How to support workplace mental health through AI-driven software

The COVID 19 pandemic has had an ongoing impact on businesses

But one consequence that managers and decision-makers continue to face is the damaging effects on the mental health of their employees. From work stress, through to caring for friends and families and, of course, the fear of losing jobs or falling ill, people are feeling the effects of the past 24 months. The signs are starting to show as stress-related illnesses and absences are on the rise.

This situation poses a unique challenge for employees and their employers, and the Great Resignation also referred to as the ‘Big Quit’ is no doubt a result of this mental exhaustion experienced across most industries. Decision makers are facing a mental health crisis on a scale not seen before. It requires them to take durable and concrete action if businesses are to look after their workforce, retain best talent, and survive the ongoing impacts of the pandemic.

Reducing stress at the root cause – with AI solutions Stress-related and mental illnesses are commonplace at work, with a staggering 79 percent of British people experiencing regular work-related stress. To combat this increasing issue, many employers are turning to specialized software tools that use AI/machine learning, to support employee mental health.

These technologies are being recognised for addressing stress, but it is critical that decision makers use these tools to make a long-term difference to this issue. Employees that continue to experience high amounts of stress will no doubt face burnout, serious illness, or resignation.

It is therefore important to tackle the problem at its root cause before stress-related illnesses occur, instead of looking to mitigate the consequences of work-related stress after it’s too late. This is where AI solutions can play a key role in business.

Using AI for data analysis and diagnosis

Many use cases for AI are yet to be explored, but this technology is already transforming how certain industries and organisations are operating and it’s making a significant difference to the mental health of workers. Data visualisation and analysis is a necessity for many professions as it can detect potential issues that might be business or mission critical. AI excels in this skill and is able to process gigantic amounts of data in real-time, detect patterns and derive recommended actions.

Take the health sector for example. Dermatologic pictures, X-rays or CT scans are often the only way to detect and confirm a medical issue. The interpretation of these images can be difficult and with a shortage of specialists and fast rising demand, this puts the strain on medical teams to interpret thousands of cases at a high pace whilst generating accurate diagnosis and appropriate action. This does not just place significant stress and pressure on medical staff but compromises the standard of their work and has a direct influence on the health of their patients.

But AI can help overcome this challenge. AI technologies can process hundreds of thousands of accurate images much faster than a human could. It can be taught to diagnose risk from millions of pictures, more than a doctor would ever see in a lifetime.

The right AI software could therefore produce preliminary evaluations in a very short time to detect cases with risk. Doctors can then assess these evaluations, confirm a final diagnosis and appropriate treatment from it. This means doctors could treat more people in the same amount of time, increase the efficiency and quality of their work, whilst also protecting their mental health through reducing stress and burnout.

Using AI to reduce daily work pressures

Many professions experience fatigue and stress on a daily basis, especially those in mission-critical and safety-critical roles. Engineers or operators, for example, can be in charge of maintaining 24/7 uptime of large and complex infrastructures such as manufacturing plants, power grids, transportation networks or large digital architectures. These responsibilities place enormous pressure on employees, as the risks and consequences related to machine failure are huge. This could include halting transactions of a major e-commerce site or preventing consumers from accessing their bank online.

To add to this stress, outages and performance issues can occur any time. This means infrastructure and DevOps teams must operate around the clock or be on-call to deal with urgent and complex situations with, at times, limited support. In some circumstances, these urgent calls will turn out to be false alarms, resulting in unneeded stress and exhaustion.

Deploying reliable system monitoring based on software telemetry and intelligent observability platform is the best solution for supporting these critical roles. Put simply, an intelligent observability platform can act like a silent guardian, monitoring all systems 24/7, without the risk of getting tired, unfocused, or stressed.

Observability or AI cannot replace the expertise and knowledge of engineers, but it reassures them that incidents won’t be overlooked due to human error. In fact 90 percent of IT decision makers now view observability as important and strategic to their business.

When the observability platform detects an anomaly, the AI can also run an initial assessment of the situation, a Root Cause Analysis, and an appropriate recommendation for action, with detailed context and insights. This helps engineers work faster in crisis situations with peace of mind that their thoughts and actions are supported by AI-enabled technology.

In turn, observability and AI help mitigate stress through acting as a second pair of ‘eyes’ for these workers, no matter the time or circumstance in hand. This creates a huge amount of reassurance for engineers and operators, builds their confidence in decision-making, and reduces stress.

AI as a long-term solution

By using the huge amounts of accessible telemetry data, AIOps systems are able to automatically detect and notify anomalies to an employee that have previously been unnoticed. This means professionals can be efficient with their time, focus on incidents that require actual attention and not constantly worry that they might miss a developing critical incident.

Regardless of the industry, embracing observability and AI means companies can better utilise the experience and skills of their employees by reducing manual processes prone to human error, and turning their attention to other, more fulfilling responsibilities such as strategic tasks. This also leads to reduced fatigue and stress in the long-term as employees are more engaged, experience higher satisfaction rates and a better balance of mental health.

About the Author

Greg Ouillon is EMEA CTO at New Relic. The world’s best engineering teams rely on New Relic to visualize, analyze and troubleshoot their software. New Relic One is the most powerful cloud-based observability platform built to help companies create more perfect software. Learn why customers trust New Relic for improved uptime and performance, greater scale and efficiency, and accelerated time to market at

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