Jorge Zuñiga Blanco explains how artificial intelligence is building better work teams

When the possibility of artificial intelligence (AI) first gained popularity, it was feared that it would replace millions of workers and this fear dominated the headlines. However, since then, the nuance has changed. Jorge Zuñiga Blanco, a successful entrepreneur and technology expert from Costa Rica, discusses how AI is helping workforces improve their operations.

While it is true that autonomous robots and intelligent software will replace us in some jobs, they will also create new ones. In fact, research has found that job creation will outpace job losses by 1.8 million to 2.3 million. But AI isn’t simply creating new career opportunities. It’s also helping leaders build better, more agile teams. The following are three areas where AI is driving change in how companies hire, train, and improve their workforces.

Many companies expressed intentions to improve gender equity in recent years, but there are many people who cannot do it alone. People are prone to making prejudiced decisions even when they consciously try to remain neutral. States Zuñiga, “A hiring manager may think they are objective when evaluating candidates’ resumes, but even a person’s name or address can have certain connotations about their gender, ethnicity, and socioeconomic backgrounds.” Try as they might, most people can’t help but be influenced by those subtleties.

New AI-powered platforms help get more diverse candidates through the door by evaluating and admitting candidates through more objective lenses. Unlike humans, software programs can be designed to ignore some data that could lead to biased recommendations or to evaluate based on performance on a task rather than the origins. While AI assessment isn’t perfect (it’s built by humans, after all, and may be designed with unconscious biases), it can help ensure that a wider variety of candidates are considered in the hiring process.

An example is which team members are included in the interview panel when a candidate comes to the office for a job. If a woman of color meets exclusively with white men, she might assume two things: that there are no other people of color in the company (let alone other women of color) or that none of those women have decision-making positions. Whatever the case, you might find yourself reluctant to be hired as the first person to break with the company’s apparent hiring pattern.

In reality, there may be several people of color on the team, many of whom could have leadership roles. However, because hiring managers always carry the same interviewers without considering the impression being made on potential candidates, they could end up losing talented people.

Beyond the hiring process, AI can also help with the onboarding process and ongoing employee training. This is essential, particularly as the speed of technological change continues to accelerate. Technology is present in every job,” asserts Zuñiga, “and employees will have to learn new skills throughout their careers if a company doesn’t want to be left behind.” However, not everyone learns at the same pace or in the same ways. Day-long trainings and those based on presentations by specialists are not as effective, not as efficient, as personalized training programs.

Meanwhile, management or leadership teams can have access to a dashboard to see what employees are doing. If someone is struggling in a particular area, they might approach that person to find out what’s going on. Perhaps you need additional support or mentoring to really start making progress.

Even in personalized training programs, it is necessary to make employee performance reviews. Analyzing the performance of team members periodically allows you to see what each one is doing on an individual level, and helps you better understand their challenges and motivations.

AI can enhance traditional performance reviews by bringing in a host of new postures and metrics that will create more productive conversations. By looking at hard numbers related to a team member’s performance, sales data, a campaign ROI, or leads generated, for example, you can identify positive and negative trends at a glance. But it can also gather more comprehensive contextual information that connects a person’s work to the company’s overall goals.

In a media or marketing company, there may be a temptation to reward public persons for accumulating a significant number of followers on social media. However, it is important to analyze the long-term impact of emphasizing social influence.

When using AI-generated data in performance evaluations, business leaders must always weigh the circumstances. The power of AI is that it can show you what’s important to your customers, and you can use those metrics to define how you evaluate your employees. However, it is essential that it also study the long-term effects of such practices.

Finally, the biggest advantage of AI in performance reviews is immediacy. Instead of reactive quarterly reviews, leaders will be able to provide coaching to team members while projects are ongoing, allowing them to have an effect on results in shorter timeframes.

Written By

Jorge Zuñiga B