The AI story inside organisations has matured quickly. It’s no longer just about tools, pilots and training sessions. In some companies it’s now part of the performance fabric: tracked, expected, and increasingly linked to progression.
At the same time, the entry point into work is getting harder. Graduates face fewer openings, far more applications, and a hiring process that can feel like a black box. Add a cautious job market, ongoing restructuring, and new forms of workplace monitoring, and you get a workforce that is less impressed by ambition and more interested in fairness.
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This edition connects the thread across four themes, then closes with The Cut List.
This Week’s Paper Cut's
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AI adoption is becoming a career requirement
Accenture is reportedly tracking senior employees’ logins to internal AI tools and tying promotion into leadership-track roles to “regular adoption”. The piece also describes weekly usage data being collected, after Accenture trained hundreds of thousands of staff in generative AI.
On its own, this is a rational move. Large organisations hate patchy adoption, and they’ve spent heavily on AI capability. But measuring logins is a blunt instrument. It can reward activity rather than impact, and it nudges teams toward compliance behaviour: “touch the tool” instead of “improve the work”.
Mercer’s Global Talent Trends 2026 makes the broader pressure clearer. In its survey of nearly 12,000 executives, HR leaders, investors and employees, Mercer reports that 72% of investors believe companies integrating human and AI capabilities are positioned to gain a competitive advantage. It also reports that 65% of executives expect 11%–30% of their workforce to be redeployed or reskilled due to AI over the next two years, and that employee concern about job loss due to AI rose to 40% in 2026 (up from 28% in 2024).
That’s the deal employers are now offering, whether they say it explicitly or not: use the tools, keep up, be mobile, and accept that the operating model is changing under your feet.
Employer Brand POV
If AI adoption is part of progression, make the rules adult and role-specific. Define what “good AI use” looks like for each job family. Give people examples that improve real work. Measure outcomes that employees recognise, like cycle time, rework, customer handoffs and quality, not just usage. And if you’re tracking activity, say so plainly and explain what it will and won’t be used for.
📌 Sources

- https://www.mercer.com/about/newsroom/mercer-s-global-talent-trends-2026-report/
Graduate hiring is getting overwhelmed by AI on both sides
The Irish Times lays out the graduate market in unflattering detail. It cites Indeed figures showing graduate vacancies tracking lower, 13% down year-on-year in mid-February, and describes employers becoming more risk-averse. It also captures what many graduates are living through: an “applications blitz” where AI makes it far easier to create and tailor CVs, search and monitor listings, and apply at scale. One business analyst role cited by a recruiter drew more than 2,000 applications.
Employers respond with AI screening. The Irish Times reports that many big employers use AI to scan CVs and rank suitability, with tools also used for interview transcription and evaluation of recorded interviews. It adds that chat-based engagement can replace early phone screening, and cites a survey claiming 73% of entry-level jobseekers suspect an AI filter is responsible when applications go unanswered, while only 21% reach a human recruiter.
The Business Times adds the UK dimension. It reports Adzuna data showing UK job vacancies falling, and graduate job ads dropping 19.1% in January to below 10,000 for the first time since Adzuna began tracking in 2016.
Zoom out further and the “job market freeze” story matters here. Business Insider describes a labour market where employers are hesitant to hire aggressively. It also notes that in tech, the share of postings requiring at least five years of experience is increasing, even as experience requirements soften elsewhere.
South Korea is seeing a similar squeeze on early careers. The Korea Times reports a sharp fall in employment among young professionals in professional, scientific and technical services, noting a year-on-year decline in that sector and raising concerns that entry-level roles are taking the first hit as AI spreads.
Employer Brand POV
If you want graduates, your hiring system has to look human again. Publish clear timelines. Explain how screening works. Make the first hurdle meaningful rather than invisible. If you use AI screening, say so, and explain what candidates can do to be assessed fairly. And if you keep raising experience requirements while entry-level routes shrink, don’t be surprised when your talent pipeline starts to look like a funnel with a blocked spout.
📌 Sources


