Most conversations about AI focus on efficiency: how fast people can work. How many tasks can be automated? How much productivity can AI deliver?
But hidden within these questions is a growing risk. As technology accelerates work, it also accelerates decision-making, information flow, customer expectations, and the cognitive demands placed on employees. I’ve noticed this while working with teams across a variety of industries, many of whom report being exhausted by the uncertainty and speed of change. We also realized that focusing only on efficiency is not enough. Leaders who succeed in integrating AI will be those who ask a different set of questions that focus not only on the technology, but also on the conditions needed for people to thrive with the technology.
AI and sustainable performance—what the research reveals
AI will not only change the way work is done, but what humans must do to perform well. While AI can create important efficiencies, leaders also need to be aware of how its use can impact cognition, care, and connection.
A newly published study introduces the concept of AI Brainfly. This is a state of cognitive fatigue from managing too many AI tools at once. Researchers found that professionals who regularly manage three or more AI tools simultaneously are more likely to experience cognitive overload.
Another study found that the most productive AI users were 88% more likely to experience burnout and disengagement, and twice as likely to quit. The same study found that 90% of workers view AI as colleagues, 67% trust AI more than co-workers, 64% say they have a better relationship with AI than their human teammates, and 54% say AI is more empathetic.
Separately, researchers looked at how AI tools changed work habits at technology companies over an eight-month period. Although the company did not mandate the use of AI, it found that its employees were working at a faster pace, working longer hours, and taking on a wider range of tasks. This seemed like a win until I also discovered scope creep, work slop (AI-generated output that puts extra cognitive and emotional load on colleagues who can’t move projects forward and needs to fix and redo), constant pressure to deliver more, and loss of recovery time and deep thinking.
Over time, the researchers noted, this overwork can impair judgment, increase the likelihood of mistakes, and make it difficult for leaders to tell the difference between true productivity and unsustainable intensity. What is needed are clear practices for AI, clear norms and routines that add structure to how AI is used.
AI and workload sustainability: 5 questions leaders should ask
Concerns about job performance and sustainability must also be addressed in conjunction with technology integration and governance. As the use of AI increases, leaders and busy professionals should keep these five questions in mind.
- How will AI-powered workflow changes impact workload sustainability, cognitive performance, and burnout risk?
- What is the impact of hybrid human-AI teams on psychological safety?
- As automation increases, how can leaders redesign their roles to protect well-being and connection?
- What team communication norms prevent overload in an AI-heavy environment?
- How should roles be redesigned or reclarified?
Here is an overview of the potential job sustainability risks created by AI.
- Cognitive overload: Continuous new tools and updates
- Increased workload: Further review/correction tasks and expectations
- Employment insecurity: Fear of replacement by automation
- role ambiguity: Performance standards are unclear
- Work-life ambiguity: Always-on tools and alerts
- social isolation: Decrease in human interaction
- skill pressure: Request for skill improvement without support
- Expectations for productivity: Higher expected output value
In fact, a newly published meta-analysis reviewed 60 years of role stressor research (515 studies and nearly 800,000 people) and found that three stressors cause significant workplace depletion:
- Role ambiguity: don’t know what to do
- Role conflict: Role expectations that are inconsistent or mismatched with actual job duties
- Role overload: Too much to do and too little time
Although all three have negative effects on both individual and organizational outcomes, researchers have found that role ambiguity tends to be the most detrimental factor. What helps is for teams to have clear objectives, clear decision-making authority, and some autonomy over the size of their workloads.
Ideas to help build resilience into your workplace systems
Here are some additional ideas to help leaders and busy professionals build sustainability and resilience into their workplace systems.
- Build recovery into your workflow. It’s common to move from one task or project to the next, but schedule recovery time before the next sprint.
- Cross-train roles and responsibilities. I interviewed a partner at a large law firm. He talked about how important it is to the success of his practice that his clients get to know his team. He explained that as a leader, you may be the first person called and seen as the go-to person for internal and external clients, but clients also need to be comfortable with the rest of the team. It gives the client a new attachment point and creates an opportunity for team members to gain valuable experience interacting with clients (it’s also an avenue for developing judgment, something junior knowledge workers will need to cultivate more intentionally in the coming months and years).
- We recognize leaders and experts who work on preventive measures, not just reactive responses. Who will spot problems early, quietly manage risks, and improve workflows to prevent breakdowns?
- Give experts decision-making discretion when appropriate. Employee empowerment is a resilience tool.
- Protect your small buffer. Please add some time to the deadline. Bake on an additional budget. We design with recovery in mind, so you don’t have to react as much when something doesn’t go as planned.
The AI conversation has moved from experimentation to execution. In the pursuit of competitive advantage, leaders are tempted to focus solely on speed, efficiency, and results. However, sustainable performance needs to be treated as a business imperative, not something that can be an afterthought or something that people can ‘pick up’. The organizations that will benefit the most from AI will be those that intentionally invest in human capabilities as much as they do in technology. The future of work will be shaped by leaders who know how to work together to create conditions where people and technology can perform at their best.
