The career ladder is disappearing. Are taxes making it worse?

Rishi Sunak is not a man given to alarm. The former British Prime Minister, trained as a Goldman Sachs analyst and steeped in the careful language of finance, has built his post-government career advising two of the most powerful technology companies on earth — Microsoft and Anthropic. When someone with that vantage point describes the current moment as "the most dangerous and the most transformative time in living memory," HR leaders in Canada should pay close attention.

Writing this weekend in The Sunday Times, Sunak laid out a stark assessment of what artificial intelligence is doing to the labor market — and what governments and employers must do before the window to respond closes. His argument was directed at British policymakers, but its implications are just as pointed for Canadian organizations grappling with the same technological forces, in a labour market that faces its own distinct pressures.

The numbers are already moving

Sunak's piece points to research by Stanford economist Erik Brynjolfsson showing a 16% decline in hiring for entry-level jobs in the most AI-exposed professions in the United States. Given the deep integration between Canadian and American labour markets — and the fact that many of Canada's largest employers operate on both sides of the border — those numbers are not happening at a comfortable distance. They are arriving here.

Entry-level hiring at the 15 biggest tech firms fell 25% from 2023 to 2024, according to a report from SignalFire. A Harvard University study tracking 62 million workers across 285,000 firms found junior positions shrinking at companies integrating AI since 2023, with researchers warning that AI is eroding the bottom rungs of career ladders by automating many of the intellectually mundane tasks that junior employees typically handle.

Entry-level postings in software development and data analysis have plummeted across North America, with some data indicating a 67% decrease in junior tech postings in the US alone. The effect is not confined to the technology sector. Weak hiring has been especially pronounced for knowledge-work roles including marketing and human resources — precisely the functions that sit at the centre of most Canadian HR operations.

The broader labour market is operating in what economists are calling a "low-hire, low-fire" equilibrium. Companies are achieving headcount reduction through attrition — simply choosing not to backfill roles when employees leave. This dynamic hurts entry-level candidates more than anyone else. In a low-hiring environment, the few open roles that do exist are prioritized for immediate impact, with organizations under pressure to maintain margins preferring to hire one experienced senior employee rather than three juniors who require onboarding and development.

For Canadian HR professionals already navigating a sluggish hiring environment, elevated living costs deterring young workers in major cities, and a wave of talent uncertainty driven by trade tensions with the United States, this structural shift adds a new and serious layer of complexity.

The apprenticeship argument

One of Sunak's most pointed prescriptions concerns how we train people for work. He argues that apprenticeships — particularly in the professions — become especially valuable in an AI era, because they teach workers how things are actually done, not just the theoretical frameworks that AI systems have already ingested.

Canada has long maintained a stronger apprenticeship culture than the United States in the skilled trades, but the model has been slower to extend into professional and knowledge-work fields. That gap is now consequential. The traditional deal of entry-level work — trading rote labour for mentorship — is dying, with the learning curve being automated and leaving early-career professionals stranded between AI agents and senior incumbents.

For HR leaders, this reframes the talent pipeline in a fundamental way. The assumption that universities and colleges produce work-ready graduates is eroding fast. Organizations that continue to structure their pipelines around the old model will find themselves either unable to attract candidates or unable to develop them once hired. The more productive response is to redesign early-career programs around structured, on-the-job learning — building the judgment, contextual knowledge, and human skills that AI cannot replicate, while simultaneously building the AI fluency that every future role will require.

AI literacy as the new baseline

Sunak frames AI literacy as the contemporary equivalent of a driver's licence — the skill you will soon need to do almost any job. The data supports him. According to Stanford's 2025 AI Index report, 78% of organizations are already using AI in at least one part of their work, up from 55% in just one year.

Yet adoption at the organizational level is running far ahead of capability at the individual level. Only about 43% of workers in North America reported regularly using AI at work last year, and roughly 40% said they were actively disengaged with AI tools. Canada faces a particular version of this challenge. The country's productivity gap with the United States has been a persistent concern for economists and policymakers for decades, and the risk that Canadian organizations adopt AI more slowly — or deploy it less effectively — than their American counterparts is real and growing.

