Editorial
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The Future of Leadership Development: AI-Driven Manager Enablement
Systemic barriers have always existed in people-centric practices. Now AI is potentially intensifying existing barriers rather than eliminating them.
A favorite quote of a colleague, Jonah Ssenyange, aligns well here:
Audre Lorde once said: "There is no such thing as a single-issue struggle because we do not live single-issue lives."
That truth feels very relevant to Human Resources professionals right now.
The Scale of Workplace Discrimination
Discrimination in the workplace is not a unique experience. It is a documented and measurable pattern that shows up at every stage of the employment journey, from the first interview and throughout the employee’s career pathway.
| 31% → 34% | Percentage share of Canadians reporting bias or discrimination when applying or interviewing for a job, rising to 34% once inside the workplace. (Pollara Strategic Insights, 2024) |
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| 50% of employers | Identified unconscious bias specifically favoring candidates who share ethnic or other similarities with the hiring manager — as the top challenge in hiring decisions. (Canadian Human Rights Commission) |
| 55.6% of employers | Acknowledged that racialized employees do not have the same promotion opportunities as their peers. (CHRC) |
| 2 of 18 employers | Had an employment equity plan in place to boost racialized representation in management and executive roles, despite 44% citing workplace culture — including micro-aggressions, discrimination and harassment — as a barrier. (CHRC) |
Personally, I do not use the term “unconscious” bias anymore — it is bias plain and simple, and we all carry it. In fact, we all make assumptions that often lead to bias.
These are not isolated incidents. They are symptoms of systems that were never designed with all of us in mind.
The Pay Gap Is Still Wide
The financial impact of systemic barriers is real and compounded for people who carry more than one racialized identity.
| 79¢ / 72¢ | What racialized men and racialized women, respectively, earn for every dollar a non-racialized man earns. The gap persists even between Black and white workers with the same education level. (BC Human Rights Commissioner, 2025) |
|---|---|
| 74.1¢ on the dollar | What racialized women earn compared to a white male worker — roughly a $10/hour difference. (Troy Media, 2025) |
| 13.1% → 15.2% | Growth in the share of racialized workers aged 25–54 in low-wage jobs (2022–2024), while the rate for white workers held steady at 7.3%. |
| $37.77/hr | Average hourly wage for non-Indigenous workers in 2024 — a benchmark that First Nations (off-reserve), Métis and Inuit workers all earned below. (Statistics Canada, 2025) |
The gender pay gap widens further for Black, Indigenous and other racialized women, and for women with disabilities. These inequities are not in isolated categories and are often compounded.
Barriers Remain Embedded in Systems
Canada's 2024 Employment Equity Act Annual Report acknowledges that while some progress has been made, gaps and barriers to full inclusion remain for women, Indigenous peoples, persons with disabilities, and members of racialized groups and communities.
| By the numbers | 20.9% of Canadian-born racialized people report discrimination as a barrier to gaining and keeping employment — 10.6 points higher than their non-racialized peers. |
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This is the core of what HR professionals must confront: these are not individual failures. They are structural. They live inside the policies, programs and practices that govern how people are hired, onboarded, paid, promoted and supported throughout their careers. As HR professionals, it is time for us to address the systemic barriers still embedded in people programs, policies and practices that prevent some employees from access to equitable opportunities not just at the front door, but throughout the entire employment journey.
The impact of systemic barriers is even more profound for individuals facing multiple, compounding barriers and lack of equitable access and surrounding support. Understanding this intersectionality, the interconnectedness of these systems, is crucial.
AI Is Intensifying Existing Inequities
Now layer AI on top of all of this.
AI is built on and engages in a workplace environment that has embedded systemic barriers — barriers already shaped by decades of biased decisions. When that history becomes training data and “experience,” AI does not correct the pattern. Instead it learns the patterns, scales the patterns and embeds the patterns in AI-based processes faster than any single hiring manager or Human Resources team member ever could.
| 57% vs. 43% | Share of women, vs. men, more likely to be in roles disrupted by AI. Fewer women than men will see their work augmented by generative AI (46% vs. 54%). (World Economic Forum) |
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| 40% of applications | Now filtered by AI before a human ever reviews them. |
| 68% of recruiters | Believe AI removes bias from hiring, however there is not yet full confidence of this and it is not matched by the evidence. |
The WEF report states: advancing AI with limited talent diversity risks “economic drag and AI-driven inequality.” Algorithms learn from historical data, and that data carries the weight of decades of discriminatory hiring practices. Left unchecked, AI does not remove bias from the system — it launders it, and makes decades-old systemic patterns look like objective, data-driven outcomes.
