Discover how predictive AI flags at-risk accounts and recommends timely resources, helping teams resolve small issues before they become big frustrations.
Patrick Evenden
Head of Thought Leadership, EMEA
Workday
AI in customer experience is the use of AI tools, such as AI agents and LLMs, to personalise and improve the customer journey. What was once an emerging technology is already an essential part of customer experience strategy.
PwC reports that nearly nine in ten organisations have already implemented AI in customer-facing functions, including AI customer service and marketing. That momentum is expanding what companies can learn from every interaction – and how quickly they can put those insights to work. Companies are using AI to:
Personalise recommendations, offers and communications based on customer preferences and behaviour
Anticipate customer needs earlier and identify opportunities for proactive outreach
Power intelligent self-service experiences that resolve routine questions faster
Give customer service teams real-time guidance and relevant customer context during interactions
Analyse customer interactions and feedback to uncover trends, recurring issues and opportunities to improve
Together, these applications signal a broader shift in customer experience. Information that once stayed within individual interactions, channels or teams can now help shape how companies engage customers, support employees and make better decisions across the business.
AI-driven customer experiences extend far beyond chatbots and automation. Organisations are using AI to better understand customer behaviour, equip employees with real-time insights and make faster, more informed decisions across customer-facing functions.
Six of the top ways AI is enhancing the customer experience are:
Customers expect interactions to reflect their needs, preferences and history. Generic recommendations or requests for information they’ve already shared can quickly create friction.
AI helps companies analyse customer data and use the insights to tailor experiences in ways that feel more relevant and timely, such as:
Recommending products, services or content based on behaviour
Tailoring offers and communications to customer preferences
Adapting personalised interactions as needs change over time
By applying personalisation across the journey, companies create experiences that feel more connected and responsive at scale.
There are usually early warning signs before a customer reaches out. A decline in product usage, repeated visits to help content, missed onboarding milestones or rising support requests. AI can help teams identify those patterns and act sooner by:
Flagging accounts that may need attention
Recommending timely resources or outreach
Helping prevent small issues from becoming larger problems
With earlier insight, teams can provide more proactive support and strengthen the customer relationship before frustration builds.
Customers expect each interaction to build on the last, no matter which team or channel they use.
Customer journeys often span marketing, sales, service and account management. Yet customers expect each interaction to build on the last, no matter which team or channel they use.
AI can help connect information across the journey so teams can:
Carry customer context from one interaction to the next
Use service issues to inform future outreach
Reduce the need for customers to repeat information
That continuity helps companies deliver a more consistent experience across touchpoints while making each interaction feel more informed.
Employees make better decisions when they have the right information at the right time. But customer details are often spread across CRM systems, support platforms, knowledge bases and other tools.
AI can bring that context together by helping employees:
Summarise previous conversations
Surface unresolved issues
Recommend relevant knowledge articles or next steps
This kind of human-AI collaboration helps employees spend less time searching across systems and more time focusing on customer conversations, so they can respond with greater speed and confidence.
Customer demand can rise quickly during product launches, seasonal peaks or service disruptions. When support teams are stretched, speed and quality can suffer.
AI helps organisations manage fluctuating demand by:
Answering routine questions
Routing requests to the right team
Prioritising high-impact cases
Gathering information before an employee joins the conversation
That allows employees to focus on complex issues where human judgment matters most, helping organisations maintain fast, consistent service.
Every customer conversation contains signals about what is working, where friction exists and what customers need next. But as feedback grows across calls, emails, surveys, chats and support cases, handling large data volumes becomes difficult to manage manually.
AI-driven sentiment analysis can help organisations:
Identify recurring customer pain points
Track changes in sentiment
Spot emerging issues across large volumes of interactions
Those insights can inform product, service and journey improvements, helping organisations address recurring problems before they affect more customers.
Used well, AI creates a cycle of continuous improvement, where each interaction becomes a chance to learn and improve.
Customer experience is shaped by every interaction a person has with an organisation. To improve it, companies need to see those moments as part of a connected journey, understand needs as they emerge, and give employees the context to respond with confidence.
AI makes that possible at scale. It helps organisations turn signals across the customer journey into more personal, timely experiences, faster resolutions and better decisions across the business.
Used well, AI creates a cycle of continuous improvement, where each interaction becomes a chance to learn and improve. With human judgment and empathy still central where they matter most, companies can create experiences that feel more relevant, responsive and valuable.
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