How agentic AI will change the customer experience

Alex MacPherson, Manhattan Associates

Six out of 10 customers (63%) expect AI-fuelled technologies to become the primary mode of customer support in the years to come, compared with 21% just four years ago, an annual survey of 1,000 US consumers by customer service expert Shep Hyken shows.

That is a staggering change in expectations, but when you consider the advance of generative AI and agentic AI in the last two and a half years, maybe that leap forward is not quite so surprising.

Since the advent of ChatGPT, the way humans have interacted and collaborated with AI has taken big strides forward. In the early days of ChatGPT, users were asking it things like “how many ounces are in a pint?” and “generate a picture of my dog in space”. Fast forward a couple of years, and generative AI tools can build complex user interfaces, analyse large data sets and ensure we are using a friendly, professional tone in the emails we send. With the more recent evolution of agentic AI, industries are taking another dramatic leap forward.

What is agentic AI?

Agentic AI refers to artificial intelligence systems that can act independently to achieve specific goals. Unlike earlier AI tools that simply responded to questions or followed basic instructions, agentic AI can take initiative, make decisions and perform tasks without needing constant human direction.

Think of it as the difference between a helpful assistant who waits to be told what to do, and one who sees a problem, makes a plan and takes care of it proactively.

What does agentic AI mean in supply chain commerce? Think AI-powered supply chain and retail specialists, available on demand, capable of proactively optimising inventories in response to fluctuations in real-time demand; agents that can autonomously respond to consumer queries without the need for constant human guidance; or agents that can assist store operations managers by keeping tabs on store performance or sales goals.

Agentic AI represents an opportunity to improve customer experiences while also maximising operational efficiency. But let’s be honest: the goal of AI is not to simply assist the customer without involving a human – it is to provide a better experience for the customer, whether they talk to an AI agent, a human contact centre representative, or any combination of the two.

At a time when customer retention is more important than ever, we cannot let the excitement of developments in the field of AI distract us from the primary goal: providing world-class customer experiences.

The clue is in the name

Agentic AI will revolutionise the customer agent space, as it can autonomously provide 24/7, real-time support to customers: from basic FAQs about return policies to questions such as “where is my red jumper and when will it be arriving?”, to truly actionable flows like “My item arrived damaged. Can you send a replacement?” or “I ordered this last week on your site, but now it’s on Sale. Can you match the new price?”

Agentic AI offerings infused with order, payment, store and product availability information deliver personalised, contextual customer service, akin to that of human agents, while deflecting customer service enquiries, boosting customer satisfaction and delivering meaningful ROI, fast.

One example is the growing use of chatbots, which serve as efficient tools for providing quick and easy virtual assistance, while enhancing customer interactions. In fact, 74% of online shoppers prefer using chatbots for basic queries, a survey of 1,000 shoppers by AI customer service solution Intercom found – a clear indication that the integration of such technologies is not just helpful but expected.

This aligns closely with insights from the Unified Commerce Benchmark UK report, which reveals that many specialty retailers in the UK still fall short in delivering frictionless, tech-enabled experiences, particularly in bridging the gap between digital convenience and in-store support.

Offering an assist to the agents

Even with all the advances in AI, many customers will continue to get support from

customer service representatives (CSRs). Thanks to AI, the service they get will be faster and more accurate, because those CSRs will be boosted by the power of generative AI.

Here is an example: a customer chats with a CSR to ask if they can return a dress to their nearby store. Without AI, many agents need to use multiple systems to answer this question.

First, they look up the customer to find their loyalty status. Second, they look up the order to see how long ago the item was shipped and if the item is returnable at stores.

Next, they might go to a knowledge management system to read about the return policy for this specific scenario.

With AI, an agent can simply ask the AI assistant, “Can the customer return this dress to the Oxford Street store?”, and AI seamlessly looks up the information across the different systems and responds with a simple “yes” or “no”.

From getting answers to common questions to troubleshooting customer issues, having more information and context about a customer’s experience with the brand, and providing summaries of customer sentiment, past purchases and recent conversations, AI is putting the brand in the fast lane when it comes to customer support.

Better insights make for great service

One of the ways generative AI shines the most for customer service organisations is by mining data across all customer chats, emails and messages in real time, identifying behavioural trends and buying patterns.

Brands and retailers can keep a pulse on their customers and react more quickly, even proactively in some cases, to the “voice of the customer”, rather than waiting for after-the-fact survey responses. For example, if CSR leadership sees an abnormally high volume of contacts related to payment issues on the website, they can detect and resolve issues proactively, reducing the chances of customer escalation and dissatisfaction. The same goes for product quality issues or problems with certain carriers: CSR leadership can react quickly when they have a real-time pulse on their customers’ conversations.

From the early days of mechanical automatons to more recent conversational generative AI-powered chat experiences, scientists, engineers and futurists have dreamed of a time when technology can work and act intelligently and independently. Recent advances in generative and agentic AI are bringing the vision of an autonomous future a step closer to reality but, as it does, it should also remind us of the fundamental importance and value human customer service representatives will continue to play as customer expectations and brand narratives continue to evolve.