10 Game-Changing Ways AI is Transforming Customer Service in 2025

AI adoption has–unsurprisingly–skyrocketed over the last year.

Customer service leaders are discovering that AI isn't really about automation or increasing efficiency. It's about fundamentally reimagining how support teams operate, engage with customers, and drive business value.

Where AI accounted for just 1% of the customer service market in 2023, it’s becoming more and more foundational for many CX teams. 70% of CX leaders say generative AI led their organizations to re-evaluate their customer experiences.

But the real story isn't in the adoption numbers–it's in how AI is impacting every aspect of customer support.

10 transformations of AI in customer service

Some of these transformations are already well underway. 

Many support teams are already using AI to route tickets more intelligently and monitor conversation quality in real time.  But others, like photorealistic AI avatars for video support, are just beginning to emerge.

Here are ten ways AI is reshaping customer service as we move into 2025.

1. Enabling end-to-end resolution of customer interactions

The biggest difference between generative AI and the old, rule-based chatbot model that existed before is that generative AI enables the end-to-end resolution of customer interactions. 

It used to be the case that this type of self-service would enable a handful of very fast resolutions for some basic cases. AI can do that–while still delivering a holistic and memorable customer experience. 

Good AI implementations go far beyond making teams more efficient (which is a huge plus!), they also help teams build long-term customer loyalty. 

What does that look like in practice?

AI can walk customers through multi-step troubleshooting processes, process subscription changes while explaining terms and conditions, or even handle sensitive billing disputes by accessing payment systems. Because it can ask clarifying questions and verify information across multiple systems, it’s capable of a lot more than a linear conversation. 

A direct example is Coterie. They’re able to use Siena for end-to-end subscription management while providing outstanding, white-glove service to their customers. 

2. Personalizing every interaction

Current AI models have advanced massively in reasoning and empathy. 

By integrating deeply with CRM data, AI can now understand not just what a customer is asking, but their entire history, preferences, and context. That enables them to have much more tailored and emotionally intelligent customer interactions than before. 

83% of employees say AI’s capacity for decision-making is a major highlight of adoption. AI can adapt its tone and approach to every customer. It can show empathy during difficult interactions, maintain professionalism with formal customers, or match casual language when appropriate.

3. Elevating the role of human support

Low-complexity tasks like tracking order status or resetting passwords used to constitute significant volume sources for CS teams–mainly because these queries impact everyone. 

AI has started handling more and more of these routine tasks, so the role of human agents is also changing.

Human support has evolved from processing transactions to strategic problem-solving. Agents tackle complex issues that require nuanced judgment. This shift brings opportunities for career growth and skill development while reducing the burnout often associated with repetitive tasks.

At Groomie, for instance, support reps now proactively engage with customers about feedback and upcoming sales, driving both acquisition and retention, rather than simply reacting to tickets.

4. Augmenting and enhancing customer service skills

Another growing use of AI tools is actively enhancing human agents' capabilities through real-time assistance.

AI copilots now provide smart suggestions during customer interactions, automatically surface relevant knowledge base articles, and even help optimize response tone and language. For complex issues, AI can quickly summarize previous interactions and related tickets, giving agents context.

These tools make every agent multilingual and expertly versed in the product. The result is more confident agents who can focus on building customer relationships rather than juggling multiple systems.

Siena offers a copilot tool that drastically reduces the time it takes to draft well-written, empathetic responses to customers. 

5. Offering real-time quality assurance

QA programs are typically based on the manual review of a small sample of tickets. There’s value to that–AI can’t totally replace in-depth, direct feedback provided by a colleague or team lead. 

But AI can help you monitor 100% of all interactions. It can identify cases that would benefit from a manual review, while providing instant feedback and suggestions.

80% of employees surveyed by Zendesk reported that AI has already improved the quality of their work. This is the type of implementation that could have a meaningful impact on agent development in the long-term–while improving every customer interaction too. 

