inaccurate or biased, which then requires the process to have a person involved to mitigate risk
- Connecting data sets across multiple sources (e.g., internal and external/third-party systems) isn’t a simple exercise. In some countries, organizations face data privacy challenges that hinder progress. And in other instances, organizations don’t have the technology infrastructure to address data security or data management requirements
- The market has been inundated with new products, solutions and offerings, many of which were developed with niche intent and application. Weaving together different point solutions can be challenging
- In some ways, AI is so powerful that its information and insights can be overwhelming if not properly targeted. Total rewards leaders must first identify the high-value questions to ask and clearly define priorities
Total rewards leaders shouldn’t just focus on what they intend to adopt in terms of technology, but also consider how and when they will get there.
Recent data from our July 2024 edition of our Salary Budget Planning Survey suggests that less than 10% of total rewards leaders have begun to explore how AI can support their priorities in pay, benefits, wellbeing and careers. This presents an opportunity in the market to achieve a competitive advantage for leaders who embrace AI. Getting it right will take time, effort and resources (like any other technology adoption), but there’s tremendous upside potential. The path may not be fully clear yet, but the opportunity is real.
