Bridging AI and human values in pay and reward 

As humans we can often focus on the negative aspects of opportunity and highlight what could go wrong before we ever contemplate what could go right. The world of artificial intelligence (AI) seems to have arrived within our workplace and wider life with a rapid ease that you may well expect from technological progression, but if used correctly, AI opens up a world of possibilities and can allow professionals to spend more time on the softer skills and enhance the employee experience.

Evolving responsibilities

As AI continues to reshape industries, the role of pay and reward professionals is also evolving alongside this, as we are required to become more involved in aspects such as financial education and wellbeing, lifelong savings and employee benefits. From AI-driven performance evaluations to algorithmic compensation models, as professionals we are increasingly relying on technology to streamline decision-making. However, in this rush towards innovation, it’s crucial to maintain a balance between AI-driven efficiency and core human values such as fairness, transparency, and empathy. These are the matters that AI can complement, rather than replace.

Pay and reward professionals can bridge the gap between AI advancements and human values to create reward and recognition systems that are both data-driven, equitable and valued.

AI’s potential in pay and reward systems is immense. From predicting market trends and salary benchmarks to identifying patterns in employee performance, AI enables professionals to make more informed decisions. Some of the most common uses of AI in this area include:

• pay benchmarking: AI can analyse vast datasets to provide real-time insights into market salary trends, ensuring competitive pay structures
• performance management: machine learning algorithms can assess employee performance using data from various sources (eg productivity metrics, peer reviews, employee feedback) to recommend merit-based pay and workforce planning activities
• personalised rewards: AI can customise reward and recognition programmes to individual employee preferences, enhancing engagement and satisfaction

While these applications make pay and reward decisions faster and more data-driven, they raise concerns about fairness, bias, and employee trust. This is where we need to make sure that while the technology can inform decision making there will always be a need for human values. There are a number of different aspects to consider in balancing AI and human values.

Ensuring fairness

AI systems often rely on historical data to make predictions, which can unintentionally reinforce existing biases in compensation and rewards. For example, if past compensation decisions were influenced by gender, race, or other biases, AI algorithms trained on that data may perpetuate these inequalities.

This can be balanced off with human values to bridge the gap by:

• carrying out regular bias audits: always have the team continuously audit AI algorithms to identify and correct biases. Ensure that compensation outcomes are equitable across different demographic groups
• inclusive data sets: use diverse and comprehensive data sets to train AI systems, ensuring that they reflect a wide range of employee experiences and circumstances
• team oversight: while AI can provide data-driven recommendations, final decisions should involve human oversight to ensure fairness and context-specific judgment. This may involve panels to carry out additional reviews of outcomes.

Transparency and accountability

AI-driven decisions, particularly in pay and reward, can feel opaque to employees. When individuals don’t understand how their compensation or bonuses were determined, trust erodes, and this can often be the case where automation can often mean that communication breaks down.

The human approach to bridge this gap may require:

• understanding: develop systems that allow employees and managers to understand the logic behind AI-driven decisions. Simple, clear explanations can help employees feel more confident in the process
• open dialogue: maintain open communication about how AI is used in pay and reward processes with employees so that it is fully transparent. Employees should feel comfortable asking questions and receiving detailed answers about their pay.

Empathy in decision-making

While AI excels at analysing data and trends, it cannot replicate the emotional intelligence required to understand individual employee circumstances. Personal factors, such as family obligations, health challenges, or career aspirations, often play a role in performance and compensation discussions and will always need the human voice behind them.

Bridging the gap with human empathy can be achieved through:

• hybrid models: use AI as a tool to support decision-making, not to replace it. For instance, AI can flag trends in employee performance, but human managers should be involved in assessing the broader context and addressing personal factors.
• manager training: equip managers with the skills to interpret AI-driven insights alongside emotional intelligence. This can help ensure that employees are seen as more than just data points. Ensure that specific manager training courses always encourage the use of AI to better understand employees and trends but don’t let it be seen as a replacement for managers.
• employee enquiries: while AI may be able to facilitate the response to many employee questions, we all know how emotive pay is and there remains a place and purpose for the pay and reward team to be visible and approachable across the organisation.

Aligning AI with organisational values

AI systems must reflect the values of the organisation, especially when it comes to pay equity and rewards. This alignment ensures that AI enhances, rather than contradicts, the organisation’s commitment to diversity, equity, and inclusion.

Bridging the gap involves:

• ethical development: ensure through collaboration with developers that algorithms used in compensation and rewards align with the company’s core values and that recognition is being given for the right components
• policy integration: ensure that AI-driven systems adhere to organisational policies on pay equity and non-discrimination. Ethical guidelines should be part of the AI deployment process.

Data privacy and security

Remuneration data is highly sensitive, and employees may have concerns about how their personal information is being used. AI systems that process this data must prioritise privacy and security to maintain trust with employees and to remain aligned with the employee data privacy guidance.

Ways to offer assurance and bridge the gap include:

• robust security measures: implement strong security protocols to protect employee data from breaches or unauthorised access particularly where the use of AI may involve colleagues from wider functions across the business
• data minimisation: use only the necessary data for AI analysis and be transparent with employees about what data is being collected and how it is used. This can be captured in the Data Privacy Notice.

So, as pay and reward professionals we do want to be at the forefront of using AI to support employees and it is important that we continue to collaborate with the system and technology providers that support our profession to ensure that they are clear that this is the direction of travel we want to move towards, always ensuring it is done in an ethical way. 

We should see AI as we have with many technological progressions over the decades, as a continuous learning development and an opportunity to overlay it against our day-to-day duties. It doesn’t aways have to be big bang so talk to your system providers both internally and externally to see if there are opportunities to get involved in pilot initiatives and wherever possible use employees as the sounding board for the work. 

AI is already playing a big part in shaping the design of our pay and reward technologies, but it will always remain essential that these systems reflect the core human values that define a fair and inclusive workplace. By ensuring that AI complements human judgment and ethical standards, pay and reward professionals can harness the power of technology while fostering trust, equity, and transparency in compensation practices.