How a global leadership development company implemented human-AI collaboration to serve 3 million customers across 21 languages, and turned support into a revenue driver.
The learnings in this blog post are based on a discussion from Atlassian’s Team ’26 conference. You can check other sessions like this on demand.
Leadership Circle is a global leadership development company whose mission is to evolve the conscious practice of leadership through data-driven 360-degree assessments, coaching, and consulting. With 3 million customers and partners across 21 languages, and a network of over 12,000 certified practitioners worldwide, they needed customer support that could match the scale and quality of their work.
In looking to modernize their support practice, they turned to the Customer Service Management app, Atlassian’s AI-first, purpose-built offering for external customer support.
Before CSM, our help content was buried on our website, our cases lived in NetSuite, and nothing was connected. Now, with Atlassian CSM, we have one unified experience — self-service, AI, knowledge base, and ticketing — all in one place, making it easier for our team to quickly find information and trust that it’s current and approved, across 21 languages.”
–Miranda Dunn, Director of Global Transformation and Change, Leadership Circle
After implementing Atlassian’s Customer Service Management (CSM) app, Leadership Circle achieved a 71% AI resolution rate, a 65% reduction in manually handled tickets, and a support function that now actively drives revenue while delivering the best possible customer experience.
Here’s what we learned as we worked with Leadership Circle as an early adopter of the Customer Service Management app:
1. Measure resolution, not containment
The customer service industry has a metrics problem. As AI tools proliferate, many organizations have become laser-focused on AI containment rates, which is the percentage of interactions handled without a human. AI containment rates are a great way to measure from an economic perspective. However, it only tells you the AI agent handled the interaction, not whether customers got the help they needed.
Not emphasizing the customer experience and focusing only on containment can impact your retention, revenue, word-of-mouth growth, and competitive differentiation. In fact, according to a G2 study, 7 out of 10 customers have stopped doing business with a brand due to poor customer service.
That’s why the focus should be on AI resolution rate, which is a more effective measure of whether customers are getting the help they need.
From day one, Leadership Circle made sure to never lose importance on the customer experience. By ensuring that customers were actually getting their problems solved, not tickets closed or interactions deflected, they were able to resolve 71% of all incoming requests and allowed their customer success team to transform their ways of working.
The Takeaway:
Before you celebrate your AI metrics, ask yourself: Are you measuring whether the AI agent handled it, or whether the customer got the help they needed?
2. Free your people to do what only people can do
Here’s the part most “AI in customer service” stories get wrong: they end at efficiency. Fewer tickets, lower costs, done.
Leadership Circle saw the efficiency gains, a 65% reduction in manually handled tickets, and asked a different question: what should our people do now?
The answer wasn’t “less.” It was “different.” With routine volume handled by AI, their customer success team stepped into an entirely new role:
- High-value coaching relationships with practitioners and clients
- Upsell and expansion opportunities that directly drive revenue
- Proactive, consultative interactions that deepen partnerships
This isn’t a story about replacing humans. It’s a story about unleashing them with a stronger tool set to amplify their impact. When your team isn’t buried under routine requests, they can do the work that builds loyalty, grows accounts, and differentiates your brand.
CSM is changing the conversation about what support means for us. Prior to this, our team constantly juggled the ‘cost center routine’ with building client connections, as ‘building relationships’ is one of our core values.
By automating the routine with CSM, we’re freeing our people to focus on those relationships, upsell opportunities, and the interactions that actually drive revenue in repeatable fashion.”
–Amy Felix-Reese, Managing Director, North America, Leadership Circle
The Takeaway:
AI changes what kind of work your team does. Plan for that shift, and focus on growing your business.
3. Expand what your team can do
With Atlassian’s CSM app, they now support 3 million customers and partners across 21 languages from a single platform. The AI agent handles inquiries in the customer’s language, 24/7, across web, email, and chat channels. When something requires human judgment, it escalates with full context: no repetition, no cold transfers, no starting over.
The aha moment
Miranda Dunn, Director of Global Transformation and Change, found a strong example while exploring the platform: about 700 support tickets per month were solely related to login issues. She asked Rovo to assess their existing help article against those tickets.