Work is getting more visible, and trust is doing the heavy lifting
PCWorld reports that Microsoft Teams will be able to automatically update a user’s work location when they connect to their organisation’s Wi-Fi, reflecting the building they’re working from. It notes the feature is off by default, controlled by tenant admins, and requires end-user opt-in.
In isolation, this can be framed as coordination. In practice, people interpret workplace visibility features through trust. In a high-trust environment, location data is logistics. In a low-trust one, it becomes a symbol of enforcement. And once a tool like Teams becomes a proxy for “who’s watching”, the employer brand damage isn’t limited to one policy. It spreads into how people interpret every future change.
Employer Brand POV
If you use presence or location data, treat it like a trust asset. Be clear on what is collected, who can see it, what decisions it informs, and what it explicitly does not inform. If you want coordination, show employees how the feature helps them, not just how it helps management.
📌 Sources
- https://www.pcworld.com/article/3003806/microsoft-teams-will-soon-snitch-on-your-location-to-your-organization.html
Employer brand is built on experience, and culture now carries more emotion
Built In’s piece on social media employer branding is old, but the point is still current: candidates live on social platforms, and employer brand is increasingly shaped through ongoing, distributed proof, not just a careers page.
Fast Company argues the future of team culture-building is emotional, built through trust, connection and the felt experience of work, not perks and slogans. Psychology Today adds a twist that’s uncomfortable for leaders: quiet quitting isn’t only an employee behaviour. Managers can disengage too, through avoidance, inconsistency and a slow retreat from the human work of leadership.
Then there’s the mental load of the AI narrative itself. Futurism points to research suggesting that repeatedly telling workers they’ll be replaced by AI can have grim psychological effects. Whether or not a specific prediction proves right, the constant messaging of obsolescence shapes how people show up.
Inclusion sits inside this reality, not alongside it. The UK government’s disability employment statistics show 5.5 million disabled people in employment in Q2 2025, with a disability employment rate of 52.8% compared to 82.5% for non-disabled people. Numbers like these cut through performance messaging and tell you whether systems are actually accessible.
Employer Brand POV
You don’t need louder culture statements. You need more reliable management. Clarity on priorities, predictable feedback, and fairness in workload and progression are now the differentiators candidates believe. If you want to talk about inclusion, publish what employees can ask for, how quickly adjustments are handled, and how progression works in practice.
📌 Sources




- https://www.fastcompany.com/91495319/the-future-of-team-culture-building-is-emotional
The Cut List
The Cut List is our weekly, structured roundup of layoffs and restructures, focused on what changed, what it means for talent confidence, and what people leaders should do next.
What moved
- C3.ai disclosed layoffs at its Redwood City headquarters. SFGate reports a WARN filing notice for 71 layoffs at the site, including data scientist roles and engineers, ahead of a closely watched financial report.
- eBay announced it is eliminating about 800 roles, roughly 6% of its full-time workforce, framing the move as aligning structure with strategic priorities and reinvesting across the business.
What it means
In an AI-heavy news cycle, even “ordinary” restructures get heard as automation-by-default. When companies cut while talking about reinvention, employees and candidates focus less on the strategy language and more on the fairness of execution.
Employer Brand POV
If you restructure, your reputation is shaped by basics: speed and clarity of comms, consistency of manager messaging, and the reality of support (redeployment, timelines, severance, references). People remember how they were treated, and so does the market.
📌 Sources

- https://www.sfgate.com/tech/article/c3-ai-layoffs-21939617.php
Closing thoughts
This week’s thread is straightforward: AI is becoming part of how work is assessed, and entry routes into work are getting harder at the same time.
The employer brands that hold up in 2026 won’t be the ones with the most polished messaging. They’ll be the ones that can explain the rules clearly, run them fairly, and keep pathways into careers real.
Video Edition
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