Using AI to Build Better Teams

When it comes to building workplace teams, science and objectivity have historically been lacking. Instead, certain “go-to” people seem to be called upon again and again. In the process, new sources of talent may be overlooked, which can negatively impact team outcomes and also have implications for inclusion and diversity.

The same issues may also be part of the talent acquisition process, with little to no science behind selecting candidates with both strong skill sets and the potential for an exceptional cultural fit. Artificial intelligence technology may offer a solution.

How AI Builds Better Teams

“As a C-suite executive, I’ve seen firsthand how AI can revolutionize the way we approach talent acquisition, team formation, and employee development,” said Brady Brim-DeForest, CEO of tech consultancy Formula.Monks and best-selling author of Smaller Is Better: Using Small Autonomous Teams to Drive the Future of Enterprise (Micrometer Press, 2024). “Through analysis of data on individual team member strengths, work styles, and past performance, AI can help form teams that are more likely to work well together, enhancing overall productivity and job satisfaction.”

Traditional methods of building teams “often rely on subjective assessments and limited data, leading to suboptimal team dynamics and mismatches in skills,” Brim-DeForest said.

AI can provide objective, data-driven insights that allow for more informed decision-making, he said.

For instance, “AI can assess how different personality types and work styles interact, predicting which combinations are likely to result in high-performing teams,” Brim-DeForest said.

Building Teams and Selecting Team Members

 “AI-powered team-building solutions, like Asana’s AI Teammates, harness the power of machine learning to analyze a wealth of employee data, including skills, experience, personality traits, communication styles, and performance metrics,” said Deborah Perry Piscione, co-founder and CEO of the Work3 Institute, a research and advisory services firm based in Silicon Valley, and author of soon-to-be-published  Employment Is Dead: How Disruptive Technologies Are Revolutionizing the Way We Work (Harvard Business Review Press, 2025).

Employees’ hobbies and passions may also be included in the mix. “These very sophisticated algorithms uncover patterns and insights that human managers might overlook, such as hidden talents, complementary working styles, or even perhaps a personal issue that an employee is faced with,” she said.

At Kantata, a business-to-business software provider specializing in technology for professional services organizations based in Irvine, Calif., and London, Chief People Officer Gina Hartigan said that AI is used to analyze team dynamics and point to optimal team compositions based on personality traits, skills, and working styles to enhance collaboration and productivity.

During recruitment, AI is integrated with company values and culture to create standardized job profiles and onboarding processes, Hartigan said. This “ensures that while AI enhances efficiency, the human element of maintaining our organizational culture and values remains intact,” she said. AI is also used to create personalized onboarding experiences for new hires by recommending content, training, and connections based on their role, interests, and learning pace.

Ezequiel Ruiz is vice president of talent acquisition for BairesDev, a software outsourcing company based in Mountain View, Calif. An AI-powered team recommendation engine has fundamentally transformed the company’s approach to team dynamics, satisfaction, and productivity, Ruiz said. The engine constructs teams for client projects based on skill sets, experiences, and cultural alignment, enhancing efficiency and the talent selection process.

Automating the screening of talent to quickly and accurately deliver a short list of candidates can help project management teams review candidates more efficiently and thoroughly. In addition, Ruiz said, “AI tools can also assemble balanced teams that consider skills, experience, and cultural fit based on the unique needs of each department or project.”

Monitoring Team Progress

Once teams have been formed, AI can be used to continuously monitor team dynamics and performance, proactively flagging potential issues and recommending interventions or coaching as needed.

“As the AI learns from successive projects and team interactions, its recommendations become increasingly refined and effective and can even weigh in when a particular employee is most productive or creative,” Piscione 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 interventions, helping to address issues before they escalate,” Brim-DeForest said. “Furthermore, AI can analyze communication patterns, collaboration metrics, and other behavioral data to identify potential friction points within the team. By proactively addressing these issues, organizations can foster a more harmonious and productive work environment.”

Employee engagement is a critical element of individual employee and team success. Here, too, AI can play an important role.

Staying on Top of Employee Engagement

Hartigan said that Kantata uses AI-powered tools to analyze large amounts of employee feedback for insights into team morale and then identifies areas of improvement.

“After each quarter, we download the weekly pulse survey written feedback and utilize AI tools to help us understand thematic employee sentiments,” she said. “What once took weeks to compile and analyze is now done in minutes and hours. AI gets us 80% of the way there and helps us build engagement by creating this essential and timely feedback loop.”   

As team needs change and emerge, and as team members may also change, a myriad of development and upskilling efforts can be efficiently and effectively handled using AI tools.

Development and Upskilling

Traditional organizational training and development programs have historically taken a one—size-fits-all approach, which may not be effective for everyone, Brim-DeForest noted. AI can tailor training programs to individual needs by creating customized development plans that target specific skill gaps and promote continuous growth. That AI-driven personalized approach not only boosts employee satisfaction and engagement, Brim-DeForest said, “but also contributes to the overall success of the organization.”

Importantly, AI use in development and upskilling should be augmented by human support, Hartigan pointed out.

“With HR spending less time on administrative tasks, we can amplify our engagement efforts, keep a pulse on team morale, and take action quicker to ensure that we live and celebrate our values to build trust and create remarkable customer experiences,” she said.

Best Practices for Implementation

Implementing AI solutions to help build effective teams requires access to “robust employee data from HR systems, project management tools, and communication platforms, as well as a clear understanding of what constitutes a successful team within the organization’s context,” Piscione said. That requires close collaboration with AI vendors “to train and validate models and establish governance frameworks for using AI recommendations in decision-making.”

It’s also important to keep in mind that AI is not infallible.

“As AI is still in its early stages, it will inevitably make mistakes, necessitating human oversight and guidance,” Piscione said. In addition, “AI is only as good as the data it is trained on.”

Piscione recommended that organizations “begin with clearly defined use cases that align with top business priorities to focus efforts and resources where AI can drive the most value.”

Ruiz agreed. If the information used to train AI tools is biased, that bias can be perpetuated, he said. There is also the potential to over-rely on AI for decisions that require human judgment and empathy.

“To avoid this, establish clear processes that assign critical decision-making to your team,” he recommended. “A fully automated process executed by AI loses the human touch. That’s why we not only work with our AI tool but also have a team of specialists who validate any suggestion/decision made by the AI and ensure candidates have contact with people and feel supported throughout the selection process.”

Piscione said, “AI is meant to augment and support human decision-making, not replace it entirely. While AI can provide valuable insights and recommendations, human judgment remains essential in navigating the nuances and complexities of team dynamics.”

Kantata understands this well. “At Kantata, one of our core values is ‘Embrace Authenticity,’ ” Hartigan said. “As we utilize the power of AI, we consistently check to ensure that our voice and decisions are authentic and align with the specific needs of our people, customers, and industry. This careful balance of AI and human oversight optimizes our HR functions and sets a strong foundation for future growth.”

Lin Grensing-Pophal is a freelance writer in Chippewa Falls, Wis.