AI & the workplace: AI is changing the way we feel about our jobs

AI is changing how work gets done. It’s also changing how people feel about their jobs. As AI tools become more common across industries, organizations and employees alike are being forced to rethink skills, roles, and expectations. The shift is creating new opportunities, but also uncertainty, as workplaces adapt to a future where human and machine work increasingly overlap.

When employees are trained, trusted, and involved, AI becomes empowering. When they’re not, it simply amplifies anxiety about becoming irrelevant.

What Employees Want

Meanwhile, many employees are scrambling to use AI in their work for reasons such as feeling like their skills no longer matter. As per a study “fear of missing out” (FoMO) around AI at work has become a regular occurrence.

The findings show that the level of FoMO increased and decreased based on employee perception of AI. If they feel like AI is devaluing their skills or watching them, anxiety levels rise. On the other hand, when employees see AI as a helpful tool, FoMO drops.

What Employers Want

Organizationally speaking, Gen AI dominates quality engineering trends right now. AI fluency is in demand with employers. Tech companies ask candidates to use AI to write lengthy documents in a short amount of time or create an email bot, for example. A new IBM Institute for Business Value study revealed that 49% of Indian CEOs are hiring for generative AI roles that didn’t exist last year.

Meanwhile, trends like vibe coding are picking up. Vibe coding is an AI-driven software development method where you describe your desired app or feature in natural language to an AI assistant, like an LLM, which then generates functional code, shifting the developer’s role from writing every line to guiding the AI and refining the output through conversation. With this, startups and AI giants are hiring fewer entry level coders and computer science enrollment is plummeting.

Wanted: Workers Fluent in AI

As per the World Quality Report 2024, with 68% of organizations now using Gen AI to advance quality engineering, developer productivity and quality engineering has passed the tipping point of adopting generative AI to drive business success.

68% of organizations are either actively utilizing Gen AI (34%) or have developed roadmaps following successful pilot implementations (34%). Test automation is the leading area where Gen AI is making an impact, with 72% of respondents reporting faster automation processes as a result of Gen AI integration.

Upskilling remains a crucial issue amongst engineering organizations. While 82% of organizations report having dedicated learning pathways for their QE teams, only 50% actively track the effectiveness of these programs. Skills such as Gen AI, Agile integration and cross-functional collaboration need to be in the realm of continuous learning.

Organizations face a lack of comprehensive test automation strategies and reliance on legacy systems as key barriers to advancing automation efforts.

What Is the Way Out?

The problem isn’t AI per se, it’s how we use it. The recommended fix is cultural and practical, i.e., leaders need to frame AI as a collaborative tool that demands context and critique, and hold AI?assisted work to the same standards as human?only output.

The big takeaway? Companies need to be open, offer training, and bring employees into the process if they want AI adoption to feel empowering instead of threatening. Done right, AI can help teams grow; done poorly, it just fuels fears of becoming obsolete.

The gap between what employees fear and what employers want is widening. Companies are demanding AI-literate workers, experimenting with tools like vibe coding, and hiring for roles that didn’t exist a year ago, while cutting back on entry-level positions. The solution isn’t less AI, but better AI adoption. Leaders need to be transparent, invest seriously in upskilling, and treat AI as a partner rather than a surveillance or replacement tool. When employees are trained, trusted, and involved, AI becomes empowering. When they’re not, it simply amplifies anxiety about becoming irrelevant.