Dr. Paige Bauer, PhD, is director, Global Corporate Advisory at Cleveland Clinic Canada. Dr. Talia Varley, MD, is managing director, Global Corporate Advisory at Cleveland Clinic Canada.
In business, artificial intelligence is becoming omnipresent. In fact, 93 per cent of organizations are using AI in some form, according to a KPMG report. While AI supports business efficiency and helps grow corporate top and bottom lines, we are seeing health and wellness ‘blind spots’ in companies implementing and integrating this powerful technology.
These blind spots are pervasive across sectors, job functions and all organization levels. They cut across a wide swath of the most pressing topics in business today – including mental health, culture and leadership – and have the potential to nullify corporate efforts to keep pace with the AI evolution and make good on AI’s efficiency and competitiveness gains.
As medical doctors and advisors in employee health and corporate performance, we believe these blind spots, when addressed with emerging best practices, can unlock both employee well-being and business value.
Key AI blind spots:
Mental health: We are seeing a significant and growing mental health burden, being driven by work-related stress, financial instability and a younger generation tackling high rates of mental health issues. Now, evidence demonstrates that many employees are also anxious that AI will replace their jobs, require time-intensive upskilling or stressful reskilling. Today, mental health disability claims make up 70 per cent of total disability costs, and organizations implementing AI report significant increases in requests for mental health support.
Burnout: AI is touted to reduce workloads so employees can focus on value-add tasks. However, research shows AI increases efficiency but the capacity created is often redirected to other work. A study in Harvard Business Review reveals that AI tools didn’t reduce work, they “consistently” intensified it. Employees worked faster, took on more tasks and stretched their hours. “That workload creep can in turn lead to cognitive fatigue, burnout and weakened decision-making,” said researchers. We also see companies making staff cuts in expectation that AI will make operations more efficient, before efficiencies are realized. The result is more work and anxiety for employees who remain.
Brain capital: There is a strong connection between brain health and productive workplaces. Yet over-reliance on AI, including delegating thinking tasks to AI, can lead to cognitive decline and reduced critical thinking skills. In addition, people who rely heavily on AI tools often report lower confidence and a weaker sense of ownership over their ideas. In the age of AI, companies must reinforce workforce cognitive health, retain brain capital and institutional knowledge and enable young employees to gain the experience and expertise required for their jobs today, and to grow their careers over time.
Psychological safety: Human judgment is an important safeguard against AI-related error, so employees must feel comfortable reporting concerns with AI implementations. Consequently, psychological safety must be embedded alongside AI implementation and transformation. Psychological safety enables employees to challenge the information that AI provides, ultimately to help make better decisions, and fuels experimentation to accelerate learning and innovation, which are increasingly needed in the AI era. If psychological safety is not present, employees may not speak up and AI issues will fester and grow rather than be addressed.
Leadership: AI implementations are complex. They require meticulous risk management, systems integration, scalability, staff training, governance frameworks, culture shifts and managing employee anxiety. The result? Leadership exhaustion and decision fatigue. In a recent survey, 38 per cent of CEOs report high or crippling stress around AI strategy. We are seeing senior leaders exit roles when they feel unprepared for AI-driven change, highlighting the need for executive mental health support, leadership training and succession planning.
A healthier AI transition
While these blind spots can be serious impediments to AI success, we consider them speed bumps, not road blocks. They can be mitigated and resolved through the adoption of emerging best practices in areas such as health and wellness, training, leadership and communication.
Many of these best practices address more than one blind spot and should be considered core tactics as companies embark on AI transformations. To maximize their benefit, these best practices should be layered on top of robust mental health and wellness programs, benefits navigation support and ongoing health engagement campaigns.
To successfully leverage health and wellness to support your AI transformation, consider the following:
Enrich training and cognitive support:
- Teach employees how to appropriately challenge, edit or reject AI-generated content. This instills greater employee confidence in using AI tools and stronger ownership over output.
- Expand training beyond the mechanics of AI tools to critical and analytical thinking, to support cognitive development among employees and drive organizational brain gain.
- Offer protected time within work hours to experiment with AI tools and provide low-pressure training, including lunch-and-learns, that build confidence and skills.
- Provide recognition for reporting AI inaccuracies and implementation issues that incentivizes a ‘challenger’ mindset.
Expand support for leadership:
- Train managers to hold supportive AI-related conversations with employees to reduce stress, anxiety, stigma and burnout.
- Ensure frequent pulse checks, one-on-one and team meetings, and segmented data reporting to executives to address anxiety, stress and health and wellness issues early.
- Provide additional training for leaders to enhance physical, mental and cognitive health to enable better on-the-job performance, including specialized resiliency training to help navigate change. Training should include future leaders in the succession pipeline.
Embed health expertise into AI transformation:
- Seek the support of health experts, including corporate medical directors, to help develop and implement effective AI-related health and wellness strategies.
- Ensure AI transformation planning includes pillars to safeguard psychological safety, mental health and cognitive health.
- Bring HR, IT and mental health and wellness teams into conversations about supporting AI learning and implementations in the workplace early, before issues arise.
Enhance communication:
- Develop and share a ‘case for change’ narrative to foster employee trust, reduce anxiety and get ahead of employee concerns. Include reassurances that psychological safety as well as health and wellness will be prioritized throughout the implementation process.
- Ensure consistent communication around the how, when and why of using AI. Discuss acceptable risks when using AI to reduce anxiety and generate employee confidence around AI use.
As the AI revolution gains pace, leaders need to be aware of the significant health and wellness implications that can either challenge or support AI transformation. By being aware of blind spots and taking action to mitigate them, companies reinforce their commitment to their people, their corporate culture and their business performance, all while prioritizing a successful AI implementation. With people driving 70 per cent of AI transformation value, health is a key enabler that companies cannot afford to ignore.
This column is part of Globe Careers’ Leadership Lab series, where executives and experts share their views and advice about the world of work. Find all Leadership Lab stories at tgam.ca/leadershiplab and guidelines for how to contribute to the column here.