At a glance:
- Role ambiguity hides in plain sight: Lack of role clarity tends to surface as stress, errors, avoidance and conflict.
- AI creates three specific clarity gaps: What tasks employees still own, where AI should and shouldn’t be used, and who’s accountable when something goes wrong.
- Unclear roles fuel the biggest hazards: Left unaddressed, role ambiguity can intensify poor support and job demands — Sonder’s two most common psychosocial hazards.
- Clarity is an ongoing conversation: The most effective organisations revisit role clarity continuously through AI adoption, not as a one-off communication.
As AI reshapes the way work happens, many organisations are focused on implementing new tools. Yet role design, expectations and internal communication often struggle to keep pace.
Maybe you’ve noticed a sense of uncertainty creeping across your team? A previously confident employee seeking more reassurance before making decisions. A manager spending more time answering questions about responsibilities and expectations. The work is getting done, but something feels less clear than it did before.
81% of employees believe leadership understands how AI is shaping work. Yet significantly fewer feel genuinely included, supported or prepared for the changes ahead.
Sonder’s latest guide, How to Navigate Psychological Safety in an Age of AI, explores how when employees lack clarity about how their roles are changing, uncertainty can quickly take its place.
And when expectations become blurred, confidence can waver, and psychosocial risks often emerge long before organisations recognise them. This blog explores how to counteract that impact, and ensure your AI adoption comes with clarity – not risk.
The questions your team is probably not asking out loud
Even when encouraged, employees don’t always express their concerns about role clarity. Instead, uncertainty often manifests in subtler ways, such as hesitation, second-guessing, reduced confidence, or reluctance to make decisions independently.
As AI becomes more integrated into daily work, three questions are becoming increasingly common beneath the surface:
- What tasks should I still complete myself?
- What should I delegate to AI?
- How will my performance be measured now?
Within Sonder’s support case data, lack of role clarity represents approximately 2% of reported psychosocial hazards. However, this figure could understate the true impact. Employees rarely identify “role ambiguity” as the source of distress. Instead, it can emerge through symptoms such as stress, frustration, errors, avoidance, or conflict.
Role ambiguity also intersects with several of the most commonly reported psychosocial hazards: Poor support accounts for 20% of psychosocial risk cases, and job demands account for 23%.
When employees are unsure of expectations, all three hazards can intensify. While role clarity may not always be named as the problem, it often lies beneath it.
Read more: Understanding the risk and impact of poor role clarity.
How does AI erode role clarity?
Most leaders recognise that AI can improve efficiency, but what many are now realising is how it can create immense confusion when implementation focuses on the tools — with little attention to people.
One common challenge is the assumption that AI automatically translates into faster delivery. When employees gain access to AI, expectations often shift, timelines become shorter, output targets increase, and teams are expected to accomplish more. Yet the issue is that many organisations do not clearly define how work processes, quality standards, or responsibilities should change alongside these new capabilities.
Your people are then left trying to determine the answers themselves.
- What should still be manually reviewed?
- What level of AI use is expected?
- How much oversight is required?
We give people AI tools and assume they’ll adapt. But we don’t always give them the training, context, or space to build confidence in how to use them well. So people are left to figure it out on the fly, often under pressure, and when they struggle it’s labelled as resistance rather than what it really is; a lack of support and enablement.
Work Futurist, Be Luminous
Another challenge is accountability. When AI contributes to a decision, recommendation, or piece of work, who is ultimately responsible if something goes wrong? Without clear policies and boundaries, employees can, understandably, find themselves carrying uncertainty about risk, ownership, and decision-making authority. Rather than creating agility, ambiguity more often creates anxiety.
Is AI making employees question their future at work?
It’s important for senior leaders to recognise that across the workforce, AI conversations are growing into concerns about job security.
Recent data suggests that only 48% of workers feel secure in their jobs, and just 38% believe their organisations can respond effectively to technological disruption.
Employees are wondering what AI means for their future while continuing to perform in the present.
Every other significant change to a work environment triggers some form of risk review. Introducing a new chemical. Changing a physical layout. Restructuring a team. AI should be no different, and yet in most organisations it's being deployed on productivity logic alone.
Co-Founder, Humn
When technology begins to automate core tasks, people naturally start asking bigger questions.
- Where do I add value?
- What skills will matter next?
- Will my role still exist in its current form?
