Historically, there has been a lack of science or objectivity when it comes to building teams in the workplace. Instead, we have seen a tendency to rely on certain “go-to” people over and over again. In the process, new sources of talent can be overlooked, negatively impacting team outcomes and impacting inclusion and diversity.
The same problem can apply to the talent acquisition process, where there is little to no science behind selecting candidates with both a good skill set and a good cultural fit. Artificial intelligence technology may offer a solution.
How AI Can Build Better Teams
“As an executive, I've seen firsthand how AI can transform the way we approach talent acquisition, team building, and employee development,” says Brady Brim DeForest, CEO of technology consulting firm Formula.Monks and best-selling author. Smaller is better: Leveraging small, autonomous teams to drive the company's future (Micrometer Press, 2024). “By analyzing data about team members’ individual strengths, working styles, and past performance, AI can create teams that are more likely to work well together, increasing overall productivity and job satisfaction.”
Traditional team-building methods “often rely on subjective assessments and limited data, leading to suboptimal team dynamics and skill mismatches,” Brim DeForest said.
AI provides objective, data-driven insights to enable more informed decision-making, he said.
For example, “AI can assess how different personality types and work styles interact with each other and predict what combinations are more likely to produce high-performing teams,” Brim DeForest says.
Building a team and selecting team members
“AI-powered team-building solutions, like Asana's AI Teammate, harness the power of machine learning to analyze a wealth of employee data, including skills, experience, personality traits, communication styles and performance metrics,” says Deborah Perry Piscione, co-founder and CEO of Work3 Institute, a Newton, Massachusetts-based research and advisory services firm, and author of the upcoming book, “AI Teammate: What Works Like to Do Better.” Jobs die: How disruptive technologies will change the way we work (Harvard Business Review Press, 2025).
An employee's hobbies and passions could also be included in the mix. “These highly sophisticated algorithms uncover patterns and insights that human managers might miss, like hidden talents, complementary work styles or even personal issues an employee is facing,” she said.
Gina Hartigan, chief human resources officer at Kantata, an Irvine, Calif.- and London-based B2B software provider specializing in technology for professional services organizations, says AI can be used to analyze team dynamics and suggest optimal team configurations based on personality traits, skills and working styles to improve collaboration and productivity.
During the recruiting phase, AI is integrated with a company's values and culture to create standardized job profiles and onboarding processes, Hartigan said, so that “AI creates efficiencies, but the human element of maintaining the culture and values of the organization remains intact,” he said. AI is also used to create a personalized onboarding experience for new hires by recommending content, training and connections based on their role, interests and learning pace.
Ezekiel Lewis is vice president of talent acquisition at BairesDev, a software outsourcing company based in Mountain View, Calif. Lewis says that an AI-powered team recommendation engine has fundamentally changed the company's approach to team dynamics, satisfaction and productivity. The engine assembles teams for client projects based on skill sets, experience and cultural alignment, enhancing the efficiency and talent selection process.
By automating talent screening and providing a short list of candidates quickly and accurately, project management teams can evaluate candidates more efficiently and thoroughly. Additionally, Lewis says, “AI tools can also assemble balanced teams that consider skills, experience, and cultural fit based on the unique needs of each department and project.”
Monitor your team's progress
Once a team is formed, AI can be used to continually monitor team dynamics and performance, proactively flagging potential issues and recommending interventions or coaching where needed.
“As the AI learns from successive projects and team interactions, its recommendations will become increasingly sophisticated and effective, even taking into account when particular employees are most productive or creative,” Piccione said.
AI can also be used to track key performance indicators and provide real-time feedback to employees and managers.
“This continuous monitoring allows for timely intervention, ensuring issues are addressed before they become severe,” says Brim DeForest. “Furthermore, AI can analyze communication patterns, collaboration metrics, and other behavioral data to identify potential friction points within teams. By proactively addressing these issues, organizations can foster a more harmonious and productive work environment.”
Employee engagement is a key component to the success of individual employees and teams, and here too, AI can play a key role.
Stay on top of employee engagement
Hartigan said Cantata is using AI-powered tools to analyze large amounts of employee feedback to gain insights into team morale and identify areas for improvement.
“Every quarter, we download the written feedback from our weekly pulse surveys and use AI tools to understand employee sentiment across themes,” she says. “What previously took weeks to compile and analyze now takes minutes to hours. AI is 80% of our goal and helps build engagement by creating this critical and timely feedback loop.”
As team needs change and emerge, and team members may also change, AI tools can be used to handle various development and upskilling efforts efficiently and effectively.
Development and skill development
Traditional organizational training and development programs have historically taken a one-size-fits-all approach that may not be effective for everyone, Brim DeForest notes. AI can tailor training programs to an individual's needs by creating customized development plans that target specific skill gaps and drive continued growth. This AI-driven, personalized approach not only increases employee satisfaction and engagement, “it also contributes to the success of the organization as a whole,” Brim DeForest says.
Importantly, the use of AI in development and upskilling should be augmented by human support, Hartigan noted.
“With less time for HR to spend on administrative tasks, they're able to strengthen engagement efforts, stay on top of team morale and act more agile to embody and deliver on our values of building trust and creating great customer experiences,” she said.
Implementation Best Practices
Implementing an AI solution to help build effective teams requires “access to robust employee data from HR systems, project management tools, and communication platforms, and a clear understanding of what makes up a successful team in your organizational context,” Piscione says. That requires working closely with your AI vendor to “train and validate models and establish a governance framework for using AI recommendations in decision-making.”
It’s also important to keep in mind that AI is not infallible.
“AI is still in its early stages, so it will inevitably make mistakes and will require human oversight and guidance,” Piscionne said, adding that “AI is only as good as the data used to train it.”
Piccione recommends that organizations “start with clearly defined use cases that align with your top business priorities and then focus efforts and resources where AI can create the most value.”
Lewis agrees: If the information used to train AI tools is biased, that bias can be perpetuated, he says, and we could end up over-relying on AI to make decisions that require human judgment and empathy.
“To avoid this, establish a clear process for assigning key decisions to your team,” he recommends. “A fully automated process run by AI loses the human touch. That's why we not only use AI tools, but also have a team of experts who validate AI suggestions and decisions and ensure candidates have human contact and feel supported throughout the selection process.”
“AI is meant to augment and support human decision-making, not replace it entirely. While AI can provide valuable insights and recommendations, human judgment is still essential to address the nuances and complexities of team dynamics,” Piscione said.
Kantata understands this well. “At Kantata, one of our core values is 'Embrace Authenticity,'” says Hartigan. “As we leverage the power of AI, we always ensure that our opinions and decisions are authentic and aligned with the specific needs of our employees, customers and industry. This careful balance of AI and human oversight optimizes our HR function and lays a solid foundation for future growth.”
Lynn Grensing Poffal is a freelance writer living in Chippewa Falls, Wisconsin.
