After the United States, the “Great Resignation” phenomenon crossed the Atlantic Ocean to reach Europe. This situation is undoubtedly the result of the mental exhaustion felt by most sectors in the aftermath of the Covid-19 pandemic. Thus, decision makers are facing a mental health crisis of unprecedented scale. To take care of their employees and retain talent, it is their responsibility to take concrete and sustainable measures.
Fight stress at the root
In March 2022, 41% of French employees said they were experiencing psychological distress, up three points from October 2021. To stem this incredible growth in psychosocial risks, many employers are now turning to AI and deep learning mobilization solutions.
Technologies are known for their ability to combat stress, but decision makers must mobilize them to try to make a difference in the long term. Employees who experience high levels of stress over long periods of time inevitably face burnout or serious illness unless they quit. Therefore, it is necessary to address the problem at its root before stress-related disorders arise. As always, prevention is better than cure. This is where AI solutions can play a major role.
Use AI for data analysis and diagnostics
While many AI use cases are yet to be explored, this technology is already changing the practices of many organizations and is helping to significantly improve the mental health of workers. Visualization and data analysis can reveal potential failures that can be business critical and AI excels in these skills. Capable of processing massive amounts of data in real time, it can detect recurring patterns to determine responses to them.
In the field of health, for example, skin pictures or X-rays are often the only way to detect and confirm a medical problem. Interpreting such images can be challenging, and in the context of a shortage of specialists and a rapidly increasing demand, providing an accurate diagnosis and appropriate response is a real challenge for medical teams. A situation that not only causes stress to the medical staff, but also compromises the quality of their work and has a direct impact on the health of their patients.
By processing hundreds of thousands of images much faster than a human can, AI tools can meet this challenge. Thanks to deep learning, they have the ability to learn the diagnosis of pathology from millions of images, more than a doctor ever sees in his life.
Thus, the right AI software can produce preliminary diagnoses in a very short time to detect high-risk cases. Doctors can then analyze these evaluations, confirm or refute the final diagnosis, and prescribe appropriate treatment. Thus, medical institutions can treat more people in the same period of time while increasing the efficiency and quality of their services and protecting the mental health of their employees.
Artificial intelligence to reduce the pressure of daily work
Employees in many professions face fatigue and stress on a daily basis, particularly those in safety or maintenance critical jobs. Engineers or maintenance operators may be particularly responsible for maintaining 24/7 availability of large, complex infrastructures such as factories, electrical grids, transportation infrastructures, or large digital architectures. These responsibilities place tremendous pressure on employees due to the significant consequences of a potential breakdown.
Because failures can occur at any time, infrastructure and DevOps managers must be constantly active or adopt an on-demand mechanism to handle urgent and complex situations, often with only limited support. In some circumstances, urgent calls and alerts turn into false alerts, causing unnecessary stress and fatigue.
Deploying reliable monitoring of IT systems is essential. To do this, the use of software applied telemetry, along with an intelligent monitoring platform is the best solution to support the workers who occupy these critical jobs. This platform can act as an automated guardian that constantly monitors all systems without the risk of fatigue, lack of focus, or stress. While the ability to observe and artificial intelligence does not replace the experience and knowledge of engineers, it does provide them with certainty that accidents will not be overlooked due to human error.
When the monitoring platform detects an anomaly, the AI performs an initial assessment of the situation as well as a root cause analysis (or RCA) before recommending appropriate action. This allows engineers to act faster in crisis situations, knowing that their behavior is supported by AI-based technology. Thus, Observability and AI contribute to alleviating their stress by acting as a second pair of eyes.
Artificial intelligence as a long-term solution
Using the vast amounts of accessible telemetry data, AIOps systems are able to automatically detect and report anomalies that would have previously gone unnoticed. A crucial way to allow employees to focus on incidents that need real attention without worrying about missing out on a potentially serious incident.
Whatever the sector of activity, the adoption of observational ability and artificial intelligence thus enables companies to more effectively evaluate the experience and skills of their employees by reducing manual processes subject to human error, and focus their attention on more strategic tasks with added value. In the long run, this is a critical lever for reducing employee stress and tension while improving their commitment.
Tribune By Sophia Chidelville, France Sales Director of New Relic
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