{"id":31636,"date":"2025-11-18T19:00:01","date_gmt":"2025-11-18T19:00:01","guid":{"rendered":"https:\/\/www.intercom.com\/blog\/?p=31636"},"modified":"2025-11-27T17:36:25","modified_gmt":"2025-11-27T17:36:25","slug":"planning-your-2026-customer-service-organization","status":"publish","type":"post","link":"https:\/\/www.intercom.com\/blog\/planning-your-2026-customer-service-organization\/","title":{"rendered":"2026 customer service planning series: Vol. 01"},"content":{"rendered":"

Like many support leaders right now, I\u2019m deep in 2026 planning.<\/span><\/p>\n

I imagine this cycle is bringing a big question into focus for most: if the way work gets done has fundamentally changed, what does that mean for the shape of my support organization?<\/span><\/p>\n

In 2026, you won\u2019t get the full value of AI by keeping your org chart, systems, and operating model the same. You need to think differently about how support is structured, how performance is owned, and how your systems evolve around an AI-first model.\u00a0<\/span><\/p>\n

To help you do that, we\u2019ve designed a \u201c2026 customer service planning series.\u201d Over the next five weeks, we\u2019ll cover the roles, skills, organizational design, and operating model you\u2019ll need to be successful next year.<\/span><\/p>\n

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This is part one of our five-part series on customer service planning for 2026. We’ll be sharing all five editions on our blog and on LinkedIn.<\/h4>\n

If you’d rather have them emailed to you directly as they’re published, drop your details here<\/a>.<\/h4>\n<\/blockquote>\n

But before you can make any of those decisions, you need the right mindset and the right internal conditions for change. That\u2019s where we\u2019ll start this week.<\/span><\/p>\n

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Week 1: Start with a mindset shift<\/strong><\/h2>\n

If you were building support from scratch today, you\u2019d design around AI from day one. That\u2019s the mindset you need to adopt heading into 2026.<\/span><\/p>\n

But many teams treat AI like a feature instead of infrastructure. They tack it onto existing processes and tools, limit its scope to tier-one issues, and fail to evolve the organization and systems around it.<\/span><\/p>\n

Those teams are thinking too small. They chase incremental efficiency gains, underinvest in the system change needed to make AI successful, and get stuck. It results in the customer experience staying fragmented, the team staying reactive, and the business leaving value on the table.<\/span><\/p>\n

AI Agents are fully capable, end-to-end resolution engines. They fundamentally change the architecture of support.<\/span><\/p>\n

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Quote from Grant Lee, CEO of Gamma: “If you want to unlock the real value of AI, you have to design for it, not retrofit around it. That\u2019s how a small team like ours was able to achieve such high resolution rates. Our AI Agent [Fin] resolves over 80% of our inbound volume, and we\u2019ve been able to scale massively without adding headcount.”<\/p><\/div>To plan effectively and get the most value out of the technology, you need to adjust your mental model. Here are the mindset changes that matter most.<\/span><\/p>\n

1. Move from ‘AI as a tool’ to ‘AI as infrastructure’<\/h3>\n

For the past decade, support systems have been the intermediary between customers and human support agents. AI isn\u2019t an intermediary, it\u2019s the first touchpoint (and often the last), the primary resolver, it manages workflows, orchestrates handoffs, and takes real actions.\u00a0<\/span><\/p>\n

Planning with the \u201cAI is a tool\u201d mindset will lead to small optimizations around the edges that don\u2019t move the needle. Planning with the \u201cAI is infrastructure\u201d mindset, on the other hand, will help you redesign your organization around where value is actually created.\u00a0<\/span><\/p>\n

The teams that thrive in 2026 will be the ones who design around:<\/span><\/p>\n