AI is the game changer driving incentive programs for users and a huge determinant of business sustainability for years to come. Over the years the need for improving incentives programs for users using transformative technology has been significant, given it has come to stay in setting the trend for designing the perfect employee, customer loyalty and channel rewards program.

Incentive planning used to be broad and not user focused. Traditional incentives can take a one size fits all approach and not sustainable for the new demographic of users in the market. IRF (Incentives Research Foundation), indicates that according to the data from the US Department of labor, together Millennials and Gen Z (aged 16-44) are expected to account for 60% of the workforce by 2025. In Africa, the total population size is projected to hit 1.5 billion by 2025 having the working population grow by 3% annually which is headed for a projected 2.4 billion people by 2050. 60% of the African continent’s population is under the age of 25.

Traditional incentive plans have gradually evolved into more advanced programs that leverage technology, delivering even better results for organizations. The IRF trends report for 2024 quoted the June 2023 issue of Academic Research in Action, stating that, AI can be used to enable greater personalisation of rewards and shift towards true individualisation, tailoring travel experiences and merchandise rewards to specific employees. While incentives are designed for an improvement in performance across the board for organisations, recent trends such as the “silent quitting” has given awareness to prioritising the incentive needs of the younger generation as a large consideration.

Standardized reward solutions are less appealing to the younger generation compared to their appeal to the older generation. The importance of individual preferences now plays a huge role in program design. The use of AI enables the analysis of individual behaviors and preferences, offering valuable insights for creating personalized incentives.

The use of AI has refined program adaptability with its flexible nature. Traditional incentives used to be fixed, structured and pre-determined. Effecting change would require a chain of events which would include re-communication impacting timelines. AI operates in real time, using machine learning to identify user behaviours and apply program management strategies which are effective and on time.

Traditional incentive planning relied heavily on historical data to determine program dynamics, such as user preferences, and predicting the program’s success remained uncertain. With AI, predictive analytics has revolutionised participant behaviour forecasts. AI can promptly identify disengagement behaviors and address them with tailored rewards and offers to maintain user engagement.

With the use of AI, program feedback systems have experienced a huge change in real time. The days of manually sending out surveys and questionnaires for program feedback, only when the program has ended, is over. With the use of surveys, reviews and social media, AI saves time and provides vital information that can improve user experience. This feedback allows for quick decision making and program adjustments for better results.

AI enhances gamification with adaptive mechanics. The former incentive program approach is to use fixed elements like points, leader boards, and badges to encourage engagement. These elements often lead to participant burn-out over time if rewards don’t evolve. AI has made gamification more dynamic by adjusting game mechanics in real time. An AI-driven program can automatically adjust difficulty levels, award extra points to underperforming participants, or introduce new challenges for highly engaged users. This dynamic approach keeps gamification engaging over the long term, sustaining users’ interest

While traditional incentives had limitations due to operating in silos making engagement data fragmented across platforms, AI enables seamless integration across multiple digital channels. Users can engage with programs on social media channels, in mobile apps, on websites and more. AI tracks engagement via these channels, giving users a unified experience that enables them earn rewards with no hindrance.

There is also an improvement in reporting and performance measurement. AI now provides real-time reporting and insights on program performance, participant engagement, and ROI. These elements are crucial for making data-driven adjustments while running incentive plans. They allow for proactive program management, enabling changes as needed during the program’s execution, rather than waiting until the end to analyze the results. This approach helps ensure that the program remains effective throughout its duration.

Conclusively, the use of AI in program management is having a significant impact on addressing user performance and talent retention challenges. AI has made incentive programs more dynamic and personalized, which is particularly appealing to the younger workforce. The time management advantage offered by automated adaptive systems, as opposed to manual alternatives, enhances user engagement by resolving issues in real time. Overall, this approach has made incentives more effective in motivating behavior, while streamlining management processes, reducing costs, and increasing program impact.