How Enso brings Culture Amp’s mission to the agentic era

In the earliest days of Culture Amp, before there was a product in the world, there was a belief in the mission of creating a better world of work, and in enabling companies to amplify the glimmers of greatness within their own culture rather than superimposing a one-size-fits-all solution from the outside in. 

To do this, we believed, and still do, that an organization needs to understand its people as deeply as it understands its numbers, and use that understanding to help people and the company perform together. This takes insights, and most of all dedicated action. In the age of AI and hybrid workforces, that imperative is more pressing than ever. It is why we are launching Enso, our domain-specific, always-on agentic AI system, to provide insights, coaching, and assistance to leaders facing into the gnarly challenges of AI transformation, increasing spans of control, and more complex collaboration patterns across the hybrid workforce of people and AI. Enso is named after our longstanding Culture Amp logo: an incomplete circle symbolizing progress and growth as a continuous process.

For fifteen years, Culture Amp has helped thousands of companies listen to their people and act on what they hear. Over that time, the pace of work has quickened, spans of control continue to widen, management layers are thinning, and work is moving in shorter cycles. Leaders are accountable for more people and more decisions with less direct line of sight into how their teams are doing.

What hasn’t changed is what people need to perform well: to collaborate, to communicate, and to connect. And to understand what their work contributes to, what deserves prioritizing, and why. These needs compound as more sophisticated work is done with AI and tasks are completed faster. 

AI has been focused on improving efficiency on ‘doing’: drafting or summarizing documents, writing code, or now even taking generic actions on a person’s behalf. But what’s missing are AI systems that focus on understanding people in the flow of work.

Why HR needs domain-specific AI

Understanding people at work used to be constrained to periodic processes owned by a few. AI is changing that, supporting strategic people planning and cyclical people processes with continuous processes closer to the work. Frontier models are valuable complements to Culture Amp, and, within the boundaries of your existing permissions, your people can already access Culture Amp insights inside their everyday AI tools. 

Frontier models and their agents are powerful generalists that many people now rely on personally and professionally. They also get more feature-filled every week. However, Gartner predicts that by 2027, more than half of the generative AI models enterprises use will be domain-specific, up from 1% in 2024. For HR technology, in addition to what frontier models have to offer, we believed it was important to ensure Enso can: 

• track the same measures over time even during continuous employee listening, and break them down by demographic group for targeted action

• ensure confidential raw data is not shared with or available to the company, to support genuine responses that in turn benefit the company

• be informed by Culture Amp’s proprietary, aggregated data to surface insights, with explainability about why they reasoned the way they did

• compare a team or company’s performance with other teams or companies, including companies or teams like yours by industry, region, size and beyond, to inform priorities and next steps 

• recommend informed, consistent actions and offer to take them on a leader’s behalf

• have domain-specific safety guardrails that gate out-of-scope conversations and actions, and keep key decisions with the human, such as giving a performance rating or judging readiness for promotion.

This is why we’ve built Enso. Enso is powered by 15 years of People Science research, drawing on aggregated insights from more than 1.6 billion data points, facilitating our proprietary Culture Culture Intelligence graph. This unique intellectual property provides a grounded map of the people factors at play under a given set of conditions for a company or team, enabling Enso and a leader to answer: “For a team like ours, in a situation like this, what insights matter and what actions should we take?” This map is what gives Culture Amp’s AI its domain specificity.

AI adoption is outpacing clarity on its benefits

The need for AI grounded in people science data shows up in our own benchmarks too. In our 2026 AI at Work benchmark, drawn from organizations likely to be ahead of the market on AI adoption, 85% of employees say their organization encourages experimentation with AI and 80% trust it to use AI responsibly, yet only 58% say leaders have clearly explained how AI will help the company reach its goals, and only 60% say their manager shares examples of how AI can support their work.

The productivity story is similar. 71% of employees say AI makes them feel more productive, rising to 93% of power users, yet workloads barely move: 72% of power users say their workload is reasonable, against 69% of non-users. The productivity arrived, but it hasn’t freed up time for innovation, development, strategic thinking, or investing in people. The glimmers of greatness are there; what’s missing is the clarity and the capacity to amplify them. Employees’ awareness of internal career opportunities also fell 10 percentage points in a year. 

For AI-forward companies, AI transformation is a people and workforce challenge. Success depends on individuals being enabled to change how they work with AI and each other, and believing they can succeed, together, with AI, and on the organization reshaping roles, teams, and ways of working as more of the work is shared with AI. Insights from our AI Effectiveness survey inform our Culture Intelligence graph, helping Enso tailor its support for AI transformation.