These concerns are much more complex, extending far beyond workload. Work provides structure, purpose, identity, and financial security. For many employees, significant time and energy have been invested in building expertise within a particular role or profession. When those foundations feel uncertain, naturally, wellbeing can be affected.
This highlights the importance of proactively naming what AI will change — and what it won’t. As Sonder CPO Ingrid Jenkins explains, the greatest risk is not necessarily the technology itself.
The real risk is leaving teams behind, when people don’t feel informed, supported, or clear on what AI means for them. When that happens, you don’t just miss the AI upside, you heighten psychological risk. People lose agency. Clarity erodes. And teams get stuck in ambiguity that quietly chips away at trust and performance.
Chief People Officer, Sonder
What proactive role clarity looks like in an AI workplace
The good news is that AI adoption presents an opportunity to strengthen role design rather than weaken it. The most effective organisations treat role clarity as an ongoing conversation rather than a one-time communication exercise.
A useful starting point is mapping three categories within each role:
- What AI is removing
- What remains the responsibility of the employee
- What new responsibilities AI is creating
This framework, highlighted by Kristen Raison, Co-Founder of Humn, helps employees understand how their role is evolving and where their value continues to sit.
It's not the amount of work that harms people most — it's the lack of clarity. People can tolerate heavy work; they struggle with unclear work.
Co-Founder, Humn
Leaders can then reinforce clarity through practical support. This may include:
- Written guidance outlining where AI should and should not be used
- Clear workflows that define review and approval responsibilities
- Accessible answers to common AI-related questions
- Training focused on AI as a decision-support tool rather than a decision-maker
- Manager capability building to support conversations about changing expectations
Leading organisations are also embedding governance into their AI strategies from the outset.
Culture Amp’s hub-and-spoke model provides one example. Its central AI governance team establishes standards, accountability, and oversight, while individual business units adapt implementation to their specific needs. Transparency, traceability, and human oversight remain embedded throughout the process. The result is greater consistency, clearer accountability, and stronger employee confidence.
For further guidance, explore our resources on understanding the risks and impact of poor role clarity and how to overcome poor organisational change management.
To learn more about how both human potential and AI are shaping the future of work together, watch our panel of senior HR leaders and expert voices discuss the topic below.
How do you build role clarity during AI adoption?
The organisations navigating this AI transition most successfully are the ones helping employees understand how their work is changing, what remains within their control, and where they continue to create value. Role clarity sits at the centre of that effort.
When expectations are clear, employees are better equipped to adapt, make decisions, and engage confidently with new ways of working.
Download Sonder’s guide, How to Navigate Psychological Safety in an Age of AI, for expert insights and practical frameworks to support employee wellbeing throughout your AI adoption journey.
FAQs:
What is role clarity, and why does it matter?
Role clarity means your people have a clear understanding of:
- Their core responsibilities and tasks
- The outcomes they’re expected to deliver
- Who they report to, and who they collaborate with
- Where their responsibilities start, and where they end
- How success is measured, both short- and long-term
When this clarity is present, employees are more engaged, confident, and autonomous. They can make informed decisions, prioritise effectively, and collaborate with less friction. Most importantly, they’re able to focus their energy on high-value work, rather than second-guessing expectations.
When can poor role clarity happen?
- During employee onboarding
- During organisational change
- In the absence of clear communication
- With inadequate role definition
- During transitions
- In dynamic or high-growth environments
Role ambiguity doesn’t happen in a vacuum. It’s often a symptom of broader organisational gaps, like unclear communication, poor change management, outdated processes, or too much complexity. Let’s explore those common scenarios when poor role clarity crops up.
What is AI-induced role ambiguity?
As organisations accelerate their investment in artificial intelligence, AI-induced role ambiguity can emerge. While much of the global conversation focuses on AI replacing jobs, the more immediate risk to employee mental health is the lack of clarity regarding how roles are changing.
When AI is integrated into a workflow, roles rarely disappear. Instead, they shift. Tasks are automated, but accountability remains human. However, if leadership fails to redefine these new boundaries, employees are left in a state of chronic uncertainty, often referred to as AI anxiety.
Is ‘low role clarity’ a psychosocial hazard?
Yes. Safe Work Australia explicitly includes “low role clarity” as a common and preventable psychosocial hazard, alongside things like high workload or poor support. Under WHS law, employers have a duty to manage psychosocial hazards and risks to psychological health and safety that arise from poor workplace design or culture. That means improving role clarity isn’t just good for people, it’s a compliance requirement, too.
