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The future of CX is AI-powered and human-centric
AI is revolutionising customer experience, but companies must prioritise data quality and human oversight to deliver personalised services that builds loyalty and drives growth
Over the past decade, the proliferation of artificial intelligence (AI) has dramatically transformed customer experience (CX). Customers now expect faster, hyper-personalised services, and companies are constantly trying to keep up with new technologies.
In a rapidly evolving digital marketplace, where products and services are commoditised and competition is just a few clicks away, the brands that stand out are those that quickly adopt AI and integrate it into their CX strategies.
A recent 2025 CX trends report by Zendesk noted that “human-centric AI is redefining customer loyalty”, noting that companies balancing technological advancements with empathetic customer service have a higher chance of cultivating long-lasting relationships.
While 90% of companies are already using generative AI in some capacity, with nearly as many citing it as a top priority, companies must be careful not to get too caught up in the AI hype and neglect the “C” in CX – the customer.
Earlier this year, I spoke at TDCX Talks, an event that brought together industry thought leaders to explore how AI is reshaping customer interactions. There, I shared what I deem the 5Cs of customer expectations: consistency, convenience, competence, customisation and continuity.
When used appropriately in alignment with these 5Cs, AI has the potential to revolutionise customer engagement. However, processing vast amounts of customer data with AI can also lead to misuse, causing serious repercussions for businesses, including ethical and legal issues, operational inefficiencies, or damage to reputation.
The most powerful AI isn’t the one that solves the most complex problems but the one that solves the right problems. Instead of asking, “What can AI do?”, perhaps organisations should ask, “What should AI do?”
Singapore’s AI ambitions
As nations worldwide compete for AI dominance, it’s worth noting that Singapore is making significant strides in harnessing AI to capture new opportunities and drive economic growth. It was among the first countries to publish an AI plan in 2019, and its refreshed National AI Strategy 2.0 underscores its commitment to building a trusted AI ecosystem, driving innovation and empowering businesses to engage with AI.
In this year’s Budget speech, then deputy prime minister Lawrence Wong announced that Singapore would invest over S$1bn in the next five years to enhance its AI capabilities. While we’re heading in the right direction, there’s still more to be done.
Like Singapore, TDCX is excited about integrating generative AI into CX to drive significant economic value for businesses. One key challenge, however, is ensuring that the data used in CX applications is fit for purpose.
AI data labelling: Key for customer engagement
Without accurate, structured, and reliable data, firms are not ready to leverage generative AI. Businesses must first undertake the critical step of data labelling – annotating raw data to make it understandable for machine learning algorithms.
For instance, in a mystery shopping exercise conducted by TDCX this year across multiple industries, chatbots scored lowest in providing quality service compared to mobile apps and email. One reason for this inconsistency could be that the data fed to these AI models wasn’t well-prepared in the first place.
Data management is a critical challenge that can hinder companies from scaling AI use cases. Developing a robust AI model requires an iterative process based on experimentation and continuous refinement using feedback from various sources.
Beyond accuracy, raw data must be enriched with additional information to enable machine learning models to make relevant and insightful suggestions to customers.
Keeping humans in the loop
Chatbots, mobile apps, automatic email replies, and even robots offer innovative ways to engage customers, but they don’t always guarantee better service. The rise of AI often overshadows what truly matters: practical solutions that deliver quality output.
In Asia specifically, Western companies may find it challenging to navigate cultural nuances, language, and regulatory differences. This is where human intelligence plays a critical role. Responses that miss the mark – failing to grasp colloquialisms, idiomatic expressions, or cultural references – can feel impersonal and frustrating. Human intelligence is essential in training machine learning models to ensure they understand and connect with diverse audiences.
Moreover, delivering excellent customer experiences requires skilled talent, and empathy's role in shaping CX cannot be overstated. In times of crisis, displaying warmth and empathy helps customers feel supported. This, in turn, elevates the customer experience, boosting satisfaction and loyalty.
Ultimately, when designing customer interactions, we must harness the true value of each resource – AI for efficiency and humans for empathy.
Lianne Dehaye is senior director of TDCX AI, a Singapore-based supplier of AI-powered CX tools
