You're only seeing 20% of the report.
You're only seeing 20% of the report.
Connecting Service Professionals with AI
Customer service is entering a new era. Our last State of Service documented a rise in customer demands. Today, artificial intelligence (AI) is boosting productivity, speeding up resolutions, and providing more support to service teams - while also cutting costs. The AI revolution promised to transform customer service. It delivered.
We surveyed 6,500 service professionals to understand what's working now that the technology has moved from pilot programs to daily operations. As AI adoption matures across the industry, all eyes are now turning to AI agents - autonomous systems that can take action alongside human teams, not just provide information. Our findings show that most service leaders (79%) believe investing in AI agents is fundamental to meeting current business demands.
The companies pulling ahead aren't just using AI agents. They're building real collaboration between humans and AI agents across all their digital channels, with a unifying data strategy that makes these partnerships actually work at scale. This report digs into both their successes and struggles, revealing how companies and service professionals navigate this new landscape through human-AI collaboration.
The perspectives shared by today's service leaders - the ones pairing humans with AI in their daily operations - will illuminate the path forward. Our hope is that this research will be a trusted companion as you chart the future of customer service - a future in which humans and AI agents work together to create unprecedented success.
Kishan Chetan
EVP & GM
Salesforce Service Cloud
For the seventh edition of the State of Service report, Salesforce surveyed 6,500 service professionals to learn how:
Data in this report is from a double-anonymous survey conducted from April 25, 2025, through June 6, 2025. Respondents represent 40 countries across five continents. All respondents are third-party panelists. For further sample details, see page 37.
Salesforce Research provides data-driven insights to help businesses transform how they drive customer success.
6,500 customer service professionals surveyed worldwide
Frontline employees who support customers from the employee's home, store, or office.
Frontline employees who provide support in the field, at the customer's home or business - in-person or virtually.
Service professionals who oversee operations and equip internal teams with tools, systems, and processes.
Service vice presidents, directors, and team leaders who oversee both field service technicians and service representatives.
All survey respondents, inclusive of all groups above.
Service Challenges and Hiring Tactics
AI empowers teams to deliver faster and more accurate interactions. From providing proactive customer recommendations to helping service leaders with real-time insights, AI is transforming the nature of service work.
The result? Improved decision-making, increased efficiency, and happier customers. And companies that use AI agents specifically anticipate better results across their KPIs, from customer satisfaction scores to case deflection.
Service ops and leaders who use AI agents expect their service costs and case resolution times to decrease by an average of 20%.
Bar chart showing service organizations' current and expected use of Agentic AI, Predictive AI, and Generative AI.
The collaboration between humans and AI in customer service yields significant benefits. In fact, 83% of service representatives at organizations with AI say they have better career prospects because of it, and 82% say working with AI has helped them develop new skills. It's also made them more productive and their jobs less stressful.
And at organizations with AI agents, service representatives can take on the more complicated cases. With human service representatives and AI working together, more can be accomplished - including meeting customers' needs, both simple and complex.
By boosting self-service offerings with AI, organizations can also save valuable resources like their service representatives' time, which can be used for higher-value cases.
Charts showing expected impact of AI agents on KPIs and service leaders' perceptions of AI benefits.
Against this backdrop of growing AI case resolution, customer FAQs emerge as the leading use case for AI agents - a natural fit given their role in helping customers to resolve issues independently independently.
Other prominent agent applications include providing answers to order inquiries, as well as offering product recommendations that are personalized to the customer's needs, preferences, and past purchase history.
Charts showing top field service productivity barriers as reported by leaders and technicians (travel time, scheduling conflicts, waiting on parts, switching apps), and hours spent on low-value tasks.
Field service leaders aren't just experimenting with AI - they're betting big on its impact. Ninety-six percent of field service teams plan to use AI for instant access to information through knowledge retrieval, because a technician's time is better spent solving than searching. Many teams are considering visual diagnoses and repairs guided by augmented reality (AR). Forty-five percent currently use AI for AR-guided repairs, but another 43% plan to adopt it.
Technicians say AI could tackle 35% of admin work, freeing up two hours a week. Eighty-eight percent report at least a moderate improvement in technician utilization - and 85% report at least a moderate improvement in dispatcher productivity.
85% of field service leaders believe their AI investments will increase over the next year.