“It told me the article would only solve 25% of the tickets,” she says. “So I asked it to generate one that would cover more.” Rovo scraped every agent response since launch and produced a comprehensive help article, saving an estimated 1,200 team hours per year. “I didn’t need to be an IT expert,” Dunn adds. “Having it all in one spot — I can find insights on my own, look at trends, and escalate issues without needing others to do it for me.”
From reactive ticket-answering to deep customer connections
“We want to build deep connections with our customers,” Miranda explains. Before CSM, the team reacted to tickets one by one, often after customers grew frustrated. Now, with AI handling routine inquiries, “we can pivot on what’s possible.” The team focuses on coaching, upselling, and proactive relationship building, the work that grows the business.
The Takeaway
AI‑first omnichannel support helps customers get the help they need – when they need it, where they are, and in a way that fits them (including in their own language).
4. You can’t “set and forget” AI
We acknowledge that every organization has a different level of AI readiness and a different level of desire to adopt. It’s important for teams to explore what is best for them.
For teams looking to implement AI, one of the most important concepts is that it’s not set-and-forget once it’s deployed. You have to continuously provide guidance and manage the experience so the AI agent never stops improving, and you are always delivering a great customer experience.
With the Customer Service Management app, after deployment, Leadership Circle could:
- Review every AI conversation to understand how the agent is behaving and where it’s falling short
- Coach the AI directly by providing guidance on better responses for specific scenarios
- Create and test new versions against curated “golden data sets” of real tickets and recommended answers, measuring whether each iteration improves resolution quality
- Identify and close knowledge gaps that monitor interactions and proactively suggest new or updated knowledge base articles
When the AI can’t solve something and a human steps in, that resolution becomes training data. The AI gets smarter, the knowledge base gets richer, and the next customer with the same question gets the right answer, so you make sure you compound and build on the enhancements you establish.
The Takeaway
The best AI deployments aren’t the ones with the fanciest models; they’re the ones with the tightest feedback loops. Build the habit of reviewing, coaching, and versioning your AI from day one.
5. Connect support to the rest of the business
Historically, customer service has always been disconnected from the teams building and running your products. As you might suspect, Leadership Circle was experiencing the same and was looking to better connect its teams.
By moving customer service to the Customer Service Management app, Leadership Circle tapped into Atlassian’s Teamwork Graph. Now, support, engineering, and product share the same customer context, so teams stay aligned for launches and can act faster on customer‑impacting issues.
In practice, this means support agents see the full picture (not just the current ticket, but the customer’s history, entitlements, and open requests across every channel). And when a fix requires development’s help, issues can be sent directly to the team in Jira. Then, product teams “hear” the customer because support interactions feed insights that shape roadmaps, clarify real pain points, and surface high‑value requests.
Optimized support through stronger collaboration
Consolidating work on one platform has changed how Dunn connects with the business. When a new product launches, she’s confidently closely connected to the teams driving it, ensuring customer success is involved early and has the right materials ready for customers from day one. She can see marketing campaigns, track IT issues that need escalation, and spot trends across the business.
And because everything lives in one place, she can do more of that lifting herself rather than waiting on others, making cross-team conversations less about dependency and more about collaboration.
The Takeaway
When support is connected to engineering, product, and success teams, every customer interaction makes the whole organization smarter.
The bottom line
Leadership Circle’s transformation isn’t just a feel-good customer story. It’s a blueprint.
They started with a clear philosophy: AI plus people, not AI versus humans. They focused on the customer experience, metrics that measure it rather than cost efficiency, and spent time deeply integrating and managing AI to enhance how they work. And they connected support to the rest of the business, so every team benefits.
The results: 71% of resolutions via AI, 65% fewer manual tickets, and a support function that now drives revenue. Their team went from fearing AI would take their jobs to discovering what’s possible when routine work is handled, and they found deeper customer relationships, proactive coaching conversations, and insights they can surface on their own without waiting on other teams.
As Miranda Dunn puts it, “It’s not about a bot answering the questions. It’s about leading people on a journey and helping them come to a solution. It’s a beautiful balance of AI and people.”
If you’re evaluating how AI fits into your customer service strategy, Leadership Circle’s journey offers a clear message: success will come from AI and humans working together.
Leadership Circle implemented Atlassian’s Customer Service Management (CSM) app, available across all Service Collection editions.
