Customer experience (CX) is undergoing a profound transformation. As operational pressures mount and customer expectations rise, businesses are seeking new ways to deliver faster, more personalised service without escalating costs. Against this backdrop, agentic AI — a form of artificial intelligence capable of not just suggesting actions but autonomously carrying them out — is emerging as a powerful tool to reshape the economics of CX delivery.
The shift from traditional agent-assist tools to true agentic AI reflects a broader change in business priorities. For years, technology in customer service focused on helping human agents work more efficiently. Smart prompts, knowledge bases and automated workflows all contributed to incremental gains. Yet rising volumes, growing customer impatience, and ongoing labour shortages have exposed the limits of this model.
According to research from Gartner, customer service costs are now rising by an average of 5% per year, even as budgets tighten. Meanwhile, McKinsey estimates that automation could reduce service costs by up to 40% while improving customer satisfaction if deployed intelligently. The key lies in the move from support to substitution: allowing AI not merely to assist agents, but to resolve low-complexity cases independently.
Agentic AI models, such as those provided by companies like Deepdesk that we covered earlier this week, are designed to interact dynamically with customer queries, back-end systems and workflow engines, performing actions without needing constant human oversight. This capability has profound financial implications.
The economics of agentic AI —
Average handle time (AHT), which is a critical cost driver in contact centres, can be significantly reduced when simple issues are resolved without escalation. A 2023 report from Forrester found that AI-driven resolution of routine inquiries could reduce AHT by 20–30%, leading to direct labour savings and improved first-contact resolution rates. At the same time, freeing human agents from repetitive tasks allows them to focus on higher-value interactions, strengthening customer loyalty and improving lifetime value metrics.
However, the opportunity comes with a clear caveat: businesses must avoid the trap of viewing automation purely as a cost-cutting exercise. Poorly deployed agentic AI risks alienating customers, increasing churn, and damaging brand equity. Research from PwC shows that 32% of customers would walk away from a brand they love after a single bad experience. In highly competitive markets, a marginal saving on contact centre costs could easily be outweighed by lost revenue. This makes careful implementation essential. Enterprises must identify which customer journeys are appropriate for autonomous handling, design escalation paths that are seamless and transparent, and rigorously train AI models to understand brand tone, empathy thresholds and regulatory compliance requirements.
Equally important is the need for ongoing monitoring and optimisation. AI models do not stay static. They must be evaluated continuously against service metrics such as Net Promoter Score (NPS), customer effort score (CES), and customer satisfaction (CSAT) to ensure they are delivering the intended benefits. Businesses should also prepare for regulatory scrutiny as policymakers sharpen their focus on the role of AI in customer interactions.
The UK Information Commissioner’s Office (ICO) has already indicated that organisations must ensure transparency and fairness when deploying AI in decision-making roles — a principle that extends directly to agentic CX models.
The broader economic case for agentic AI is compelling. In sectors from retail to banking, leading organisations are already realising double-digit improvements in customer satisfaction scores while simultaneously reducing service costs. But the early winners in this space are not those who pursued automation for its own sake. They are the companies that understood a simple truth: in customer experience, doing more with less only works if you first invest in doing it right.
