{"id":31778,"date":"2026-02-05T18:19:26","date_gmt":"2026-02-05T18:19:26","guid":{"rendered":"https:\/\/www.intercom.com\/blog\/?p=31778"},"modified":"2026-03-20T13:50:34","modified_gmt":"2026-03-20T13:50:34","slug":"why-ai-deployment-depth-makes-the-difference","status":"publish","type":"post","link":"https:\/\/www.intercom.com\/blog\/why-ai-deployment-depth-makes-the-difference\/","title":{"rendered":"Transformation in action: Why AI deployment depth makes the difference"},"content":{"rendered":"

It\u2019s clear that AI adoption is widespread. More and more businesses are using and investing in the technology.<\/p>\n

However, in our latest Customer Service Transformation Report<\/em><\/a>, it emerged that this usage is not equal. There\u2019s a deployment gap opening up between teams that are just scratching the surface with AI and those that are going deep with it. In other words, it\u2019s becoming clear that launching AI is easy, but transforming with it is not.<\/p>\n

So, how do you transform with AI? Over the next five weeks, we\u2019ll dig into the key findings from the report to identify what leading teams are doing differently. We\u2019ll show you how to make the most of the opportunity that\u2019s on the table and close the gap before it gets too wide.<\/p>\n

\n

This is part one of our five-part deep dive into our new research: \u201cThe 2026 Customer Service Transformation Report.\u201d We\u2019ll be sharing all five editions on our blog and on LinkedIn<\/a>.<\/h4>\n

If you\u2019d like to get straight to the report, download it\u00a0here<\/a>.<\/h4>\n<\/blockquote>\n

AI adoption is the norm, depth makes the difference<\/h2>\n

We surveyed 2,470 global support professionals across a range of industries to understand how teams are currently using AI for customer service, their challenges and pain points, and the opportunities they\u2019re going after in 2026.<\/p>\n

Overall, we found that organizations have recognized the value of investing in AI for customer service. Eighty-two percent of senior leaders say their teams invested in AI in the past year and 87% say they plan to invest in 2026.<\/p>\n

These initial investments are paying off. Over three-quarters of CS teams (77%) say AI is meeting or exceeding their expectations, delivering faster response and resolution times, always-on coverage, cost savings, increased capacity, and the ability to serve more customers around the globe with multilingual support.<\/p>\n

<\/p>\n

However, only 10% of organizations say they have reached a \u201cmature\u201d level of deployment, where AI is fully integrated into operations and working at scale.<\/p>\n

<\/p>\n

That tells us that most teams are only scratching the surface of what’s possible and are leaving significant improvement opportunities on the table.<\/p>\n

The maturity difference shows up in the results<\/h2>\n

Teams that have reached mature deployment report a more sophisticated use of the technology. They\u2019ve put AI at the core of their service operation, integrating it into critical workflows, giving it more responsibility, and continuously improving it.<\/p>\n

Beyond automating the bulk of their manual work, they\u2019re using AI to proactively engage with their customers and perform tasks on their behalf.<\/p>\n

<\/p>\n

This gap between basic adoption and deep integration helps explain the variance in outcomes. Of the teams that have reached mature deployment, 43% report higher quality and consistency across support \u2013 nearly double the rate of those still in the initial deployment stage.<\/p>\n

High-quality support is essential for transforming support from a cost center to a value driver. Great experiences don’t just get customers to stay, they encourage them to advocate. Great support becomes a reason to choose you and that\u2019s what teams with mature deployment are building towards.<\/p>\n

The more you trust your AI Agent with meaningful work, the more it creates the conditions for higher-quality, more consistent support.<\/p>\n

What mature deployment looks like in practice<\/h2>\n

One of my favorite examples of a team that\u2019s seen results from committing to going deep with AI is Lightspeed<\/a>.<\/p>\n

They\u2019re a big organization with a complex product, operating across multiple regions and languages. When they adopted Fin in early 2023, they were handling tens of thousands of monthly support requests and they needed a solution that could scale with that complexity.<\/p>\n

What stands out to me about their approach is how deliberately they handled the change management piece. They leveraged the Intercom Academy for foundational training, but also developed in-house training modules specifically tailored to their own processes and provided ongoing support for team members following launch.<\/p>\n

Critically, they also worked closely with their leadership team to ensure everyone was aligned on the goals and benefits of implementing AI. In a large, geographically dispersed team like theirs, that coordinated effort fostered a sense of ownership across the organization.<\/p>\n

Their VP of Information Systems, Yamine Gluchow, summed it up well: \u201cIt’s not magic. If you invest in understanding, adoption, and great content, AI performance takes off.\u201d<\/p>\n

With this foundation in place, Lightspeed has gone on to achieve:<\/p>\n