Beyond Traditional Surveys: AI-Driven Approaches to Wellness Assessment

Introduction
Employee wellness has evolved significantly over the past few decades (Marsburg, 2022; Martela & Sheldon, 2019). Traditionally, workplace wellness programs focused mainly on physical health, offering benefits like gym memberships and health screenings. However, as the world of work transforms, driven by rapid technological advancements and shifting employee expectations, wellness now encompasses mental, emotional, and even financial well-being as essential components of holistic employee wellness. Recognising this evolution, organisations are increasingly viewing wellness not just as a driver of engagement, productivity, and retention but as a foundational element for cultivating the future skills needed to thrive in tomorrow's workforce. In South Africa and globally, employee well-being has become a strategic priority tied to broader business outcomes and future talent strategies. Companies are moving beyond annual employee engagement surveys and yearly health assessments tools that, while informative, lack the frequency and depth required to address the dynamic needs of a workforce preparing for an uncertain and fast-changing future. The demand for continuous, real-time insights reflects the growing recognition that adaptive and proactive wellness strategies are critical for developing the resilience, creativity, and collaboration skills that will shape the talent of tomorrow.
Assessment Centre Practitioners, too, must evolve to meet this demand, integrating advanced tools and methodologies that align with the future-focused priorities of organisations. Traditional tools, like periodic surveys, capture only a limited view of employee well-being, falling short of providing the actionable, real-time data required for proactive intervention. This has created a pressing need for innovative approaches, such as AI-driven wellness assessments, that leverage passive data from multiple sources. By continuously gathering and analysing data, these assessments provide the comprehensive insights required not only to enhance employee wellness but also to identify and cultivate the key skills and attributes that will define future-ready talent.
Objectives
The session aims to explore the practical application of AI-driven wellness surveys that analyse passive data from external sources to assess employee well-being. Through real-world case studies, participants—particularly Assessment Centre Practitioners—will gain insight into how these AI-powered assessments are applied in various organisational contexts to measure and improve wellness.
Theoretical Foundation
AI-driven wellness assessments draw on an integrated theoretical framework that combines well-established perspectives, including Self-Determination Theory (Deci & Ryan, 2000), Subjective Well-being (Diener, 1984), psychological well-being (Jahoda, 1958; Ryff, 1989), and the PERMA model (Seligman, 2011). This framework captures both internal mindset factors—such as emotional well-being, motivation, and resilience—and external contextual factors, including organisational culture, work environment, and personal influences. Together, these dimensions create a holistic view of employee wellness, recognizing that both psychological states and situational factors shape workplace experiences. By integrating these theoretical foundations with AI technology and statistical methodologies, AI-driven wellness assessments provide a comprehensive and validated approach to measuring employee well-being and engagement.
Implications for Practitioners
For Assessment Centre Practitioners and HR professionals, AI-driven wellness tools offer a transformative approach to measuring and managing employee well-being and engagement. These tools use passive data collection from external sources, minimizing the need for intrusive surveys and enabling a more objective and continuous assessment of wellness. Real-time data insights empower practitioners and HR teams to make proactive, data-driven adjustments to wellness and engagement strategies tailored to meet the workforce's evolving needs. This session will introduce Assessment Centre Practitioners to innovative wellness measurement techniques that they can incorporate into their toolkit, supporting a more dynamic and responsive approach to employee well-being.

References

Deci, E. L., & Ryan, R. M. (2000). The “What” and “Why” of Goal Pursuits: Human Needs and the Self-Determination of Behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01
Diener, E. (1984). Subjective well-being. Psychological Bulletin, 95(3), 542–575. https://doi.org/10.1037/0033-2909.95.3.542
Jahoda, M. (1958). Current concepts of positive mental health. Basic Books. https://doi.org/10.1037/11258-000
Marsburg, A. (2022). Development and evaluation of a longitudinal dynamic needs-action model of employee well-being: A psychological perspective. Unpublished PHD dissertation. Stellenbosch University. South Africa.
Martela, F., & Sheldon, K. M. (2019). Clarifying the concept of well-being: Psychological need satisfaction as the common core connecting eudaimonic and subjective well-being. Review of General Psychology, 23(4), 458–474. https://doi.org/10.1177/1089268019880886
Ryff, C. D. (1989). Happiness is everything, or is it? Explorations on the meaning of psychological well-being. Journal of Personality and Social Psychology, 57(6), 1069–1081.
Seligman, M. E. P. (2011). Flourish. A visionary new understanding of happiness and well-being. Wiley.