Now AI analyzes candidates' voices during hiring.

In the TechCrunch podcast hosted by Sara Lussen, Mappa startup founder discusses how artificial intelligence helps companies evaluate not only candidates' professional skills but also their behavioral compatibility with the team, creating more effective and balanced workforces.

Problems with traditional hiring and the new AI-driven approach

Finding the right employees is one of the most challenging and critical tasks for companies. Many organizations spend significant time and money on recruitment processes: reviewing resumes, conducting interviews, and administering technical tests. Despite these efforts, companies still frequently make hiring mistakes. Employees who appear ideal on paper sometimes struggle after joining the team. This issue has prompted many companies to reconsider how they evaluate candidates and which factors truly predict success in the workplace.

The TechCrunch podcast episode Using AI to Hire for Compatibility, Not Just Skill discusses a new hiring approach that uses artificial intelligence to analyze not only a candidate's professional skills but also their behavioral compatibility with the team. The episode features Sara Lussen, founder of the startup Mappa, which develops technology to assess behavioral traits through voice analysis.

The main problem with traditional hiring is that it is heavily focused on skills, experience, and education. These factors are important, but they do not always determine how effectively a person can work within a team. Many companies assume that hiring the most qualified individual will automatically lead to better results. However, research and practice show that this assumption is often incorrect.

Sara Lussen notes that throughout her career, she has repeatedly encountered situations where candidates with excellent resumes failed to deliver results after being hired. Meanwhile, people who seemed less impressive on paper sometimes turned out to be highly effective employees. These observations led her to question whether traditional methods actually assess the right qualities. Resumes and interviews primarily evaluate past achievements and technical skills but rarely provide reliable insight into a person's behavior, communication style, decision-making process, or ability to collaborate. These factors are critical for understanding how a person will function within a team.

How Mappa and voice analysis work

To address this issue, Lussen founded Mappa, a company that uses artificial intelligence to analyze voice patterns and behavioral signals, creating psychological and behavioral profiles of candidates. Instead of focusing solely on past achievements, the technology aims to understand how a person thinks, communicates, and interacts with others.

The system works as follows: candidates answer a series of short questions, and their responses are recorded as voice messages. AI analyzes various aspects of speech: rhythm, tone, pauses, word choice, and other linguistic patterns. These elements can reveal how a person processes information, expresses emotions, and approaches decision-making. For example, speech pace may indicate confidence or speed of thought, tone and voice modulations reflect emotional awareness and empathy, pauses may suggest thoughtfulness or hesitation, and word choice shows whether a person tends to think analytically, emotionally, collectively, or individually.

By analyzing thousands of such signals, the system builds a behavioral profile of the candidate: communication style, leadership tendencies, adaptability, stress response, and decision-making patterns. A key idea discussed in the podcast is the distinction between similarity and compatibility in hiring. Many companies unconsciously hire people who are similar to themselves: in personality traits, education, cultural background, or thinking style. Similarity creates comfort but does not necessarily lead to effective team performance. Compatibility refers to how well individuals complement each other's strengths and weaknesses. Effective teams are built not from identical people but from individuals whose differences create balance and enhance productivity.

Advantages of voice analysis and AI in recruitment

Voice analysis is particularly effective for understanding human behavior. Researchers previously attempted to analyze facial expressions or social media behavior, but these signals are easily faked. The voice is harder to control consciously: subtle aspects of speech often reveal emotional and cognitive processes about which a person may not even be aware.

AI processes these signals faster and more accurately than humans. Traditional hiring takes weeks or months, while AI takes minutes. Additionally, using AI can reduce the impact of human biases: gender, age, cultural background, accent, and appearance. If the system is properly trained, it focuses on measurable behavioral signals rather than external characteristics. However, AI is not automatically free from bias—it depends on the data used for training.

The podcast also discusses how AI could become a standard in recruitment: analyzing interviews, assessing communication skills, and evaluating team compatibility. Similar technologies could be used by investors, schools, and banks. Nevertheless, AI should not completely replace human judgment. It serves as a support tool, providing additional data for recruiters and managers. Experience, intuition, and contextual understanding remain important.

Key takeaways and future outlook

Successful teams are built not only on talent and skills but also on communication style, emotional intelligence, collaboration habits, and compatibility. Combining traditional methods with AI-driven analysis of behavioral signals helps make more informed decisions and build balanced teams.

In the future, hiring may shift from asking, "Who is the most qualified candidate?" to "Who fits best with this specific team and organizational culture?" Understanding the difference between skills and compatibility leads to more efficient workflows and better outcomes for both employees and companies.