Top 5 Customer Service Trends to Watch in 2026

As customer service technology advances, the state of customer service changes along with it. Customers expect companies to adapt to their needs, and technologies like AI agents are playing a major role in meeting those evolving expectations. Here are five customer service trends to keep on your radar as you prepare for the future of customer service, based on data from the State of Service report.

Customer service is undergoing a transformation through AI agents, capturing significant attention from the business world. Seventy-nine percent of service leaders view AI agent investment as critical for addressing today's business challenges.

Organizations anticipate that AI agents will reduce both service expenses and case resolution times by approximately 20%, while simultaneously boosting customer satisfaction scores – creating multiple wins across the board. The benefits extend to service professionals themselves, with 83% experiencing enhanced career opportunities and 82% acquiring fresh skillsets. Through AI integration, customer service representatives are empowered to perform at their peak potential.

Self-service today should help customers resolve simple issues on their own with speed and precision.

Though our research finds that 61% of service professionals say their organization already addresses service issues proactively, only 33% of customers agree that the typical company actually does this. The best platforms reshape self-service from a reactive, time-consuming experience into one that’s not just low-effort, but drastically increases resolution rates. Take Service Cloud’s fully integrated agentic self-service experience – with it, businesses can combine the power of Agentforce with real-time insights across your Customer 360 applications to deliver smarter, faster, more personalized self-service at any time, on any channel.

That’s the future of self-service: shifting customers from reactive problem-solving to proactive value creation on their own.

Many organizations keep data in different silos or applications, so it’s difficult to get a complete view of the customer across all channels.

Bringing customer data together is all about creating an end-to-end view of the entire customer journey. This way, you’ll have a continuous feedback loop between sales, service, and marketing, keeping everyone on the same page. Maybe that’s why 88% of service leaders are prioritizing tech integration to bring data together, eliminate silos, and unlock the full potential of AI.

As companies try to stay one step ahead of these and other customer service trends, leading organizations are adopting programs that prevent large language models (LLMs) from retaining sensitive customer data. More organizations are training their own domain-specific models to access a secure AI cloud while storing data on their own infrastructure. These efforts are essential to preserving customers’ loyalty and trust in the years to come.

When it comes to meeting customers’ sky-high expectations, proactive service is more important than ever. “It’s essential to proactively resolve issues before they have any significant business impact,” says Jules O’Donnell, Salesforce administration manager at Quickbase. “This means keeping up with technology solutions to scale service and meet customers where they are.”

Conversational AI is one of the innovations that makes these benefits possible. Agentforce's AI agents, for example, operate 24/7 across self-service portals and messaging channels and preserve conversation history and context so customers can get the help they need, wherever and whenever they need it. With 89% of service professionals saying that conversational AI increases self-service resolution rates and 88% saying it accelerates resolution times, it’s clear this tech is here to stay.

Our research shows that mobile workers say innovative field service technologies make them feel safer and more effective at their jobs, empowering them to be better brand ambassadors. These technologies include intelligent scheduling, route optimization, AI-generated reports, and augmented reality (which can create detailed 3D rendering of large areas in seconds).

One of the emerging benefits of these and other technologies is the ability to generate insights and predict job duration. For example, workers can use AI to easily view asset conditions as well as maintenance and repair history, then schedule proactive service to minimize downtime. Eight-eight percent of field service leaders already report moderate or significant improvements with the help of AI.

Customers are benefiting, too. They can book and reschedule their own appointments using intelligent appointment assistance. And many customers have the ability to check when a technician is on the way, reducing no-shows and call volume for a better customer experience all around.

At its core, AI and automation are enabling companies to handle a higher volume of inquiries with greater speed and accuracy. AI agents can instantly address common questions, guide customers through processes, and resolve issues around the clock, significantly reducing wait times and improving immediate satisfaction.

Beyond mere efficiency, AI is also empowering a new level of personalization. By analyzing vast amounts of customer data — from purchase history to past interactions — AI algorithms can predict customer needs, recommend relevant products or services, and tailor communication to individual preferences. This proactive and personalized approach helps build stronger customer relationships and fosters loyalty. 

AI tools aren’t just for customer-facing interactions; they also serve as powerful aids for human service reps. AI-powered systems can provide agents with real-time information, suggest optimal responses, and automate repetitive tasks, allowing human teams to focus their expertise on more complex, empathetic, or high-value customer issues that truly require a human touch.

Adapting to the dynamic shifts in customer service requires a strategic and forward-thinking approach. One of the most crucial best practices is to embrace a hybrid model that seamlessly integrates AI and automation with human expertise. Rather than viewing AI as a replacement for human representatives, successful organizations use it to augment their teams, handling routine queries and data analysis while freeing up human reps to tackle intricate problems, build rapport, and deliver empathetic support. This balance ensures both efficiency and a high-quality customer experience.

Another key practice is continuous investment in rep training and upskilling. As AI takes over more transactional tasks, human reps need to evolve into problem-solvers, strategists, and relationship builders. Training should focus on developing soft skills, advanced problem-solving techniques, and proficiency in utilizing AI tools to their full potential. Trailhead is an example of a platform that offers plenty of courses for service professionals.

Finally, organizations need to take a data-driven approach to service. Businesses should actively collect and analyze customer interaction data, feedback, and AI performance metrics to identify pain points, optimize processes, and continuously refine their service strategies. The best way to do this is to invest in software that incorporates humans, AI agents, and data into one unified platform – like Agentforce Service.

By staying agile, prioritizing customer experience, and fostering a culture of continuous improvement, companies can not only adapt to changing trends but also set new benchmarks in customer satisfaction.