Agentic AI in CX: Navigating Hype, Reality, and the Future of Customer Operations

The tides of transformation are shifting as businesses increasingly embrace agentic AI to navigate a landscape shaped by labor shortages, heightened customer expectations, and the relentless pursuit of operational efficiency. No longer a futuristic concept, agentic AI has become a strategic necessity within the boardroom. A recent report indicates that 96% of ANZ C-suite executives consider its integration a priority for the upcoming year. Yet, while enthusiasm is high, realising AI’s full potential is proving to be more complex than many anticipate.

For leaders in customer experience (CX), call centers, and business process outsourcing (BPO), the rise of agentic AI presents a significant opportunity as well as a strategic challenge. The sector has long been at the forefront of automation, with AI-driven chatbots, self-service solutions, and workflow automation integrated into various service operations. However, agentic AI—AI that can autonomously plan, reason, and act—signals a more profound shift. It is set to reshape CX delivery models, prompting leaders to rethink their people, processes, and technology strategies.

The Expectation vs. Reality Gap in Agentic AI for CX and BPO

The prevailing industry narrative suggests that AI agents will soon replace a significant portion of human-led customer interactions, reducing labor costs while also enhancing efficiency and personalisation. However, IBM’s analysis of AI agents in 2025 highlights a stark reality: today’s AI systems still struggle with reasoning, contextual understanding, and the complexities of human communication.

AI excels at handling structured, rule-based tasks; however, its ability to interpret ambiguous requests, understand nuanced customer emotions, and make judgment-based decisions remains limited. AI agents can be trained to perform specific CX functions—such as responding to FAQs or triaging support tickets—but they still lack the deep contextual intelligence required for more fluid, high-value customer interactions.

For CX leaders, this presents a critical challenge: how to integrate AI in ways that enhance rather than undermine the customer experience. Contact centres already face issues such as agent burnout, high turnover, and rising consumer expectations for faster, more personalised service. AI can act as a powerful enabler; however, if implemented poorly, it risks creating new pain points, including inaccurate responses, excessive reliance on automation, or failed escalations that frustrate customers instead of addressing their concerns.

In the BPO sector, where cost efficiency is often a primary driver, the temptation to automate entire workflows can be intense. However, most AI agents today lack the adaptability to handle the diverse range of queries that BPOs process across industries daily. Over-automation risks eroding customer satisfaction, increasing churn, and damaging brand trust, especially if AI-driven interactions feel impersonal or struggle with complex problem-solving.

Strategic Imperatives for AI in CX and BPO

To close the expectation-reality gap, CX, call centre, and BPO leaders must adopt a strategic, phased approach to integrating artificial intelligence. Instead of treating agentic AI as a standalone solution, it should be embedded within a comprehensive operational framework that aligns technology with customer needs, workforce transformation, and business objectives.

1. AI as a Co-Pilot, Not a Substitute

AI’s greatest value in customer experience (CX) and business process outsourcing (BPO) lies in augmentation rather than substitution. The most effective implementations combine AI with human intelligence, enabling AI to manage repetitive, high-volume tasks while human agents concentrate on complex, relationship-driven interactions.

• Real-Time AI-Augmented Customer Engagement: AI acts as a real-time co-pilot for live agents, providing sentiment analysis, contextual prompts, and recommendations for the next best actions, enhancing efficiency and personalisation.
• Proactive Issue Resolution: AI-driven predictive analytics can foresee customer needs and address issues before they escalate, lowering inbound call volumes and boosting satisfaction.
• Empowered, Not Replaced Agents: AI-powered knowledge assistants can support agents in real time, enhance first-call resolution rates, and reduce the cognitive load that contributes to burnout.

2. People, Process, and Technology: The Managed Service Evolution

For large-scale contact centres and BPOs, AI adoption should be thorough, including workforce strategies, operational processes, and technology ecosystems.

• People: AI-driven transformation demands new skills, roles, and approaches to work. The future call centre agent will not simply read scripts but will be a problem solver armed with AI insights. Workforce strategies should focus on reskilling agents, enhancing AI literacy, and establishing career pathways that include AI oversight.
• Process: AI requires a re-evaluation of operational workflows to facilitate smooth collaboration between humans and AI. This entails redesigning case management, escalation pathways, and governance models to improve AI-human transitions.
• Technology: Integrating AI into customer experience (CX) through CRM platforms, contact centre software, and customer data lakes is crucial. A fragmented AI implementation may lead to disjointed experiences; however, an AI ecosystem shaped by real-time customer data can enhance personalisation and contextual awareness.

3. AI Governance and Trust: The Ethical Imperative in CX

The biggest risk of adopting AI is the erosion of customer trust. AI-driven decisions must be transparent, unbiased, and aligned with ethical standards to guarantee fairness and clarity.

• AI Guardrails: Organisations must establish robust AI governance frameworks to ensure accurate decision-making and prevent unintended biases, particularly in regulated sectors such as finance and healthcare.
• Customer-Centric AI Design: AI agents should be empathetic, adaptable, and culturally aware, especially in the context of BPOs operating in diverse global environments markets.
• Human-in-the-Loop Systems: AI must not operate in isolation. Businesses need to establish fail-safe mechanisms that enable effective human intervention when automation encounters its limits.

The Future of AI in CX and BPO: Intelligent, Human-First AI

The most successful AI strategies will prioritise humans, using AI to enhance—not diminish—the customer experience. The future of agentic AI in CX and BPO focuses not on replacing human agents but on making them smarter, faster, and more effective.

Organisations that combine AI efficiency with human empathy will gain significant advantages, such as cost savings, increased operational agility, and enhanced customer experiences. However, success will depend on strategic execution to ensure that AI adoption aligns with business objectives, ethical standards, and customer trust.

As AI continues to evolve, the leaders in CX and BPO will excel at the intersection of technology and human experience, where AI serves as a force multiplier for operational excellence and customer satisfaction. The future is not just automated; it is intelligently augmented, shaping a world where digital intelligence and human ingenuity collaborate to achieve better outcomes for customers and businesses alike.