Workforce 2026: What Actuaries Need to Know from Gartner’s Future of Work Trends

One of Gartner’s key messages is that many employers have already made substantial workforce adjustments in anticipation of AI-driven productivity gains – sometimes before those gains have actually materialised. Notably, only a small share of layoffs in 2025 was directly attributed to AI replacing work. For actuarial teams, this is significant: pressure to “do more with less” may increase even in areas where quality, governance and validation cannot be compressed. Actuaries may therefore be asked not only to model financial and insurance risks, but also to support workforce and operating-model scenarios – for example, assessing how delivery risk, control risk and decision quality change when capacity is reduced ahead of proven automation benefits.

At the same time, Gartner points to a growing mismatch between performance expectations and what employees receive in return – whether it be compensation, flexibility or meaningful support – creating what it calls “culture dissonance.” In highly specialised analytical functions, this gap can quickly translate into retention challenges, loss of institutional knowledge and heightened model risk. For actuaries working in cross-functional settings, understanding these cultural fault lines becomes part of professional effectiveness: technical excellence alone may not be enough if teams are strained, turnover rises or collaboration weakens under conflicting expectations.

Gartner also highlights the less visible costs of AI adoption. While AI can streamline tasks, it can also introduce cognitive load, uncertainty and over-reliance – raising concerns about mental fitness at work and “disordered AI use.” For actuaries, whose credibility depends on judgement and explainability, the takeaway is clear: AI should reduce friction and deepen insight, not accelerate unchecked outputs. Establishing healthy usage patterns – clear quality gates, peer review, robust model governance and transparent documentation – will help ensure AI supports, rather than undermines, actuarial standards.

A related issue is the rise of low-quality AI output that increases effort instead of reducing it – often referred to as “workslop.” In actuarial contexts, this may appear as plausible-sounding summaries, auto-generated code fragments or “almost-right” analyses that require extensive checking. The profession is well positioned to counter this trend by prioritising quality over speed: using AI where it genuinely improves robustness (for instance by automating repetitive data preparation or producing first-draft reporting), while keeping responsibility for assumptions, validation and interpretation firmly with accountable experts.

Gartner also notes that recruitment is being reshaped by AI, from automated screening to new forms of candidate fraud detection. For actuarial hiring, this sends a dual signal: first, employers will need better ways to identify genuine analytical thinking beyond polished, AI-assisted applications; second, there is renewed emphasis on assessment formats that test reasoning, communication and professional judgement – capabilities that remain difficult to fake and essential in regulated industries.

Security and insider risks are another prominent theme. As AI becomes embedded across workflows, the risk surface expands – from sensitive data leakage to corporate espionage and misuse of internal systems. Actuaries, trained to quantify and manage uncertainty, can add value here by helping quantify the economic impact of insider threats, define controls, and model trade-offs between accessibility, productivity and protection – particularly where personal data and proprietary models are involved.

Looking ahead, Gartner anticipates shifts in career pathways, including moves toward hybrid roles and more “AI-proof” skill combinations. In the actuarial world, this reinforces the value of broad capability stacks: domain expertise paired with data literacy, process understanding, stakeholder management and communication. This aligns with another Gartner insight: those who unlock the most value from AI are often not the most technical specialists, but people with strong process expertise – who can redesign workflows, clarify decision points and embed governance. Actuaries frequently work in exactly this way, translating complexity into controlled processes and decisions, and are therefore well placed to lead AI-enabled transformation rather than simply adopt new tools.

Finally, Gartner highlights emerging debates around “digital doppelgangers” – AI-driven replicas of top performers – and how employees may be compensated for the value their data and expertise contribute to training such systems. While this may still feel futuristic, it connects directly to issues actuaries care about: intellectual property, accountability, data rights and incentives. As human–AI collaboration deepens, questions of ownership, consent and remuneration are likely to become more tangible – particularly in knowledge-intensive professions.

Overall, Gartner’s 2026 trends point to a workplace where AI adoption is real but uneven, efficiency pressure remains high, and the differentiator is not tool usage but disciplined, human-centered implementation. For actuaries, the opportunity is clear: to bring the profession’s strengths – rigorous thinking, strong governance and risk-aware decision-making – to ensure AI improves outcomes without eroding trust, quality or professional judgement.

Find more information on the Gartner website.