Have you ever imagined that algorithms could “read” the mood of your employees, anticipating absences and necessary adjustments to workflows, avoiding wasted time, layoffs and even burnout?
Behavioral monitoring may present itself as an HR strategy, but it clearly presents challenges. Artificial intelligence (AI) tools, used by large companies, monitor software usage, screen switching patterns, time spent on repetitive processes, etc., to extract signs of fatigue, dissatisfaction or overload, as well as opportunities to adjust workflows. In many cases, this analysis makes it possible to identify operational bottlenecks and optimize working hours, reducing costs, improving productivity and also contributing to the health of workers.
It is not enough to install sensors and reports: this practice is on delicate ground, and transparency and trust must be maintained between employers and workers. The General Personal Data Protection Law and good practices require transparency; employees need to know what data is collected and for what purpose, and it must be clear that any discriminatory practice is clearly avoided. From a human perspective, the line between care and over-control is thin, and the cost of losing inner trust is high.
Below we point out 4 good practices for mitigating risks and maximizing value:
1. Clearly explain to employees the why and how of data collection (legitimate purpose), formalizing the respective contractual instrument;
2. Use aggregated and statistical analysis, not invasive individual monitoring, as well as seeking to avoid discriminatory practices;
3. Combine AI insights with human interpretation, contextualization, and dialogue with managers; and
4. Regularly assess the impact on the organizational climate and adjust collection policies.
When applied well, this behavioral intelligence stops being a “big brother” and becomes a strategic resource for everyone involved: it helps retain talent, adjust workloads, anticipate disruptions, and protect employee health. The line between competitive advantage and labor risk is narrow, and technology alone isn’t a solution. Legally evaluating these projects, designing clear data governance policies, and ensuring that implementation respects culture and transparency is a complex task, but with due caution, it can represent an effective competitive advantage and talent retention.
