How Artificial Intelligence is Revolutionizing Companies’ Mental Health
Over the past year it has become evident that overall companies present weaknesses in terms of taking care of the workforce’s mental health state. As of today, we know that investing in the prevention of mental health problems in the organization equals money savings. Among the benefits are increased engagement or lawsuit cost savings. Although it is a growing topic of interest, it can still be disturbing to think that there are few actions being taken in terms of evaluation and prevention that are actually valuable on a daily basis.
However, the present problem is no surprise when we take into account that Human Resources departments tend to only use traditional methods to assess their employees. Thus, most companies report the mental health risk rating based on a survey and reporting methodology that often takes several months to run.
Consequently, there is an urgent need to improve the current employee evaluation methodologies. It is here that new technologies, such as Artificial Intelligence, are stepping in to fill this organizational gap.
Currently, most AI SaaS evaluate high-value metrics in the market. Thus, the most commonly offered metrics are engagement, burnout, turnover and well-being levels. Another shared aspect among industry leaders is that they provide value to users on a daily basis, which goes beyond any current standards of traditional reporting. However, one aspect in which there is not much consistency across companies is in the way data is visually displayed to the user. Companies use diverse options such as bar charts, scatter graphs, and color charts among others, but there is no standardized system being applied.
The most groundbreaking AI tools to date are those based on Natural Language Processing (NLP). This is because they can measure psychological risks of employees based on written and spoken conversations at the corporate communication tools. These SaaS are probably the most desirable at psychological gauging, since it gathers data on how workers are interacting. The software’s Neural Network delivers a probability distribution yielding values based on the interpretations of Certified Psychologists. Yet, whenever we deal with Neural Networks it is particularly relevant to ensure that a large data set is involved and that the psychological metrics have been validated.
In contrast, other SaaS are based on inducing psychological metrics based on daily short questionnaires or action-based measures such as time spent on the dashboard or working hours. Although these corporations also provide interesting values, it’s important to highlight that they don’t really provide a value that represents psychological risk states, but rather focus on potential behavioral factors that are related, making them more uncertain. Besides, some of the disadvantages of questionnaires include that they require a time cost for the employees, that they depend on the employee’s insight ability, and that they are not always lie-sensitive.
It comes as no surprise then that the most promising softwares are the NLP based, as they bring with them multiple advantages for People Analytics over those that rely on questionnaires. Personally, a benefit of NLP SaaS which fascinates me is that it reduces the amount of time spent searching for at-risk workers, since you no longer have to wait to get the questionnaire results.
To conclude, these new additions to the Human Resources team are growing to be revolutionary and promising. By the looks of it, Artificial Intelligence methodologies are here to stay.
What do you think about these AI softwares?