6. Providing advanced insights and analytics

CS teams used to invest a ton of time and energy in training dedicated models to automatically analyze unstructured data, in a process that would take months and consistent fine-tuning at an incredibly high price point. 

Pulling insights from customer interactions was only accessible to enterprise-level companies, handling massive volumes of data. 

While AI models can’t replace this effort completely, they’ve definitely made it more accessible to more companies. AI-powered tools like Idiomatic and EdgeTier help support teams instantly spot emerging issues and transfer customer support data into actionable insights. This is becoming increasingly essential for CX teams looking to level up their customer experience. 

7. Routing tickets intelligently

Because intent recognition and categorization have improved so much with current AI models, CS teams can also route tickets much more intelligently than before. 

Say you want to identify and combine multiple factors, like agent expertise, current workload, customer sentiment, and account value. Where it used to be normal to set up multiple views for each category and agents would often have to manually move tickets from one view to the next, AI-powered ticketing tools like SentiSum can automate this with a higher degree of accuracy.

You can also do something similar with Siena by using the collaborative routing feature and/or adding ticket tags when an automation is triggered, by setting up routing rules for these in your help desk. 

8. Generating revenue via proactive recommendations

The previous changes are all indicative of a general trend across customer support. 

Customer service is about much more than solving the initial query. Every support interaction will become (if it isn’t already) an opportunity to generate revenue. AI can spot natural moments to recommend relevant upgrades or complementary services–by analyzing conversation context, purchase history, and usage patterns. 

The result will be that support touchpoints are potential sales opportunities–without being pushy or transactional. 

For example, Hospitable’s short-term rental software can automatically suggest extended stays, premium amenities, or future booking opportunities. 

9. Predicting opportunities and risks in advance

Another implementation of AI tools are predictive analytics. These aren’t as widespread yet as they will become over the course of 2025 but the technology is already there. 

AI can detect potential issues before they impact customers. Here are some practical examples of what that looks like: 

• Workforce management software can use AI to predict seasonal demand spikes, so teams to prepare resources in advance.
• SaaS products can use AI to identify when users skip key feature adoption steps, detect declining engagement patterns that are typical of churning customers, or recognize anomalies that indicate common technical issues.
• In ecommerce, AI can analyze browsing behavior to prevent potential returns. For instance, if a customer repeatedly views sizing guides, AI can trigger proactive size recommendations or fitting assistance before the purchase—reducing both returns and support volume. 

Some tools that are already offering features like this include Clerk, which provides personalized product recommendations, and Syte, with its visual discovery suite, which makes it easier for customers to find products they like. 

As CX teams invest less time on frontline support answering routine questions, they’ll start focusing on these areas. 

10. Interfacing with customers via phone and video

We’re still in the early stages of AI-generated speech and video. Most of the current options still sound a little uncanny but–like text–it’s highly likely that AI will start catching up with these other mediums as well.

We expect to start seeing AI able to handle fluid phone conversations that feel natural, complete with appropriate pauses, emotional responses, and contextual understanding. This can totally transform how CX teams approach phone support, which has been one of the most expensive channels to have and is often difficult to manage at scale.

The next frontier will be visual AI support. AI models are just starting to interact with computers directly and early implementations of digital avatars are starting to emerge. It’s hard to predict exactly how long it will take for the technology to mature enough to be usable but the future will likely include photorealistic AI agents handling video support calls, 

The shift from text to voice to visual interaction will make complex problem-solving more intuitive while maintaining the scalability benefits of AI support.

Future-proof your customer service

These transformations are already starting to reshape customer service but they’re just the beginning.

AI technology is still very young and developing rapidly. As it continues to evolve, we’ll see deeper integration between human expertise and artificial intelligence. 

The result will be customer experiences that we can hardly imagine today. 

The companies that thrive will be those that embrace these changes–while continuing to keep human connection at the center of their strategy. 

At Siena, we’re focused on building exactly that future. If you want to implement an AI agent thoughtfully and effectively, book a free session with us today! 

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