The COVID 19 pandemic caused economic damage for many companies right from the start - but now managers and decision-makers are slowly realizing how deep and far reaching the consequences are. Especially when discussing the mental health of their employees (opens in new tab). The multiple stresses of work, caring for friends and family and, of course, the fear of perhaps losing jobs or falling ill, have been a distressing daily routine for many people. While many have managed to hold on over the last year and a half, stress-related illnesses and absences are currently on the rise.
Gregory Ouillon is EMEA CTO for New Relic (opens in new tab).
Employees who were already on the verge of being overworked before the pandemic began (as is often the case in the healthcare sector, for example) are now finally reaching their limits. This situation poses a special challenge for those affected as well as for their employers, and the Great Resignation might well be a symptom of this workforce mental exhaustion. Many employers had never had to deal with mental health issues of their employees to such an extent and such a scale before - but this situation required durable and concrete action.
Get to the root of the problem: Reducing fatigue and stress with AI solutions
Stress-related and mental illnesses are becoming increasingly common in the workplace, with a staggering 79% of British people commonly experiencing work-related stress. As a result, many employers have recognized the benefits of specialized, software tools leveraging AI (opens in new tab)/machine learning (opens in new tab), that enables new ways of providing direct sell-care mental health support to employees.
But what is the long-term benefit of providing care to an employee if he or she remains exposed to the same levels of strain and stress as before? It creates a cycle that, in the worst-case scenario, will lead to burn-out, illness or resignation.
It is therefore important to tackle the problem where it starts and to reduce the basic stress and strain level of employees before stress-related illnesses can occur. For this, AI solutions do have a role to play.
AI as a data analyst and diagnostic tool
Many tool categories can greatly improve mental health by reducing stress, toil, and fatigue. Many professions require visualizing and analyzing very large amounts of data (opens in new tab) to detect potential issues that might be business critical or mission and safety critical. Applied smartly, Artificial intelligence is particularly good at one thing: processing gigantic amounts of data within a very short time, detecting specific signals and deriving recommendations for action from it.
For example, dermatologic pictures, X-rays or CT scans are often the only way to detect and confirm what a patient is suffering from and how he/she needs to be treated. However, the interpretation of these images is obviously difficult and with a shortage in specialists and fast rising demand, this puts the burden and toil on medical teams to interpret thousands of cases at a high pace with the imperative of avoiding false negatives. This puts medical staff under significant stress and pressure, as the quality of their work has a direct influence on the health of their patients.
Today, AIs for the medical sector can process hundreds of thousands of images accurately and faster than a human could, having learnt 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, which a doctor could then analyze with the help of his or her experience and derive a final diagnosis and concrete treatment from it. In this way, doctors could treat significantly more people in the same amount of time and increase the efficiency and quality of their work, while at the same time protecting their own health.
Daily pressure in everyday work
This fatigue and stress exists for many mission-critical and safety-critical roles today, for example for engineers and operators who need to ensure that large and complex infrastructures keep operating 24/7, like manufacturing plants, power grids, transportation networks or large digital architectures.
Employees who are responsible for the monitoring and supervision of IT and Software architectures in companies are often under such particular stress. This stress does increase with the size and complexity of the IT infrastructure and the extent of the consequences that an IT incident could have, e.g. halting transactions of a major e-commerce (opens in new tab) site, preventing consumers from accessing their bank online or booking a vaccination appointment.
Also, outages and performance issues can happen at any time, and infrastructure and DevOps teams, operating 24/7 or on-call, can have to deal with urgent and complex situations with very limited support, e.g. in the middle of the night, when most colleagues are unavailable. They often have to deal with many false positive alerts which do take a toll in the long run.
For such critical roles, deploying reliable system monitoring based on software telemetry and an intelligent observability platform is the best solution. To put it simply, an intelligent observability platform can act like a silent guardian, monitoring (opens in new tab) all systems 24 hours a day. And it does so without getting tired, unfocused or stressed.
Observability or AI cannot replace the expertise and knowledge of engineers, but it supports them with the secure feeling that they won’t overlook incidents. Since every incident remains a stress factor that requires quick action, when the platform detects an anomaly, the AI can also provide an initial assessment of the situation, a Root Cause Analysis, and an appropriate recommendation for action, with detailed context and insights.
AI as a solution
The decisive factor here is that Observability and AI solutions reduce false positive alarms and more accurately recognize critical situations. Additionally, AI can detect issues, even if no alerting threshold has previously been defined by the IT team.
Leveraging the vast amount of available telemetry data, AIOps systems are able to automatically detect and notify anomalies to an employee that he or she had not previously recognized as potentially problematic. Consequently, AI systems ensure that professionals can be efficient with their time, focusing on the incidents that are actually relevant and not constantly worrying that they might miss any weak signals hinting at a developing critical incident.
In this way, companies can use the experience and knowledge of their employees in a much more targeted and effective way, which also leads to reduced fatigue and stress, higher employee satisfaction and a better balance of mental health.
AI and mental health
Regardless of the industry: with the help of AI solutions, employees can concentrate on more demanding and thus more fulfilling tasks for which they previously had no time. In this way, AI and Telemetry data not only reduce the workload of employees, but also enable their personal development in the long term. Benefiting the company as a whole and ensuring that they can focus on the mental health, culture and experience of their employees, now and into the future.
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