Lifelong learning and upskilling are now a top priority for 75% of employers across North America. But priority and execution are different things. Most corporate training programs were not designed for the pace and breadth of change that AI demands. The federal government's investment in upskilling initiatives, and the work of organizations like the Future Skills Centre, provides a foundation — but the speed of change at the frontier of AI is outpacing the policy response.

The practical implication for HR leaders is that waiting for a coordinated national skills strategy before acting internally is not a viable option. The organizations building AI literacy into their onboarding, performance frameworks, and learning and development programs now will hold a material advantage over those treating it as a future agenda item.

The tax and policy argument, in a Canadian context

In Britain, Sunak's most politically charged argument concerns the asymmetry in how employers are taxed on human workers versus AI tools. Companies pay payroll taxes and benefits costs when they hire a person; they pay nothing comparable when they deploy an AI agent to do the same work. The argument translates directly to Canada, where employer contributions to the Canada Pension Plan, Employment Insurance, and provincial payroll taxes create a meaningful cost differential between human and artificial labour.

Canada has not yet moved aggressively to address this asymmetry through tax policy, and the federal government faces its own fiscal pressures that complicate new expenditure commitments. But the structural question — whether the tax system should be rebalanced to reduce the cost of hiring humans relative to deploying AI — is one that Canadian policymakers will need to confront, and that HR leaders are well-positioned to inform.

The stakes are significant. Workers' income taxes and payroll contributions represent a major share of government revenue at both the federal and provincial levels. A sustained shift toward AI-driven automation — particularly in white-collar, knowledge-work roles that have historically been high earners and therefore high contributors — would erode that revenue base at precisely the moment when demands on public services would be greatest.

In the United States, bipartisan legislation has been introduced requiring major employers to report quarterly on AI-related layoffs, new AI-created positions, retrained workers, and positions left unfilled due to automation. Canada has not yet moved to equivalent transparency requirements, but the direction of travel in comparable jurisdictions suggests it is a matter of when, not if.

The compliance picture is evolving

Canadian HR leaders operate in a jurisdiction where employment law is primarily provincial, which creates both complexity and opportunity. Several provinces are actively examining how AI use in hiring, performance management, and workforce decisions intersects with existing human rights obligations and privacy legislation.

Federally, the Artificial Intelligence and Data Act, which forms part of Bill C-27, has had a protracted legislative journey, but the direction it signals — toward mandatory impact assessments, transparency obligations, and accountability for high-impact AI systems — is consistent with what is already in force in jurisdictions that Canadian employers increasingly operate alongside.

Organizations using AI tools in recruitment, screening, performance evaluation, or workforce planning should be conducting their own audits now, documenting decision-making processes, and ensuring that human oversight remains meaningful rather than ceremonial. The reputational and legal risks of getting this wrong are growing, and the standard of "we didn't know the tool was biased" is becoming less defensible by the month.

What Canadian HR leaders should do now

Sunak's article is a warning, but it also carries an implicit blueprint. The companies that navigate this transition well will be those that treat it as a workforce strategy problem, not a technology procurement problem.

For Canadian HR professionals specifically, that means several things. It means making the case internally for reskilling investment at a moment when many organizations are tightening budgets — framing it not as a cost but as the single most important hedge against talent obsolescence. It means redesigning entry-level and early-career roles around what AI cannot do, rather than simply reducing headcount and hoping the pipeline replenishes itself. It means engaging with the emerging regulatory environment proactively, rather than waiting for federal or provincial guidance to crystallize.

And it means recognising that Canada's geographic, demographic, and economic position gives it a genuine choice about how this transition unfolds. The country has strong post-secondary institutions, a diverse and educated workforce, a history of navigating technological transitions through social partnership, and a public policy tradition that takes labour market equity seriously.

Sunak's closing warning is worth carrying into every workforce planning conversation happening in Canadian organizations right now: the defining question is whether AI ends up automating jobs — producing structural unemployment as a permanent feature of the economy — or augmenting them, helping workers do more and do it better. That choice is not made by governments alone. It is made, every day, by the people responsible for how organizations hire, develop, and deploy their most important asset.

In Canada, as everywhere, the HR function has never been closer to the centre of a question this consequential.