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Monday.com Study Suggests UK Firms Will Reject AI Job Cuts

ended 18. December 2025

The Monday.com/Nielsen survey of 500 UK and US directors exposes what researchers call the “Operational Era of AI”, where adoption is high but trust remains fragile. This is in contrast to the CIPD who reported one in six employers say AI will shrink headcount in 2026.

Monday.com found:

  • While 94% of directors use AI daily and 70% of IT leaders claim expert proficiency, enterprise leaders are twice as likely to worry about being judged or discredited for AI use compared to mid-sized companies
  • Directors over 35 feel this guilt significantly more than younger colleagues.
  • 76% of directors report constantly switching between multiple AI tools to get work done. This is composed of 24% who "always" switch and 52% who "often" switch., with only 2% relying on a single solution.  This "AI sprawl" compounds data privacy concerns (cited by 40% as the top adoption barrier) and creates doubt about output reliability. 
  • The drive for output quality is strong: 56% of directors cite enhancing the accuracy and quality of work as a top personal driver for adopting AI.
  • Three in five directors expect employees to use AI in at least 25% of their daily workflows
  • Directors are adopting AI for pragmatic, immediate gains, defining the "Operational Era of AI". The top three personal motivators are: 

    1. Improving speed and efficiency: 59%. 
    2. Enhancing the accuracy and quality of work: 56%. 
    3. Boosting productivity levels: 53%,.
  • The goal of boosting efficiency and automation is the top motivator at the company level, cited by 62%. By contrast, future-oriented goals like enabling innovation in products or services is cited by only 45% of directors,.

Despite high adoption rates, trust remains fragile, leading companies to seek control over their AI infrastructure:

  • Data privacy and security is ranked as the top barrier to AI adoption, cited by 40% of directors
  • 83% of companies currently relying solely on external AI tools are either building internal solutions or planning to do so within the next year
  • Only 38% of directors cite labour reduction as a motivator for adopting AI, suggesting the primary goal is not mass job displacement.

The industries leading AI adoption are often those not traditionally seen as tech-forward:

  • The Real Estate industry is the top overperformer, using AI at 1.6 times the expected rate relative to its user base on the monday.com platform
  • Construction follows closely, using AI at 1.3 times the expected rate
  • The perceived tech leaders are lagging, with Marketing (0.7x), Tech (0.8x), and Finance (0.9x) all underperforming their expected AI usage rates
  • CRM (Customer Relationship Management) is viewed as one of the clearest and most immediate use cases for AI, with three in five directors reporting their organisations already use AI "a lot" or "extensively" for CRM tasks.

The Power Shift (Who is Driving AI)

AI strategy is often driven from the middle, not the top:

  • Dedicated AI or Innovation Teams are cited as the primary driving force for AI adoption by 34% of directors,.
  • Only 29% of directors cite Senior Leadership or the Board of Directors as the primary driving force,.
  • UK organisations are more likely than US organisations to report that AI adoption is being driven by dedicated AI/Innovation Teams (39% vs. 29%).

The Gender Paradox

  • 58% of women use tools like ChatGPT and Claude in professional and personal contexts, making them power users at a significantly higher rate than men (44%).
  • Despite being high users, women are 80% more likely than men to say they "only know a little" about AI (18% vs. 10%), revealing a confidence gap that does not reflect their actual capability.

We'd like your views:

  • If enterprise directors are twice as likely to fear judgment for AI use, what's causing the confidence gap between claimed expertise (70%) and emotional reality?
  • Why do real estate (1.6x) and construction (1.3x) lead adoption while tech (0.8x) and finance (0.9x) lag, does practical implementation beat technical sophistication, or are "tech-forward" industries paralysed by overthinking?
  • Three in five expect employees to use AI in 25%+ of workflows, but only 34% of strategy comes from senior leadership, who's accountable when adoption outpaces governance?
  • Directors want accuracy (56%) but doubt reliability (34%), chase speed (59%) while experiencing tool-switching friction (76%). How long can cognitive dissonance be actively ignored and excused?

3 responses from the Newspage community

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Colette Mason
AI Ethics Consultant at Clever Clogs AI
IT teams are more aware of the rules and regulations they're playing with. Finance is especially hamstrung. heavily regulated by FCA requirements and GDPR concerns where a single data leak would be catastrophic. Construction and real estate don't face the same regulatory minefield, so they can move a little faster. This isn't about tech sophistication, it's about legitimate compliance risk that stops you deploying before you've thought it through properly. These industries are pre-programmed to be more cautious.
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Rohit Parmar-Mistry
Founder at Pattrn Data
The fact that the Monday.com data shows Finance (0.9x) lagging behind Construction (1.3x) confirms that white-collar sectors are paralyzed by overthinking, while builders get on with it. Finance is addicted to 'throwing bodies' at technical problems-historically. Instead of fixing the legacy IT they hire armies of humans to copy-paste data between systems.

The study's 76% tool-switching stat proves the danger: High-value fee-earners are drowning in 'digital friction', serving as expensive middleware.

The quick win isn't replacing these experts, it's automating 'time-to-revenue'. Client onboarding and KYC check is a bottleneck where profit dies. By using AI here, you are freeing up costly staff to stop wrestling with PDFs and get to the billable strategy work that they were hired for. This isn't headcount reduction, it is capacity creation. That is the only way Finance plays catch up to the pragmatic efficiency of the construction site.
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Patricia McGirr
Founder at Repossession Rescue Network
I'm actually pleased AI finance is lagging behind on the ground. Academic studies show we're at least five years away from AI that's accurate enough for reliable financial advice and the finance industry knows it.

Only last week, google reported AI accuracy can vary from 46-70%. At that level it’s simply not fit for purpose yet.

They're right not to trust systems that shouldn't go anywhere near a client portfolio. They are right to keep up the head count of trained human advisors.

There's nothing wrong with using secure fingfenced tools like MS Copilot for basic admin, but let's applaud all those IFA practices for understanding that keeping humans in the loop isn't caution.... it's commercial survival. The wild west that is the AI arms race only ends one way for regulated firms if the FCA catches them: badly.