This week’s Digest looks at what happens when technology moves faster than the people systems around it. In recruitment AI and automated screening are changing who gets seen, who gets rejected and who owns the decision. In background screening the same pressure is raising sharper questions about evidence, verification and human judgement. And in digital skills new WTW data shows how quickly scarce capability is forcing HR to revisit reward, careers and workforce planning.

The thread running through all three pieces is accountability. Technology can speed up decisions, widen reach and improve consistency, but HR must still ask what is being measured, who is being excluded, what evidence is being used and whether the organisation is building the human capability it will need next.

I’m keen to hear how these issues are showing up in your organisation. If you are reviewing AI in hiring, rethinking screening and verification or trying to build scarce digital skills please do get in touch with me. I’m interested in what is happening in practice, what is proving difficult and what HR leaders are learning.

1. Are your hiring algorithms filtering out your best talent?

Recruitment technology is now doing a great deal of work before a recruiter or hiring manager sees a candidate. This may help organisations deal with high volumes of applications, especially as AI-assisted job applications and easy-apply functions increase the number of people applying for each role. But it also raises a difficult question for HR: who is being removed from the process before anyone has judged their potential?

This question is at the heart of a new article we commissioned from Lucy Standing, psychologist, careers expert and founder of Brave Starts. Lucy’s new book, Age Against the Machine: New rules for working in an ageist world, written with Martin Hyde and Maggi Evans, is out now and looks at how ageism is shaping people’s working lives at a time when organisations can ill afford to waste experienced talent.

Her argument is that automated screening tools may appear efficient but they often work by matching candidates against narrow patterns. A CV is parsed, scored and ranked. Keywords, job titles, employment dates and experience thresholds become decisive. As Lucy writes: “These systems don't evaluate talent. They evaluate pattern-matching and genuine talent has an irritating habit of not fitting patterns.”

This matters most for people whose careers do not look tidy on paper: older workers, career returners, carers, generalists, people who have changed direction or those whose job titles no longer map neatly onto current terminology. These are not marginal cases. Research from Harvard Business School and Accenture on “hidden workers” found that millions of qualified candidates are made invisible to employers, often because automated systems cannot recognise what they bring. In that study 88% of employers acknowledged their screening tools were filtering out viable candidates.

Lucy is particularly concerned about older workers. In the UK people aged 50 and over make up a third of the working-age population. Yet Brave Starts’ own survey data suggests age discrimination is becoming a greater concern. In 2020 and 2021 41% of respondents said they had experienced or feared age discrimination. In the most recent responses, from 2025 and 2026, this figure had risen to 57%.

The HR issue here is governance. What is the tool actually measuring? Who is being screened out? Are the criteria linked to performance or are they simply reflecting past assumptions about what a “good” candidate looks like? Is there a route for someone to be reconsidered if the system gets it wrong? And who in the organisation is accountable for the decisions made by the technology?

Lucy ends with a question worth taking seriously: “The machine is making decisions about your talent pipeline every day. Are you paying enough attention to know what decisions it’s making?”
👉 Read the full story on The People Space for Lucy’s analysis of how hiring algorithms may be excluding experienced and hidden talent, and what HR leaders should do before automation becomes the final gatekeeper: Are your hiring algorithms filtering out your best talent? 6-minute read

2. The recruitment question HR can’t leave to technology

If the first recruitment question is who gets filtered out before a human sees them the next is who is still applying judgement once technology has done its work?

That is the focus of a new Expert Insight article from the Professional Background Screening Association (PBSA), our new Expert Insight Partner on The People Space. It looks at a part of hiring that often sits too far down the HR conversation: screening, verification and the quality of evidence behind recruitment decisions.

AI is changing hiring at both ends of the process. Candidates can now use AI to polish applications, rewrite CVs and present themselves more convincingly. Employers are using technology to screen CVs, assess candidates, check identity and manage background information at scale. Research cited in the article finds nearly half of UK job seekers have experienced AI interviews, with a pattern across Europe and the US of candidates withdrawing from processes where AI was being used and where there was little clarity about how decisions were made.

