By Camellia Chan
In this article, Camellia Chan addresses AI disruption in the workplace, arguing that with inclusive leadership strategies, it can become a tool for shared progress rather than exclusion.
The adoption of new technologies always brings uncertainty to the workforce: during the industrial revolution, it meant losing farming jobs, while the dotcom era completely revolutionised the way we work. The conversation about artificial intelligence (AI) echoes many of the same themes: it’s another innovation that risks leaving certain groups behind.
As AI continues to transform the workforce, upskilling will be key for employees to keep pace. However, research shows that AI adoption remains largely at the pilot phase in most companies. Reports also indicate that jobs traditionally held by women are more vulnerable to the impact of artificial intelligence, highlighting a widening AI divide and the urgent need to ensure its deployment is equitable – before gaps in access and opportunity turn into long-term exclusion.
But AI’s impact on the workforce is not predetermined. With deliberate, people-centred implementation, it can work for everyone, becoming a tool for progress rather than division.
The blueprint: Reframing limitations as opportunities in the age of AI
What separates organisations that broaden opportunity from those that narrow it is not the technology itself, but how people are encouraged to approach it.
I’ve seen firsthand how workplace culture shapes those outcomes. Early in my career as a woman in tech, I never viewed my gender as a barrier – until others framed it that way. Luckily, I was encouraged to focus on excellence instead and even came to see the advantage of being different in the room – I was bringing a distinct perspective that made me more memorable and led to new connections. Crucially, I was supported by an environment that reinforced that mindset time and time again.
That experience shaped how I view moments of change. When people are given the right support and signals, they are far more likely to engage with new challenges constructively than resist them.
This is where leadership matters most. As AI becomes embedded in how we work, the decisions made today will shape how its value is created – and how far it reaches.
What inclusive AI adoption means for a diverse workforce
Diverse workforces have different needs, and a truly inclusive approach to AI must reflect that.
Early career professionals may already see AI as a teammate, so company policies must offer more advanced learning opportunities to apply and deepen their skills. More experienced employees, on the other hand, may be more resistant to change, making clear use cases and encouragement to experiment essential to building their confidence.
But barriers are not only generational. Confidence gaps, time constraints, and proximity to AI all shape how people engage with it. Employees with conflicting priorities outside of work (for example, women, who often carry a greater share of care responsibilities) often have less time to upskill. Similarly, while many employees recognise the value of AI, uncertainty around when and how to use it can slow adoption. For example, women are more likely than men to feel that using AI at work is cheating.
To ensure each employee can take advantage of the AI opportunity, organisations must go beyond access alone – they need to make it central to all conversations about how work gets done.
Practical building blocks: Ways to help employees grow alongside AI
Reframing how AI is viewed in the company is only the starting point. For adoption to take hold, it must be supported by structures that encourage employees to use it in practice.
Some examples of how to do this include internal knowledge-sharing sessions built around real AI use cases, peer-to-peer mentoring sessions to spread practical experience, and informal training opportunities that reflect even the smallest changes in how AI is used in day-to-day work. Sharing internal newsletters or helpful resources can also help demystify the technology for employees who may be less exposed to it.
During one internal session, our Head of HR shared how she built an automated system to streamline hiring and onboarding. Rather than formal training, she simply explained her thinking process.
That sparked new ideas across the business – logistics used it to track shipments, marketing adapted it for campaign planning, and within weeks, similar approaches were being used across teams.
While these efforts will not turn everyone into an AI expert overnight, they play a critical role in building confidence and capability over time – creating an environment where learning is continuous and engagement with AI is completely normalised.
The conversation around AI often focuses on what the technology can do, but the more important question is what kind of workforce it will create. The real divide will emerge not from a single decision, but from a pattern of small, uneven gains. What happens next depends on whether those gaps are recognised early – or only once they are too wide to close.