Charts showing reported benefits from AI in field service (e.g., technician utilization, dispatcher productivity) and current/expected use of AI for tasks like knowledge retrieval, visual diagnosis, and predictive maintenance.
Technicians are open to new tools that enhance their work. Who could blame them? There's a possible future where AI agents handle all the scheduling calls and paperwork while they focus on the work they're actually trained to do - no more interruptions during complex repairs, no more juggling appointments when there are real problems to solve.
Technicians are ready for this shift. Eighty percent want less time on admin tasks and more time doing what matters. The breakdown is clear: 87% believe AI would make their job more satisfying, 83% expect better appointment accuracy, and 82% just want more time for the work that actually matters.
Data on this page is from a related study of U.S. tradespeople and technicians.
Technicians think AI agents could do 35% of admin tasks, saving around 14 hours per week.
Agentic maturity is a transformational journey from 'good' to 'great' - and beyond. 'Great' means handling simple interactions with autonomous experiences, while also helping humans with complex customer requests.
Ready to augment your workforce with AI? Our digital labor guide shows you how. Read our guide
As organizations strive to deliver exceptional customer experiences, AI has emerged as a transformative force in service. While AI holds promise for service delivery, its adoption isn't without challenges. By understanding the obstacles to AI implementation and harnessing its potential, businesses can improve customer interactions, streamline operations, and drive growth as they evolve into agentic enterprises.
Service teams face challenges like meeting customer demands with limited resources, talent shortages, and implementing AI successfully. However, companies who've integrated their service channel data in one unified platform are 1.4x more likely to call their AI implementation very successful compared to those with siloed systems.
Companies are incorporating predictive, generative, and agentic AI to deliver faster, more accurate, and more personalized interactions. Leaders expect AI agents to amplify prior AI outcomes and are backing that expectation with investment. Seventy-ninety percent of service leaders say investment in AI agents is essential to meet business demands.
Conversational AI is reshaping customer communication across digital channels, like text and chat, increasing self-service resolution rates. When cases do need human attention, the right AI tools maintain context. Eighty-five percent of service professionals with voice AI say transitions to human representatives are seamless for customers.
Field service organizations face inefficiencies due to administrative tasks, scheduling issues, and long waits for parts. AI can help. Eighty-five percent of field service leaders believe their AI field service investments will increase over the next year.
Chapter 1: Teams Tackle AI Adoption Challenges
Eighty-two percent of service professionals agree that customer expectations are higher than they used to be. And customers expect a lot, from 24/7 support to tailored interactions.
And though 81% of service representatives say building relationships with customers is an important part of their job, they spend less than half their time (46%) with customers due in part to administrative tasks and internal responsibilities.
Throw in an expected case volume increase over the next year, and you have a recipe for service rep burnout and a lot of unhappy customers. Fortunately, service leaders also expect increases in budget, which can be put toward making operational improvements.
43% of consumers say a poor customer service experience will prevent them from making a repeat purchase.¹
Changes Service Leaders Anticipate and How Service Representatives Spend Their Time
In addition to keeping up with changing customer expectations, service leaders also cite difficulty hiring and retaining employees as a top service challenge.
Twelve percent of service employees left their company over the past year, and these highly trained individuals are often hard to replace. When hiring, more than a third of service teams struggle meeting demands for better work-life balance and wages, as well as finding talent with the right skills.
To address service capacity demands, leaders say the most effective tactics are expanding training and skill development and implementing self-service for customers. At companies with AI, leaders cite AI for customer use as the #2 tactic.
As technology becomes increasingly complex, so do cybersecurity threats, with attacks ranging from data poisoning to cloud breaches.
IT security leaders acknowledge that AI further complicates the matter - a concern that is unlikely to fade as the technology becomes increasingly prevalent and autonomous.
75% of IT security leaders believe AI-driven cyber threats will soon outpace traditional defenses.¹
Indeed, service leaders cite security concerns as their #1 challenge while implementing AI, and over half say it's delayed or limited these initiatives. To combat the issue, 86% say they're willing to pay more for technology that keeps data secure.
Top AI Implementation Challenges and Security Concerns
Silos across teams and technologies obstruct many activities - and AI implementation is no exception. Forty-four percent of service leaders with AI say tech silos have delayed or limited their AI initiatives.