Across all levels and functions, HR professionals and people leaders need to understand that the emerging future of work and AI requires expanding existing skills and competencies. The tools may be new. The accountability is not.
What Needs to Change — and Where Should HR Start?
The evolution of systemic HR practices is inevitable given the changing labor markets and demographics, increased reliance on AI, and the ongoing redesign of work itself. But this evolution faces significant challenges in HR skill sets, organizational people strategy and resource allocation. HR professionals must transition from specialized roles to cross-disciplinary expertise moving from the status quo to action.
That means going beyond awareness. It means building capacity to:
- Critically evaluate the social, institutional and contemporary structures that limit access to diverse talent across recruitment, onboarding, performance management, compensation, career development and departure practices.
- Identify and address attitudinal barriers to racial equity, including the culture of language, implicit power and structural bias embedded in everyday HR processes.
- Apply the principles of Inclusion, Diversity, Equity and Accessibility (IDEA) to real workplace decisions, not just policy documents.
- Move from allyship to advocacy, taking collective responsibility for dismantling the barriers that still remain.
The work ahead spans the full employment lifecycle: from how we source and recruit talent, to how we welcome people through onboarding, how we assess and compensate them, how we develop their careers, and ultimately how we support their departure with the same dignity we intended at hire.
Safeguarding AI in HR and Advocating for Better Tools
Let’s be realistic here: HR is already using AI, whether through resume screening, interview scoring or performance analytics. The question is not whether to engage with these tools, it is whether HR is prepared to govern them with the same rigor applied to any other people-centric decision.
Safeguard what is already in use
- Treat every AI-assisted decision as an employment decision, not a technical process. The accountability for a discriminatory outcome sits with the employer, not the AI vendor, regardless of who built the algorithm.
- Insist on regular, independent bias audits of any tool that screens, scores or ranks candidates or employees and review the results, not just the existence of the audit.
- Keep humans in the loop. AI can inform a decision, however it should not make the decision. If HR cannot explain why a recommendation was accepted or overridden, then there is a governance gap, not a technology problem.
- Monitor outcomes over time, not just at launch. A tool that looked fair in testing can drift as it is used against new populations and new data.
- Build bias accountability directly into vendor contracts, so responsibility for fairness does not quietly disappear into a "black box.”
Advocate for where these tools go next
Safeguarding today's AI tools is necessary but not enough. HR is also one of the few functions positioned to shape what these systems become and HR needs to understand how important this is.
- Vendors and platform providers must provide transparency by design: explainable outputs, documented training data, and visibility into how a tool was tested for disparate impact before HR ever sees a demo. Check the facts over and over again.
- Bring lived organizational experience not just procurement criteria into product conversations with AI vendors. Is people impact and the organization culture a part of the procurement criteria. HR knows where bias actually shows up in a hiring funnel, that knowledge should inform how these tools are built, not just how they are purchased.
- Support and contribute to emerging standards and regulation rather than treating them as a compliance burden. Frameworks like independent bias audits and impact assessments exist and must be engaged because self-regulation alone does not close the gap.
- Make fairness and equity a stated requirement, not an assumed one, in every RFP and renewal conversation, so the market has a financial incentive to build equitable tools, not just efficient ones.
None of this requires HR to become a technical function. It requires HR to understand the accountability that should be embedded in HR and the importance of asking who gets left out, and the importance of bringing that question into every room where these tools are designed, purchased and deployed.
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The Work Ahead for HR Professionals
Bias did not go away. In many cases, we automated it. The question now is whether HR professionals and people leaders are ready to do the harder, more human work of dismantling it, intentionally, structurally and at every stage of the employment journey.
For more on this theme, see my previous article — What People-Centric Leadership Looks Like When AI Is Involved.
Editor's Note: HR plays a key role in what the future of work will look like. Here are further thoughts on the topic
- If We Want AI to Help HR, HR Has to Join the Conversation — Engineers are designing AI systems to address problems that are rooted in the very systems HR understands best.
- AI Can Give HR the Answer. Can HR Tell if It's the Right One? — AI can generate HR insights in seconds, but without data literacy, teams won't know when to challenge the output. Upskilling and AI adoption must grow together.
- How AI Is Rewiring People Strategy and What HR Can Do to Adjust — HR leaders see AI transforming work beyond automation — reshaping teams, culture and people strategy. The future is “human-engaged” work, not human-replaced.
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