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Cyprus Lags Behind Europe in Job Satisfaction and Workplace Culture

by THEFUTURE.TEAM

July 8, 2025

Overview Of The Survey

A recent European Workforce Study has revealed that Cyprus falls behind many of its counterparts in critical areas such as job satisfaction, leadership trust, and workplace flexibility. The study, which surveyed 24,938 employees across 19 countries, highlights that only 53 percent of Cypriot workers regard their workplace as exemplary—a rate that trails the European average of 59 percent.

Workplace Satisfaction And Leadership Trust

The survey’s findings underscore significant disparities in employee perceptions of leadership. While a majority of European workers—55 percent—express confidence in their senior management, Cyprus reported a slightly lower confidence level at 54 percent. In stark contrast, countries like Denmark, the Netherlands, and Sweden lead with trust ratings of 64 percent, 63 percent, and 62 percent respectively.

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Concern Over Employee Retention

The study also draws attention to potential challenges in employee retention. In Cyprus, one in three respondents indicated they plan to seek new employment within the year, while only 46 percent expressed satisfaction with their current roles. This contrasts with countries such as Austria, where 61 percent of employees reported satisfaction in their roles, signaling stronger retention prospects.

Limited Flexibility And Critical Psychological Safety

The lack of flexible working arrangements is another area where Cyprus trails. Only 32 percent of workers in Cyprus reported having access to flexible hours, compared to a European average of 39 percent. The gap is even more pronounced when assessing psychological safety—a key driver of innovation. In nations like Norway and Denmark, 64 percent of employees feel they work in an emotionally healthy environment, compared to just 49 percent in Cyprus.

Broader Implications For European Workplaces

Experts, including Tron Kleivane, head of the European Workforce Study, warn that these findings come at a time of significant systemic challenges facing Europe, such as geopolitical tensions, climate change, and technological disruptions. These factors underscore the critical importance of fostering robust workplace cultures and effective leadership to drive both performance and resilience in the modern economy.

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AI Adoption Makes Employee Performance Harder To Assess, Survey Finds

by THEFUTURE.TEAM

October 22, 2026

Companies have rapidly adopted AI tools to improve productivity, but the technology is creating new challenges for managers, who say it is becoming harder to evaluate work, supervise teams and maintain control.

More than half of senior leaders surveyed said assessing employee performance had become more difficult since their organisations adopted AI, according to a Nielsen survey of 1,700 directors and senior managers across seven countries, commissioned by work-management software company Monday.com.

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AI Makes Performance Harder To Measure

AI allows employees to produce polished work more quickly, making it harder for managers to distinguish between human effort and machine-generated output. Nearly half of respondents said they now spend more time reviewing and guiding their teams’ work.

Despite these challenges, enthusiasm remains high: 94% said they were excited about using AI to improve work.

Michal Miller Levi, head of market research and customer insights at Monday.com, said organisations were struggling to adapt their processes at the same pace as the technology.

“AI works very well for [managers] individually, but they also have a different role as managers. They need to drive the organization as well […] Their struggle is [due to] the fact that AI is just moving faster than the organizational processes,” she told TechCrunch.

Performance Reviews And AI Bias

AI is also changing how employee performance is evaluated. According to the survey, 78% of respondents had changed their performance criteria since adopting AI, placing greater emphasis on prompt-writing, deciding which tasks to delegate to AI and experimenting with new working methods.

At the same time, AI is increasingly involved in the evaluation process itself. Some 46% of managers said they use AI to inform decisions, while 39% use it to draft performance reviews.

This raises concerns about fairness and algorithmic bias. Research from the Luxembourg Institute of Socio-Economic Research found that, without clear objective standards, large language models tend to rate performance in ways that mirror human evaluators. A separate paper published in early 2025 found that AI models could exhibit biases against Black male candidates, with differences across social groups.

Levi said companies had yet to establish the right frameworks for managing these risks.

AI Adds To Managers’ Workloads

Managers are increasingly responsible for assigning tasks to AI agents, reviewing their output and intervening when systems make mistakes. This creates an additional layer of oversight, or “invisible labour”, on top of their existing responsibilities.

The software environment is also becoming more complex. Some 57% of managers said their organisations now use more tools than before AI adoption, while 51% reported greater interdependence between those tools. Only 29% described their AI infrastructure as fully optimised and centralised.

Rather than consolidating software, many companies are dealing with more applications, integrations and unauthorised AI tools used outside approved systems.

Governance Becomes The Next AI Challenge

The survey suggests that oversight will become even more important as businesses deploy increasingly autonomous AI agents. Some 58% of managers expect to oversee more AI agents than human employees within the next year, while 46% are concerned about losing control over their agents’ actions. Another 35% worry about being held responsible for decisions made by AI.

Levi said managers wanted human involvement in critical tasks and decisions, with AI supporting rather than replacing human judgement.

The findings point to a broader challenge for businesses: boosting productivity is only part of successful AI adoption. Companies also need clear processes, reliable infrastructure and accountability frameworks to ensure that faster output does not come at the expense of effective management.