Giving leaders time back, with a clear view of what to do with it for their people and their performance, is what Enso is for. In the context of AI transformation, take a leader whose teams are three months into an AI rollout:

• The same measures, broken down: Enso runs a short check-in using consistent measures each round, and shows where teams are getting results from AI, where they believe they will, and where the two diverge.

• Confidentiality: responses are confidentially aggregated before the leader sees them, so people can answer candidly.

• Visibility up the line: themes from check-ins run by different leaders are combined, so senior leaders accountable for the rollout see how teams are experiencing it as it happens.

• Grounded, explainable insight: when one team’s confidence dips, Enso explains why that matters for a team like this one, drawing on the Culture Intelligence graph.

• Comparison: it shows how that team compares with similar teams, inside the company and beyond.

• Action, as trust is earned: Enso recommends a next step, such as a team conversation or a 1-1 agenda, and with the leader’s approval drafts or sets it up. The leader can dial that approval up or down over time.

• Guardrails and control: the company and the leader decide what context Enso can access, and decisions like a performance rating stay with the leader, though Enso can still coach on landing difficult feedback.

• Continuous improvement: Enso tracks whether its recommendations moved the measures, and refines its support for that company or user over time.

Enso listens, recommends, and acts for every leader, where they already communicate and work

Enso brings the basis of what Culture Amp has always enabled: insights, coaching, and assistance. But now, continuously with agentic support, to every leader, in the places they communicate, starting with Slack and expanding to other surfaces including Teams, and via AI tools like Claude and ChatGPT. 

Enso is also proactive. It uses the context the organization and the leader choose to give it, such as engagement survey and performance cycle results, HRIS data, company and people principles, priorities and goals, and increasingly the metrics your teams are measured on. When something shifts in a leader’s context, such as a dip in a team’s clarity, Enso can proactively reach out with what it noticed, why it matters and what the leader might do next.

I’m especially excited about how Enso can run agentic feedback and act on results, because of what the Culture Intelligence graph enables. This is Culture IntelligenceTM in full flight - including evidence-based observations, recommendations, and comparisons with the market, in the flow of work. Agentic feedback in Enso spans leader effectiveness (180s, 360s, and beyond) and interviews with individuals through to continuous employee listening with groups. 

Explainability is key to Enso, too. Responsible AI frameworks hold that AI systems must be able to explain their reasoning, which in practice usually means describing the steps that produced an output. Enso can go further: where applicable, it shows how a recommendation was shaped by the Culture Intelligence graph, so two teams with the same score can receive different advice suited to their conditions, with the reasoning laid out. That turns an explanation into coaching, in service of clearer, more confident and faster human decisions.

Agentic action, as trust is earned

Leaders with widening spans do not have hours to design a listening exercise, chase responses, synthesize findings and schedule follow-ups. Enso can do that work, with their approval, and take on more as trust is earned.

Our research suggests people trust the intent behind AI but are wary of AI acting for them. In our 2026 AI in HR study of 264 HR professionals, 37% of C-suite HR leaders and 16% of individual contributors said they were comfortable with agentic AI. That caution is healthy, and reflects the need for AI to earn trust before it acts on anyone’s behalf. It also bears on AI transformation: respondents who had let AI act within boundaries they set were seeing process transformation at two to three times the rate of their peers.

Insights captured in the flow of work arrive paired with Enso’s recommended actions. The leader decides whether to allow each one, and as confidence in Enso’s judgment grows they will be able to grant standing permission for certain actions: scheduling the conversation, drafting the feedback, following up on a commitment, then listening again to see whether the change landed. Autonomy is granted one permission at a time and can be withdrawn at any point.

2027: every leader will need an AI people partner 

Leaders heading into 2027 are responsible for more people, through more change, with less time to understand how any of it is landing. Our early results on Enso, which we’ll share more about soon, have us pretty excited about how it can help leaders at all levels, as an AI people partner, face into the people side of AI transformation. And, as foundation models improve, Enso is built to become even more useful.

When employees are heard and leaders have Enso’s support to understand and act, companies are better equipped to perform well at pace, even amid rapid change. The mission we signed up for in those earliest days of Culture Amp hasn’t changed much, but agentic AI, and specifically Enso, is set to become a force multiplier for it.

If your organization already runs on AI and you want to shape what comes next, click here to learn more about Enso.