These days, it’s rare for people to find a job that truly makes them happy. Even with decent pay, good benefits, and work-life balance, many employees feel less motivated. This has led to what we now call quiet resignation or quiet quitting, when people do only what their job requires, without extra effort or enthusiasm. At first, it may not look like a big deal, but over time it can cause serious problems.
According to McKinsey, the cost of quiet quitting can be almost as high as those of people actually leaving. Companies often face lost productivity, higher hiring and training expenses, and lower efficiency as new employees take time to adapt. In other words, quiet quitting silently drains organizations much like high turnover does.
This raises an important question: how can companies tackle this hidden threat before it escalates? More importantly, can AI help spot the warning signs early and give leaders a chance to re-engage employees before they walk away, mentally or physically? Let’s explore.
Understanding What Drives Quiet Resignation
Quiet resignation is not always easy to notice, because it doesn’t mean the employee is actually leaving. They still do their job, but only the basics, no extra hours, no extra projects, and no extra effort. It’s a quiet sign that something is bothering them, maybe the culture, the way they’re managed, or the amount of work. At first it may seem small, but over time it can cause serious problems. So what are the early signs of quiet resignation? Let’s find out.
Lower participation: You may notice performance-related signs such as showing less interest in meetings, particularly the ones where they once contributed actively, or choosing not to share their ideas.
Behavioral changes: You may notice shifts in their attitude, such as showing frequent frustration or complaining unnecessarily about management.
Productivity drops: Quiet quitting often leads to lower productivity. If you are already tracking performance metrics and notice a decline, it may be an early sign.
Detachment from others: Another sign is when employees start isolating themselves, often keeping to themselves or using headphones for long periods instead of engaging in the workplace’s social interactions.
Absenteeism: Employees may start taking more sick days than usual or often say they feel tired or have headaches.
How AI detects Quiet Resignation
We’re all familiar with traditional ways of spotting disengagement, like performance reviews or pulse surveys. But these often capture only surface-level data or come in too late. With AI, employers now get deeper insights that allow them to act early and take proactive steps before the situation worsens. Let’s explore how this technology predicts quiet resignation.
- Sentiment analysis: Sentiment analysis helps organizations understand employees’ feelings—both positive and negative—about their work, colleagues, managers, and the company overall. AI-powered tools can track messages, emails, chats, and feedback in real time to spot shifts in sentiment, identifying early signs of burnout, disengagement, or potential attrition. For example,Blue Tokai’s AI chatbot Nikki leverages sentiment insights to boost job satisfaction and reduce attrition through a more responsive approach to workplace management.
- Beyond employee behaviour: While many AI tools focus mainly on employee behavior to forecast attrition, IBM’s Watson considers a broader set of factors. These include time between promotions, overall tenure, and potential friction points such as long commutes or frequent overtime. By analyzing these attributes, the AI can alert HR managers when an employee might be at risk of leaving, enabling HR to act proactively instead of reacting after turnover occurs.
- Personalize listening: While many AI tools focus solely on analyzing employee traits without direct interaction, Marico is taking a different approach. The company has implemented an AI-driven tool that continuously engages with employees, listens to their challenges, and provides real-time insights to the HR team. Amit Prakash, Marico’s CHRO, reviews daily prompts shared by employees, cross-checks the information, and coordinates with HR personnel to address issues promptly, all while ensuring confidentiality. The HR team at Marico connects with at least four to five employees daily to gauge sentiments and identify potential attrition risks.
- Predictive analytics: Predictive analytics is key to understanding and reducing employee turnover. By examining historical and real-time attrition data, AI can detect patterns and trends that signal potential departures. This proactive approach has proven impactful. Companies using predictive analytics in HR have reported a 30% reduction in turnover, saving organizations with 100 employees up to $1 million annually. Google leverages predictive analytics insights to intervene early and retain valuable talent before issues escalate.
The Way Forward
We often hear concerns about AI taking over jobs, but this article sheds light on a different, positive side of the technology, its ability to help organizations retain their top talent. AI-powered features like sentiment analysis, predictive analytics, and personalized listening allow companies to detect early signs of disengagement and quiet resignation.
By acting proactively, organizations can safeguard their most valuable human resources but also save significantly on the costs associated with hiring and training new employees. It’s time for companies to embrace AI not as a replacement, but as a strategic partner in keeping their workforce motivated, connected, and committed.
