AI-Powered Workplace Wellness Works Best When Managed by PeopleAI-Powered Workplace Wellness Works Best When Managed by People
Employee experiences are already changing every day thanks to AI. It's up to human managers to determine whether AI is shaping those experiences for the better.
As graduation season unwinds and this year's crop of aspiring employees is released to the job market on a flood of well-intentioned advice, let's divert our energies and check in with the currently employed.
Specifically, let's check in on their employee experience. You'll recall that the massive remote work shift in 2020 amplified the need for a digital platform that allowed workplace strategists and managers to gauge employee engagement, collaboration, and well-being. Enter the employee experience platform (EXP).
While estimates on its growth differ -- Zion Market research pegs the EXP compound annual growth rate at 9.80% through 2032 while Global Market Estimates projects The global employee experience platform market is projected to grow at a compound annual growth rate of 11.5% from 2023 to 2028 -- the trendline indicates EXPs are part of the collaborative technology stack. Now that employee experience platforms are integrated into wider enterprise communications platforms, there are two questions we can ask: Are these platforms really boosting employee well-being? And how will the increasing integration of AI in every aspect of the enterprise affect employee experience?
EXPs often include wellness components such as physical, mental, emotional, social, occupational, and financial well-being tools. For example, Microsoft Viva Insights has an employee well-being tab that allows people to identify behaviors linked with improved well-being (higher control over their time, taking breaks) and support the adoption of those behaviors.
However, an October 2024 study in the Harvard Business Review argues that as they're implemented now, workplace well-being programs are not doing well:
Nearly 85% of large U.S. employers offer workplace wellness programs, yet the burnout and mental health needs that they are meant to address have continued to escalate. By 2026 global corporate spending on wellness is set to top $94.6 billion. Despite this substantial investment, anticipated improvements in well-being are not being realized. This mismatch between increased money spent and declining mental health outcomes prompts a crucial question: why aren’t workplace well-being programs achieving better outcomes?
The culprit, as study coauthors Jazz Croft, Acacia Parks and Ashley Whillans write, is:
The lack of impact of well-being programs is explained in part by a focus on the individual employee rather than the systems that affect them. To tackle the challenges employees face, we argue that there must be a shift from individual-level interventions (“I-frame”), like well-being apps, AI chatbots, and employee stress management training, to broader systemic interventions (“S-frame”), such as workload management and mental health development training for leaders.
AI could make EXPs more effective by leveraging its superlative pattern recognition abilities. By looking at workload management and by analyzing trends in individual and departmental scheduling, an AI tool could identify crunch periods for different departments, look for relationships between work overloads and other factors, and send up alerts when conditions inimical to workplace wellness begin to appear or recur.
Of course, in order for the AI to be genuinely effective, human managers need to take an honest look at how many of the tools incorporated into EXPs are meant as individual-level solutions versus tools to refine and optimize a healthier working environment.
A good example of AI as an individual-oriented solution in an EXP would be an automated onboarding routine for a new employee. However, take a minute to think about what message this sends to the employee about their value to the company -- not even worth a human being's time for introductions! -- and what an automated onboarding tells the new employee about company culture, communication and accountability.
By contrast, an AI tool in an EXP that takes a systemic approach might use predictive analytics to flag to a manager that the team's about to enter a crunch time, then offer advice on how to reduce extra work and who to work with to prevent or adjust similar crunches in the future. The burden is off the individual to manage their own burnout and the company culture is both nimbly responsive and proactive.
Employee experiences are already changing every day thanks to AI. It's up to human managers to determine whether AI is shaping those experiences for the better.
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