Artificial intelligence should not be used in employee remuneration just because it’s an exciting new technology.
“We need to identify real opportunities and problems first and then decide if and how we can apply AI to them,” says André Daniels, Chartered Reward Specialist and Exco member at the South African Reward Association (SARA).

Avoiding FOMO (fear of missing out)
Many South African reward professionals and employers might feel that they are being left behind, which could lead to panic-driven AI deployments. This mindset risks investing large amounts of time, money and resources into planning and implementing a solution that never yields a net positive result.

“The use of AI in remuneration should rather be purpose driven, focused on solving specific problems and creating tangible value, but not adopting it for its own sake,” says Daniels.  

Automation vs AI
Speaking at SARA’s 2024 Conference, Johan Steyn, founder of AI for Business, warned that AI should not be mistaken for automation. “There’s a very good chance that AI is not what you need to achieve efficiencies and effectiveness,” he said. After analysing a given problem, it may be found that simple automation is a more appropriate solution than AI.

AI can certainly contribute to efficiency, reward system transformation, bias and fairness measurement, annual salary reviews and streamlining other processes. Yet, it promises far greater utility than classic automation. 

Data utilisation
Daniels says he was inspired by Steyns’ presentation and assertion that AI is best utilised to discover meaningful patterns in corporate data.

Because of this, Daniels’ main focus currently is the value potential of AI in remuneration that lies in its ability to mine insights from remuneration and related data. In this way, it’s much like LiDAR, a laser mapping technology that can reveal archeological sites hidden deep underground.

“Similarly, AI can be used to reveal hidden patterns in remuneration data that inform powerful strategic decisions, reward policies, business processes and equity approaches,” says Daniels.

Building on flexibility
Even now, many organisations implement ERP solutions, usually at immense cost, only to see them fail to deliver the envisaged business-critical outcomes. Definitely, any AI-based implementation should be flexible enough to adapt to both current and future needs.

This will ensure that employers are investing in a bespoke solution that can evolve within its changing business environment, rather than something generic that doesn’t do everything it needs to.

Starting with the obvious
There is an opportunity to identify quick wins for some of the more obvious applications.

One is managing complexity. Do we really still need people to manually compile remuneration disclosures, or could an intelligent agent do this far more efficiently and accurately?

Another is managing bias. For example, can an AI model with access to an employee database carry out equal-pay-for-work-of-equal-value (EPWEV) analysis and judgements better than a human?

Or could AI help you refine your remuneration processes so that time-consuming admin and labour are eliminated?
Certainly, AI has been shown to quickly turn raw data into rich insights to inform and empower decision making at all levels of the organisation, including remuneration.

Beyond the obvious
After the quick wins, organisations can start looking at less obvious applications.

Could AI assist with the alignment of reward strategy to remuneration practices, ensuring cohesion between these concerns?

Might it also integrate remuneration with other HR practices, such as analysing the talent profiles of individual workers to help reward practitioners understand the reward preferences of a workforce? Or allowing them to understand how and when people prefer to be recognised?

Would employees, who sometimes feel embarrassed discussing their personal challenges with another human, find comfort in seeking guidance from an impartial AI agent? Not the limited chatbots with preprogrammed responses, but a language model that is trained to offer, say, realistic advice and assistance in a non-judgemental way. 

Starting off right
Before considering AI as a one-size-fits-all solution, organisations need to identify what they are doing that doesn’t add value or isn’t working, and opportunities to institute step change in their practices. What can they do that would take them to the next level?

This means identifying concrete business problems that must be solved or opportunities that may be exploited, rather than starting with an AI-first approach and expecting to retro-fit the model as and when required.

Only then should they consider which tools or solutions to employ - which may or may not include AI.

Involving reward professionals
For SARA, the burning question is: if AI is identified as a solution in remuneration, what is the role of the reward professional in the future?

This is critical because, if we cannot show them what their future looks like alongside AI, they see technology as an enemy that makes them redundant, and fear progress instead of embracing it. “However, if there is a shared vision of their role in the future, it becomes an exciting opportunity to work towards,” says Daniels.

With clarity on how the reward professional of the future adds value to the business, they can fully understand how to become better strategic enablers in organisations, and communicate their worth confidently.

ENDS
 
MEDIA CONTACT: Idele Prinsloo, [email protected], 082 573 9219, www.atthatpoint.co.za 
 
For more information on SARA please visit:
Website: www.sara.co.za 
X: @SA_reward
LinkedIn: South African Reward Association
Facebook: SARA – South African Reward Association

The launch of ChatGPT late in 2022, and the tremendous interest it provoked, inaugurated what one will one day see as the Age of Artificial Intelligence (AI). AI will make it easier to generate outputs in virtually every industry, creating a challenge for reward professionals: how does one measure an individual’s performance when one of his or her outputs can be generated by an algorithm?
 
“AI is here to stay, and we can expect it to get significantly better. Reward professionals should see it as a great opportunity to refine their thinking about what constitutes great performance, and thus how to reward it,” argues Dr Mark Bussin, Master Reward Specialist and Executive Committee Member of the South African Reward Association (SARA). “Specifically, AI prompts us to look at what humans do best and use that insight to determine how we measure and reward our people.”
 
