Technology is Once Again Promising to Transform Customer Service

Customer Service Technology Has Yet to Meet Expectations

Many consumers continue to find customer service difficult to navigate. Interactive voice response systems can lead callers through lengthy menus, while chatbots often provide generic answers that do not resolve specific problems. Digital self-service tools may require customers to re-enter information or fail to provide a clear path to resolution.

Only 18% of consumers say technology has significantly improved their service experiences, according to an Accenture report published in March 2025.

Businesses are continuing to invest in artificial intelligence. The current generation of technology includes real-time translation, conversational AI and agentic systems that can assess a situation, select a response and take action with limited human involvement.

Companies can use these tools to reduce costs or improve customer outcomes. Accenture found that 87% of customers would leave a brand after a single bad service experience.

Customers Prioritize Results, Empathy and Simplicity

Surveys involving more than 7,000 consumers identified three main features of a positive service interaction. Customers want effective service that solves a problem without wasting time or creating additional work. They also value responses that recognize how an issue may affect their finances, health, home or employment.

Consumers also want straightforward processes that help them understand what to do next time. They are generally willing to use human-led, technology-led or combined service models when those models resolve the issue and account for the customer’s circumstances.

Companies can improve retention by closing the gap between customer expectations and current service performance.

AI Systems Could Address Problems Before Customers Report Them

Traditional customer service is reactive: A problem occurs, the customer notices it, and the company responds after being contacted. Agentic AI could change that sequence by identifying and addressing some issues before customers notice them.

A broadband provider, for example, could detect deteriorating connectivity, reroute traffic and install a firmware update. A financial institution could identify unusual account activity, contact the customer through an approved channel and recommend freezing an account or replacing credentials.

In health care, a system could connect a reported symptom with a new medication, notify the patient’s care team and present appointment options.

Category-Specific AI Concierges Begin to Emerge

One potential application is the category concierge, an AI-enabled service designed to manage a broader set of needs within travel, health care, finance or another field.

A travel concierge could retain information about a family’s budget, previous trips, preferred accommodations and transportation needs. It could recommend destinations, book flights and lodging, arrange a rental vehicle and monitor potential disruptions. If prices fell or a flight was canceled, the system could propose or complete changes.

Similar systems could coordinate appointments across health care providers or offer financial guidance during events such as a home purchase, college enrollment or retirement.

Human support would remain necessary for high-stakes decisions or emotionally sensitive circumstances. Customers also should not have to repeat information when moving from an automated system to a person.

Consumers Are Bringing Their Own AI Agents

General-purpose AI assistants are also changing how customers approach companies. These tools can review return and warranty policies, compare products, summarize contract terms and prepare detailed complaints.

As a result, some customers may begin a service request with more information than the employee handling it. AI assistants can identify relevant service-level agreements, check deadlines and suggest potential remedies.

Technical and security barriers remain. Most companies cannot reliably verify that an AI agent is authorized to represent a particular customer, and no established protocols allow external agents to interact directly with systems behind corporate firewalls.

Businesses may face pressure to clarify policies and make digital processes easier for people and machines to interpret. AI assistants could steer customers away from companies with confusing terms or unreliable purchasing systems.

Shared Memory Could Reduce Repeated Explanations

A common source of frustration is the need to repeat information after being transferred between representatives or service channels. Agentic systems could create continuity by retaining a customer’s history, preferences, previous decisions and unresolved commitments.

This shared memory could carry context from one interaction to the next. An employee taking over from an AI system would receive the relevant background, while an automated service could recognize earlier agreements and avoid asking the same questions again.

Persistent customer memory will require transparency, consent and secure data handling.

Human Representatives Take On More Complex Cases

As AI handles routine questions, customer service employees are likely to take on more complex work. Representatives may spend more time assisting vulnerable customers, resolving multiple connected issues and managing cases involving significant financial or personal consequences.

Their roles may shift from following scripts to supervising automated agents and making decisions based on a broader view of the customer. Emotional intelligence, judgment and authority to resolve problems will remain important.

This model requires companies to redesign work around employees and technology rather than simply add AI to existing processes.

Implementation Requires Organizational Changes

Companies considering agentic customer service must treat service as part of their customer retention and revenue strategy, not solely as an operating expense. They also need to connect fragmented data and software systems, so AI tools can function across departments.

Implementation requires coordination across customer service, technology, legal, security and operations teams. Organizations also need rules covering consent, identity verification, data security, automated decisions and human review.

AI could improve service by detecting problems earlier, maintaining context and reducing repetitive work while preserving access to human representatives.

Discover more at Accenture.