But more organizations than not are making efforts to connect their technology across channels and teams, and those with connected technology report greater success with AI implementation. Eighty-eight percent of service leaders say they're prioritizing tech integration to support their AI initiatives.
Organizations that integrate service channel data in one unified platform are 1.4x more likely to call their AI implementations very successful compared to those with siloed systems.
Charts showing extent of system connection and AI success based on integration levels.
Chapter 2: AI Agents Redefine Customer Service
Companies are investing in all three forms of AI: predictive, generative, and agentic. Sixty-ninety percent of service professionals say their organization uses at least one form of AI, with 39% saying they use agentic AI.
Predictive AI forecasts issues (such as when a customer is likely to experience a problem with their product or service), generative AI creates new content (like automated responses to customer inquiries), and agentic AI takes autonomous actions (like completing routine tasks, providing real-time guidance, and collaborating with service representatives to resolve intricate customer issues).
Only 6% of service leaders don't expect to use agentic AI within five years - a finding that makes sense, given that 79% say AI agent investment is essential to meet business demands.
Infographic illustrating the benefits of integrated technology for service teams.
Chapter 3: AI Gets Conversational with Voice and Multimodal Interactions
Multimodal AI is technology that can handle different types of input - voice, text, chat, and visual - all in one system. AI agents are turning these touchpoints into conversations using natural language.
True multimodal interactions preserve history and context across all touchpoints, allowing organizations to eliminate the friction customers experience when switching between different channels and modes of conversation. Already, 36% of organizations with both voice and text AI have integrated these modes.
Infographic showcasing benefits of AI for customer service, including efficiency and customer satisfaction.
Conversational AI works best when it's built on your organization's data - ensuring it delivers accurate answers while maintaining your brand voice and tone. It also taps into customer data to personalize every interaction - speaking their language, matching their tone preferences, and adapting to their communication needs.
Companies that smoothly hand off conversations from AI agents to human representatives are getting high marks. These smooth transitions maintain customer satisfaction while empowering human representatives to immediately focus on solving the problem rather than gathering background details.
Chart showing service professionals' positive views on conversational AI benefits, including increased self-service resolution, accelerated resolution times, enhanced accessibility, freeing representatives for complex issues, and cost cutting.
Service professionals with conversational AI are impressed with its performance. The technology performed well across the board, with 88% of companies saying it is good or excellent at keeping their brand voice consistent. However, there's still room for improvement across the board.
One such area is understanding the nuances of dialect and emotions. While 35% of service professionals say their AI is excellent at understanding emotions, others are less impressed. This represents a major leap toward making AI interactions feel truly natural.
Chart showing the perceived effectiveness of AI at various tasks such as maintaining brand tone, switching modes, handing off to humans, understanding emotions, conversational language, different dialects/accents, and managing complex conversations.
The human-machine partnership reshapes how service teams operate. When AI handles routine tasks, teams see chances to focus on more pressing business needs. Sixty-five percent of teams with AI report more opportunities to focus on developing relationships with customers.
Fifty-four percent of teams with AI report more opportunities to focus on improving processes. The numbers tell the story - teams using AI discover more opportunities to support customers, colleagues, and the business.
Bar chart comparing opportunities for representatives at organizations with AI versus those without AI, across tasks like developing customer relationships, technology training, working with high-value customers, and more.
Chapter 4: Agentic AI Makes Field Service Safer and More Efficient
Field service professionals face frustrations with inefficiency, and one culprit is administrative tasks. Mobile workers estimate that 18% of their working hours - more than 7 hours per standard working week - are "wasted" on admin duties, such as filling out forms and hunting for information instead of fixing problems for customers.
When asked about the barriers that stood in the way of productivity, both technicians and field service leaders highlighted issues with scheduling and waiting for parts. These aren't just operational hiccups. They're universal productivity killers.
37% of technicians say admin tasks keep them from doing their actual jobs.
1 Salesforce Snapshot Survey: Field Service, 2025.
7.27 hours of a 40-hour work week are "wasted" on low-value tasks.
Base: Service ops and leaders with AI.
More difficult than expected 10% As expected 62% Easier than expected 28%
Base: Service leaders with AI.
Leaders say it takes:
Technicians say it takes:
Base: Field service leaders.