Dr Bussin offers the following tips to help reward professionals, and HR more generally, to use the AI revolution to the advantage of their organisations:
 
Focus on creativity, quality and innovation. AI is going to be a great tool for automating routine tasks, but when it comes to creative problem-solving or generating innovative ideas, it is a non-starter. Finding ways to reward individuals or teams for creativity rather than output would be beneficial to both the employees and the organisation.
 
Similarly, reward professionals should look for metrics that measure quality rather than quantity. For example, customer satisfaction or product ratings could be used to assess the performance of an individual or team.
 
Emphasise collaboration. Humans have leveraged the power of collaboration to overcome seemingly insurmountable challenges over thousands of years. Encouraging individuals or teams to work together and rewarding them for doing so will play to humanity’s strengths and will generate excellent results.
 
Provide a sense of purpose. Humans are motivated to perform better when they feel their work is making a positive impact—AI is just a machine. Global research shows that purpose-driven companies realise huge benefits. Making sure the organisation has a clear vision and purpose can motivate employees to do their best, and ultimately drive the company’s performance in achieving its strategic goals.
 
Develop policy guidelines relating to the use of AI. Everybody in the organisation needs to know how AI should—and should not—be used. Each industry will have its own set of ethical issues, and employees will need charts to navigate this tricky terrain.
 
Provide professional development opportunities. It’s long been recognised that professional development is a key lever when it comes to attracting and retaining top talent—and driving high performance. Alongside providing policies to guide employees, organisations must provide employees with ongoing training in this rapidly changing technology and what it means for them. They will use it better and, as an added bonus, they will be more likely to remain with, or want to join, the organisation.
 
Use AI to speed up the drafting of reports and policies. Finally, HR and reward professionals themselves should find ways to use AI to make themselves more efficient. Freeing up more time to be devoted to adding value will also protect their own positions.
 
“The onward march of AI is in fact an opportunity for us all, and reward professionals in particular, to concentrate on the things that humans do best and focus on supporting them—leaving the drudge work to the machines,” Dr Bussin concludes.
 
ENDS

MEDIA CONTACT: Rosa-Mari Le Roux, [email protected], 060 995 6277, www.atthatpoint.co.za 
 
For more information on SARA please visit:
Website: www.sara.co.za  
Twitter: @SA_reward
LinkedIn: South African Reward Association
Facebook: SARA – South African Reward Association

​Companies need an internal committee as well as an industry body to ensure artificial intelligence (AI) is used responsibly for HR processes within their business and by their service providers.
 
This is according to Carmen Arico, Chartered Reward Specialist, and spokesperson for the South African Reward Association (SARA). "AI is not yet mature enough to be entrusted with the ethical nuances of HR without human intervention and close supervision," she says.
 
While AI promises an exceptional productivity boost across HR functions, it should not be implemented without proper policies, oversight and safeguards in place.
 
AI in HR
AI has a wide range of applications within HR. These include creating job descriptions, sourcing applicants, analysing CVs, filtering candidates, scheduling interviews, and even analysing facial and vocal responses during interviews.
 
After a new hire is onboarded, AI can be deployed in areas such as skills development, reward design, performance reviews, wellness assessments, and more.
 
Arico is firmly opposed to AI handling much more than rote HR administration. "When you apply the technology in areas that are too subjective even for humans, like gauging deception from facial expressions or confidence from voice tone, you're straying into dangerous legal territory," she says.
 
AI security
Arico is also concerned with how personal information may be used, and how easily it might be exposed by those who know how to bypass the shallow security barriers set by AI developers.
 
"Ask for private information directly and the model might refuse on moral grounds, but rephrase the request as a plot to a fictitious story and, in that context, it could freely share everything it knows about an employee," says Arico.
 
In addition, AI models learn from historical data that can often be littered with biases and falsehood. Will it suggest only male candidates for an occupation previously dominated by men; exclude a certain minority group if it has insufficient training data on that demographic; or reject a candidate who is neurodivergent because they don't fit a traditional psychometric profile or respond to social cues in a traditionally accepted way?

Internal committee
Arico says that corporate HR must understand how AI works and what its shortcomings are, develop policies for the scope of its use, and provide safeguards to mitigate any associated risk.
 
Most importantly, companies must establish an internal steering committee tasked with ensuring AI is employed responsibly and ethically across their organisation and throughout their supply chain.
 
This means their policies and practices must consider how AI is used by external HR service providers, such as recruitment specialists, head-hunters, training partners or reward consultants.
 
Industry body
Arico believes this can best be achieved through the establishment of a regulatory body that sets shared standards on the ethical and responsible use of AI, not just in HR but across all management functions and industries.
 
"Members will participate in the development of these standards and bind themselves to their universal implementation to ensure AI is a blessing and not a curse to business and employees and can conform to agreed-upon ethical and moral standards," she says.
 
Arico also advises that for the body to be effective, it should be led by neuroscientists, data scientists, AI researchers, AI ethics experts and another top talent in the AI space.
 
“A certification, similar to ISO 9002, would not only identify companies as responsible AI users but also act as a differentiator in what will soon be a highly competitive market,” she says.
 
ENDS

 
MEDIA CONTACT: Rosa-Mari Le Roux, [email protected], 060 995 6277, www.atthatpoint.co.za 
 
For more information on SARA please visit:
Website: www.sara.co.za 
Twitter: @SA_reward
LinkedIn: South African Reward Association
Facebook: SARA – South African Reward Association