Why Culture Amp Launched an AI-Powered Coaching Tool


Business leaders may know Culture Amp as the software for rolling out engagement surveys and understanding employee sentiment. The company is taking an interesting approach with its new, AI-powered agentic offering: a performance and career coach for employees and leaders called AI Coach. This offering will leverage the data behind years of employee surveys and culture measurement to give people and team leaders actionable ideas and automated outreach.

“If we think about our mission of creating a better world of work, we see the power of coaching as being really critical to that,” Amy Lavoie, VP of people science experience at Culture Amp, told Newsweek. “But also, coaching has historically been really kind of reserved for a few people in an extremely manual and expensive way.”

The new tool launches in Q3 2025, according to a company release, which also notes that AI Coach draws on insights collected from over 1.5 billion workplace data points and a large language model (LLM) “specifically trained using industrial and organizational psychology principles to deliver purpose-built workplace coaching that drives impactful behavior change.”

While Culture Amp has long provided leaders with datasets and survey tools, the purpose of AI Coach is to deliver real-time employee sentiment to leaders and offer takeaways from behavioral data so that managers don’t have to parse through dense reports for actionable information.

Culture amp screenshot 4
Culture Amp’s AI Coach offers proactive advice to managers and employees around goal setting and performance.

Culture Amp

“AI Coach is not just about providing advice; it’s about enabling managers to develop crucial skills, navigate difficult conversations, and inspire meaningful action within their teams,” said Chris Mander, chief product officer at Culture Amp.

Richard Taylor, senior vice president, people experience at Nasdaq, said AI Coach “democratizes access to personalized guidance, empowering managers to lead with confidence.”

The feedback that managers and employees receive from AI Coach will be customized for their department, level and other contextual information.

One might think Culture Amp would deploy artificial intelligence (AI) and agentic capabilities to help people make more surveys faster. But Lavoie explains that the company and its product organization saw an opportunity to advance the platform’s capabilities.

“I don’t think the answer is more data and insights, it’s actually the story of the data,” Lavoie said. “How do you, like, help me weave all these things together alongside the context of my organization, to serve it up in a sentence or two that helps, helps people remember it and want to do something with it.”

Overworked managers sometimes don’t have time to review engagement survey data. Because the data is backward-looking and takes time to analyze, managers are reviewing information that is not as current as it could be. They don’t always have strong data judgment to read through graphs and charts to glean the important takeaways for their teams.

“Very often, if you just present [managers] with a ton of insights, they actually feel paralyzed, not motivated to work,” Lavoie said. “It’s that story, that narrative of the data in the context of my organization, that AI Coach can help them do without always needing [a] people scientist who can do that for them.”

Culture Amp screenshot 3
Culture Amp AI Coach can help managers in real-time as they respond to employee questions and requests.

Culture Amp

Advancements in AI and machine learning have allowed for this advancement in Culture Amp’s product and potentially the practice of management, if better assistance is available to employees at work.

“We can know what the other managers who’ve done well, what did they do to improve their scores. In the past […], you just have to go talk to hundreds of people,” Lavoie said. “Identifying what are the behaviors that make the biggest difference on improving scores, if somebody is working on, decision making, then we can go look. We can go isolate the teams that have improved decision making and see specifically what they have done and what they’ve logged in the system, and then bring that perspective back.”



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