As AI evolves, its impact on CX will be profound as it becomes an integral part of the customer experience.
“Gen AI will fundamentally change the way we interact with technology and the world,” Joana de Quintanilha, VP principal analyst at Forrester, told CXM.
Artificial intelligence — known for its ability to offer massive productivity savings — is poised to become the centrepiece of future business strategies.
“We are moving towards a future where AI agents work alongside human agents, enhancing productivity and allowing for more human-centric tasks,” Pedro Andrade, VP of artificial intelligence, Talkdesk, told CXM.
The shift towards collaborative AI is expected to redefine how businesses approach customer service.
“AI has the power to help bridge customer service across regions, languages, and cultures. This is not a prediction for the future – it’s currently underway,” added Andrade.
For instance, gen AI can improve customer service by summarising previous customer interactions, making service more personalised. “Agents no longer need to ask customers to repeat their issues, thanks to AI summarisation,” de Quintanilha explained.
“Companies are at various stages of AI deployment. Some have already begun, while others are preparing to experiment. CX leaders can enhance customer satisfaction and operational efficiency with AI-driven tools that automate routine tasks, and improve response times,” said Matthias Goehler, CTO EMEA, Zendesk for CXM.
Industry impact
The contact centre industry, in particular, is witnessing a dramatic transformation due to AI. According to Gartner, companies that adopt AI applications like ChatGPT and Google’s Gemini report a 25% boost in operational efficiency.
With their advanced natural language processing capabilities, these tools will reshape customer service by handling entire conversations, from simple queries to complex problem-solving.
According to Zendesk’s Goehler, by the end of 2025, third-generation AI chatbots and bot-to-bot communication will enable complex task automation and more personalised customer experiences, meeting the demand for human-like AI.
In addition, the impact of AI will reach far beyond the call centre. In healthcare, for example, AI is being used to manage administrative tasks like updating patient information or scheduling appointments.
Retail is another industry where personalised shopping experiences — powered by AI-driven recommendations and virtual assistants — are becoming the norm.
In the finance sector, AI helps combat fraud, optimise risk management, and automate certain aspects of customer service. Some institutions are using it to analyse transaction patterns and forecast market trends, claimed Jake Canaan, VP of global sales engineering at Quantum Metric.
AI in multilingual customer service
One of the immediate practical applications of AI in CX is breaking down language barriers. Tools like Talkdesk’s AI Translator enable real-time translation of text between different languages.
The feature allows agents to provide more natural and personalised customer service, regardless of language, enhancing global customer support systems.
“Talkdesk AI Translator allows agents to respond in their own language, while the customer receives responses in their preferred language,” said Andrade.
“If you aren’t using gen AI for summarisation, translation, interaction and event discovery, search, and pattern finding across journeys, processes, and business capabilities, start today, ” added de Quintanilha.
AI and human agents
Despite these advancements, humans’ role in customer experience remains crucial. Most CX leaders emphasise that AI is not about replacing humans but augmenting their capabilities.
“In the end, it isn’t about choosing between AI or humans; it’s about leveraging the strengths of both to create a truly exceptional customer experience,” said Goehler.
A collaborative approach suggests AI handles routine and administrative tasks, while human agents focus on delivering empathetic and personalised customer service.
Over the last two years, AI in customer experience has had a chequerd history. Badly configured AI chatbots that failed to solve problems or resemble empathic service led to frustration and dissatisfaction.
“The drive into chatbots with the added sprinkle of gen AI has created disappointing experiences for customers,” said Maxie Schmidt, VP principal analyst at Forrester, emphasising that while the potential is vast, the technology remains in its infancy.
When companies prioritise efficiency and cost-cutting over genuine customer needs, they risk alienating their audience and undermining trust, leaving AI solutions to feel more like barriers than enhancements in customer service.
Agentic AI
Frustration with AI in CX could give way to customer delight with the advent of agentic AI, which is poised to be big this year. Agentic AI refers to AI systems capable of autonomous decision-making, which companies are increasingly adopting for both routine and complex tasks.
Organisations will start training their workforce to develop and deploy agentic AI agents while also forging policies to ensure their ethical and effective use.
“AI agents’ ability to autonomously complete more challenging customer inquiries will redefine customer journeys and employee experiences,” Andrade explained.
Agentic AI will allow human agents to deliver more creative and nuanced interactions, ensuring a balance between automated efficiency and human empathy.
What about the bad side of AI?
However, the rise of AI doesn’t come without challenges. Privacy concerns are mounting as AI systems collect vast amounts of personal data, often without clear consent.
Incidents like the recent data breach at OpenAI, in which a vulnerability in the AI system exposed users’ chat histories, compounded the security privacy concerns held by many consumers.
A recent Qualtrics report claimed that two-thirds of consumers wanted to buy from brands that offered tailored experiences to their needs, but over half also said they were highly concerned about privacy and personal information.
Bias and discrimination are also critical issues, as AI models can inadvertently perpetuate societal biases in their training data.
Furthermore, the automation of jobs through AI threatens employment in several industries, leading to economic disparities and job displacement.