How AI can reduce pressure in the workplace

By Mark Crawford, VP, Strategy and Execution, New Relic.

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Good business leaders should always be looking for tools that can reduce the pressure placed upon their workforces. In the post-pandemic new normal, this will increasingly mean a reliance on technology.

Emerging technologies are increasingly finding their place across all verticals as ways of reducing pressure on employees. Artificial intelligence (AI) has a hugely disruptive role to play in this. AI and machine learning (ML) are now so advanced that they can massively reduce workloads, offloading more mundane tasks onto computers.

Getting to the root of the problem

To alleviate workplace pressure, business leaders can’t just deal with the end result, they need to address the root cause – and the pandemic forced many businesses that were lagging in this respect to finally do just that. This means understanding how and why employees feel their working environment has become pressurised. If they don’t, they are in danger of creating a cycle that, in the worst-case scenario, will lead to burn-out, illness, or resignation.

AI – Analysing data to save time, and reduce stress

AI is well positioned to tackle some key areas of pressure that occur within businesses, while streamlining processes to free up employee time. In particular, AI can process gigantic amounts of data in a very short time. From this data, it can then quickly detect specific signals and derive recommendations for action.

For example, imaging centres create some of the largest data sets for healthcare facilities and the technical knowledge required has created a talent shortage. Dermatologic pictures, X-rays and CT scans are often the only way to diagnose patients and structure courses of treatment. However, the current shortage in specialists and fast-rising demand puts the burden on medical teams already stretched to their limit, increasing the risk of errors. AI can learn to diagnose risk by analysing millions of pictures, so by introducing it into these scenarios, medical teams can process hundreds of thousands of images accurately and faster than a human could.

Restructuring workloads to allow AI to analyse images removes pressure from medical teams. This then lets trained human professionals focus on analysing high-risk cases, deriving final diagnoses, and providing concrete treatment, saving highly valuable time and reducing stress on the individual and medical function. It also helps doctors treat significantly more people and increase the efficiency and quality of their work, while helping to balance out the pressures they would otherwise be placed under.

Stress is everywhere

Pressurised workplaces are, however, not exclusive to healthcare and the emergency services. For instance, engineers and operators ensuring that large and complex infrastructures keep operating 24/7 often face huge amounts of pressure. From power grids to transportation networks or large digital architectures, the possibility of an outage puts people and revenue at risk.

Unsurprisingly, the monitoring and supervision of IT and software architectures in companies has added considerable pressure to IT teams. You only have to look at the number of recent high-profile outages, including a string of airlines throughout summer, to have an idea of the pressure placed on the IT function. Operating 24/7 or on-call and having to deal with urgent and complex situations with very limited support, DevOps and Infrastructure teams simply can’t enjoy luxuries such as work-life balance.

Businesses should invest in reliable system monitoring based on software telemetry and intelligent observability practices that can act like a silent guardian. Using this technology to monitor all systems 24 hours a day removes the fatigue related to alert noise and the burden of possibly overlooking critical incidents, returning power to the team's hands.

While practicing observability or using AI cannot replace the expertise and knowledge of engineers, it can, and does, allow IT teams to take quick action when the platform detects an anomaly. This helps to streamline processes and ensure that resources and employee wellbeing can be prioritised, without compromising on the business or user experience.

Reducing false alarms, reducing stress

Observability and AI reduce false alarms and more accurately recognise critical situations, removing noise and detecting weak signals. In utilising the vast amount of available telemetry data, AIOps systems can automatically detect anomalies without the need for manual engineer insight or process. By providing automated Root Cause Analysis and context for issues, AI dramatically reduces the time to understand and resolve incidents. It also frees up the DevOps team from significant toil, letting them focus on high value activities, their own wellbeing and, importantly, the areas of the business that will drive revenue.

Regardless of the industry, employees and businesses must put mental health first. AI provides an understanding of their stresses and pressure points and helps to implement measures that drive the team’s efficiency.

In this way, AI and telemetry data not only reduce the workload of employees, but also enable their personal development in the long term. This ensures the workforce is happy, healthy, and motivated to drive the business forward. It is time to embrace technology that will embed this ethos into each and every business, now and into the future.

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