The issue for HR is whether the process remains fair, explainable and properly owned. As Susie Thomson, chair elect of PBSA, argues in the piece, employers are relying more heavily on AI-led CV screening, video interview analysis and automated decision tools to manage recruitment volume. These systems can support consistency and speed but they can also miss context, overlook non-linear career paths and reinforce assumptions already present in historical data.

This is where background screening needs to be understood as part of talent strategy rather than a compliance task at the end of the process. In a hiring market shaped by AI-assisted applications, more polished candidate narratives and more sophisticated digital fraud, HR leaders need to know what information has been verified, where it came from and who has interpreted it. A flagged discrepancy may indicate risk but may also have a reasonable explanation. This is where human judgement comes in.

PBSA’s article gives HR leaders five practical checks:

• Confirm who owns the final decision
• Build in human checkpoints
• Test whether outcomes can be explained
• Review the quality of the evidence
• Check whether speed is distorting judgement.

Recruitment technology now shapes both who gets through the funnel and how reliable the information about them appears to be. If HR does not set the terms the process will be shaped by vendors, workflows and default settings.

👉 Read the full Expert Insight from PBSA to explore how HR leaders can keep judgement, accountability and evidence in view as AI becomes more embedded in hiring and screening: When AI speeds up hiring, who is still using judgement? 4-minute read

3. The digital skills race is becoming a reward and careers problem

New WTW data on AI and digital talent pay shows how quickly scarce skills are reshaping reward, careers and workforce planning across global markets.

The headline figures are striking. Median total compensation for mid-level machine learning roles in the US is now above $170,000. Germany follows at around $122,000 while the UK sits just below $100,000. Canada, which has previously ranked ahead of the UK, has dropped into fourth place for AI pay. Across the 10 countries studied by WTW median salaries for machine learning roles rose by an average of 2%, while total compensation rose by 6%. The biggest movement came in emerging markets, with Mexico recording a 19% rise in salaries and a 29% rise in total compensation.

For people leaders the figures are useful because they show where pressure is building. The US remains expensive. Germany and the UK are strengthening. Some emerging markets are moving fast. A reward structure designed around last year’s assumptions may already be out of date.

Ruchi Arora, Europe leader for work, rewards and career consulting at WTW, puts it well: “AI pay is no longer just about where salaries are highest, but where momentum is building fastest and how employers are aligning pay and incentives to keep pace.”

This is where the issue becomes more strategic. Scarce digital skills rarely create isolated reward problems. They reveal whether the organisation has a clear view of critical roles, future skills and retention risk.

The World Economic Forum’s Future of Jobs Report 2025 found that employers expect 39% of workers’ core skills to change by 2030. McKinsey has also reported that only 16% of executives in a previous internal survey felt comfortable with the amount of technology talent available to drive digital transformation, while 60% cited scarcity of tech talent and skills as a key inhibitor.

The public conversation often focuses on AI specialists but the skills picture is broader. WTW finds that software engineers remain the most in-demand digital roles globally, followed by application developers and data scientists. Cloud computing pay is also rising quickly, with median salaries for cloud engineering increasing by an average of 9% across the 10 countries studied and total compensation up 12%.

For HR this means looking beyond headline AI roles and understanding the wider digital operating model. Organisations need software engineers, data scientists, cloud engineers, cyber specialists, product managers, business analysts and people who can translate between technical and commercial teams.

Pay will remain important. Nearly half of organisations in WTW’s survey now offer differentiated reward programmes for digital talent, including enhanced base pay, flexible working, learning and development, retention bonuses and long-term incentives. Yet differentiated reward needs clear governance. HR should be able to explain which roles receive premium treatment, why they are strategically important and whether incentives are building commitment or simply delaying resignation.

A stronger response is to connect reward, career design, skills development and work design. Which digital roles are critical to the strategy? Where are those skills available? Which can be developed internally? Can technical specialists build careers without being forced into management? Are scarce people spending their time on work that creates value?

This is the real HR challenge behind the digital skills debate. Organisations can pay more for talent, but without credible careers, better workforce planning and a clear view of capability they will keep returning to the external market at greater cost.
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👉 Read the full story for the WTW data, expert analysis and five questions HR leaders should ask now about scarce digital skills, reward and workforce planning: Why scarce digital skills are forcing HR to rethink reward, careers and workforce planning 7-minute read

Find your hiring space!

Siân

Editorial director, The People Space​

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