Intercom

Most teams can tell you AI is saving them time. Fewer can clearly explain how it’s driving real business value. Why is that? The throughline from “The 2026 Customer Service Transformation Report” is that deployment depth makes a significant difference. Early on, ROI looks like faster response times and lower cost to serve. The wins are real, but they’re mostly about efficiency. As AI becomes more deeply integrated, something shifts: teams stop measuring time saved and start measuring where that time goes. That’s when ROI gets easier to articulate, because support moves beyond just operating more efficiently and starts actively contributing to growth. This week’s piece looks at how going deeper with AI amplifies results, and why that makes its impact much easier to explain. 👇

Good help content is essential for strong AI Agent performance, but sometimes it takes more (like access to external data or permission to take action) to resolve a customer conversation. For busy support leaders, knowing where to start on set-up, how to define the data or actions, or the overwhelming thought of an API is enough reason to add it to a backlog, leaving valuable gains on the table. This is where Fin’s Data and Action Suggestions become extremely powerful. Highlighting the most prominent data and action gaps to address, showing you the exact queries that could be automated (all based on real customer conversations), and then providing sample API docs to make implementation fast and easy. Christine walks through how it works and what it unlocks below.

AI is now widely adopted in customer support, but for many teams, it's still limited to simple use cases. When AI is deeply integrated, across your channels, workflows, and business systems, it moves beyond simple automation and starts handling complex work: the kinds of interactions that teams used to only entrust to humans. On February 25, we’re announcing updates to Procedures and Simulations, Intercom’s approach to building and scaling AI automation that handles complex queries. In this live product announcement, you’ll see how Fin handles multi-step customer conversations, lets teams build automations in natural language, connects directly to tools and data, and stays under control through clear rules and logic. Paul Adams, Chief Product Officer, will be joined by the product teams behind Procedures & Simulations, and sales engineers working with the customers pushing AI beyond basic automation. Click ‘Attend’ to be reminded!

Implementing AI isn’t the same as AI paying off. Yes, most support teams using AI are seeing early gains. 62% say their customer service metrics have improved since implementing AI, according to our latest research. But when AI is deeply integrated into customer service operations, the results improve even more. Teams that have reached a mature level of deployment report improved metrics at a higher rate and they’re far more likely to say they can 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 measure the return on their investment. That’s the key to unlocking ROI. Clearer ROI creates buy-in and helps teams move beyond efficiency gains alone. Teams with mature AI deployment win back more time, and they're more likely to use freed up capacity to support revenue-generating activities that ultimately benefit their business. Read more in our new 2026 Customer Service Transformation Report. Download now → link in the comments.

With any AI Agent for customer service, two things are extremely important: effectiveness and quality. CX Score is a clear marker of quality, but now we've introduced a new metric to better measure effectiveness: Automation Rate. Brian explains why your Automation Rate is now the North Star metric your CEO should care about.

As we head into 2026, it’s clear AI adoption has accelerated in customer service. But we’re also learning that not all AI usage is equal. In The 2026 Customer Service Transformation Report, we found that teams that have reached a “mature” level of deployment (where AI is fully integrated into operations and working at scale) are seeing improvements in support quality at 𝗻𝗲𝗮𝗿𝗹𝘆 𝗱𝗼𝘂𝗯𝗹𝗲 the rate of those still in the initial deployment stage. In other words, launching AI is easy, but transforming with it is not. So, how do you truly transform with AI? Over the next five weeks, we’ll dig into the key findings from the report to identify what leading teams are doing differently and show you how to make the most of the opportunity that’s on the table. Week 1 is live.  If you want understand how support teams are driving quality improvements by pushing AI to handle more complex work, this is where you start 👇

Some questions are just easier to answer visually. Fin can now send screenshots and GIFs from your existing support content, giving customers step-by-step visual guidance exactly when they need it. This works automatically across channels, with no setup required. Pedro shows how it works in practice, and why it’s such a powerful upgrade for customer clarity.

Support at Peddle sits at the center of a complex, multi-sided operation. Their online marketplace for selling end-of-life and near end-of-life vehicles supports sellers, carriers, and buyers; all under one umbrella, across four distinct divisions. As chat volume climbed into the tens of thousands each month, something had to change. Team leads, supervisors, and managers were increasingly pulled into frontline support, leaving less time for the work that drives company KPIs. In this video, Jaymee Krauchick, Assistant General Manager at Peddle, shares how her team turned to Fin, Intercom’s AI Agent, to absorb growing volume and give time back to the people focused on training, quality, and improvement. Since adopting Fin, Peddle has: → Seen resolution rates of about 70 percent across support workspaces → Automated high-volume queries like vehicle damage, offer changes, and pickup scheduling → Reduced operational pressure on team leads and managers → Created space to focus on enablement and CX improvement For Peddle, AI is helping them “repurpose the people we have into more unique newer roles that really help them grow and expand their own knowledge within the world of CX.” As Jaymee puts it, Fin’s reach goes far beyond what they’re using today, and the next phase of their CX transformation is just getting started.

The Countdown to Dublin is on! Transformation is more than just a theme for Intercom GSKO FY27; it’s our roadmap for the year ahead. Next week, our field teams and partners are headed to Dublin to align on the future of AI-first customer service. We are incredibly grateful to the sponsors who are making this year's kickoff possible. A huge thank you to Amazon Web Services (AWS), LeanConvert, DKM Ecosystem, Solidroad, Intuitive CX, Fullstory, evaluagent®, saasgenie, SendSafely, Faye, The SaaSy People, and Escalate Ops for your partnership and support. We can't wait to see this community come together in Ireland to kick off our most ambitious year yet. See you in Dublin!

Fin Suggestions lets you get hours of work done in minutes. It analyzes all your customer conversations, then suggests the exact actions to take to improve Fin's performance. This includes pre-populated, inline edits to your articles which you can accept in a single click. Christine walks through how they work (and how fast teams can act on them).