Back to top
Today’s retailers are expected to adhere to two crucial objectives: to provide exceptional customer service at scale while empowering to innovate progressively. Achieving both is not possible without the incorporation of technologies that help understand customer desires and use these insights to provide tangible benefits.
AI agents are emerging as a breakthrough solution, helping retailers and e-commerce businesses achieve unprecedented results. The autonomous AI market is projected to reach approximately $28.5 billion by 2028 at a CAGR of 43.0%, reflecting the growing trend of these technologies in retail environments.
Unlike conventional automation, AI agents operate as intelligent experts that can simplify complex workflows and streamline processes such that they enable businesses to respond faster to market trends, work smarter without burning out, and focus on what truly drives business growth.
AI agents are autonomous, AI-powered entities that can resolve a wide array of requests. In contrast to traditional bots that operate within a pre-defined dataset provided to them, AI agents operate independently by automatically detecting user queries and responding based on both content and sentiment.
An AI agent goes beyond the power of generative AI, where instead of just assisting you, it can work even on your behalf when you are away from your operations. It can perform a range of functions, from promptly responding to questions to carrying out complex or multistep assignments.
What sets them apart from a personal assistant is that they can be modified to have a particular expertise. For instance, an AI agent can be created that knows all the products and services you offer and can use it to draft detailed responses to customer queries or automatically present details about a product.
You can take this a step further by building an AI agent that acts on your behalf while you’re trying to complete all your orders while building new customer relationships simultaneously. Having agents handle some of these routine tasks can boost productivity across various industries, from manufacturing to finance and retail, ensuring businesses can save money and time.
What sets AI agents apart is their ability to be intelligent, adaptive, and most importantly, be autonomous while carrying out its functions. Here are some factors that make AI agents stand out while resolving complex enterprise needs:
Unlike traditional models that may respond with “I don’t understand your question”, AI agents are capable of fully understanding conversations, just like a skilled human. From remembering previous interactions and understanding complex requests to keeping track of all conversations, AI agents have the contextual awareness needed to respond to any cue in real-time.
Every interaction makes AI agents smarter. By leveraging machine learning, they can pick up on emerging patterns and adjust to evolving user needs to fine-tune their responses. This adaptability ensures their responses are not one-dimensional.
Unlike conventional chatbots that adhere to rigid scripts and datasets, AI agents are capable of thinking beyond what they know. From unexpected questions to unique situations, they are designed to figure out the unknown. This flexibility means they can handle a diverse range of tasks while keeping interactions conversational and helpful, ultimately providing a memorable customer experience.
AI agents go beyond simple logics of causality i-e “a” leads to “b”. They function more like seasoned professionals with a deep understanding of their tasks. Powered by advanced neural networks, they can manage complex workflows and direct customer inquiries to the appropriate department and identify potential problems before they escalate.
Here’s a breakdown of how AI agents operate:
AI agents collect information from various sources, such as customer conversations, transaction records, and social media platforms. This information helps them understand the context and details of customer inquiries. Advanced AI systems process this data in real time, ensuring they have the latest insights to respond effectively.
By applying machine learning algorithms, AI agents identify patterns in the data and make informed decisions. For instance, they can select the most suitable response to a customer query based on previous interactions and the current situation. Their decision-making improves over time as they learn from past experiences and adjust their approach.
After making a decision, AI agents carry out the necessary tasks, whether it's providing answers, processing customer requests, or escalating complex issues to human agents. This process is designed to be smooth and efficient, ensuring that customers receive quick and accurate responses.
AI agents adapt by learning from each interaction, updating their algorithms, and refining their responses. This ongoing learning allows them to improve accuracy and effectiveness, staying aligned with evolving customer needs and business environments.
By combining these capabilities, AI agents can handle a wide range of tasks autonomously, such as making product recommendations, troubleshooting problems, and engaging in follow-up interactions. This frees up human agents to focus on more complex and value-added activities.
AI agents provide a plethora of benefits to your customers, human agents, support admins, and, ultimately, the entire organization. Some of these include the following:
AI agents can handle complex inquiries independently, freeing up human agents to focus on more strategic tasks. They streamline operations by gathering information, managing ticket backlogs, sending automated CSAT surveys, verifying users, and more, reducing the manual workload for support teams.
Operating around the clock, AI agents ensure customers always have access to assistance, regardless of time zones. This enhances customer satisfaction and loyalty while allowing businesses to manage higher support volumes efficiently during peak periods.
By integrating with backend systems, AI agents use customer data—such as purchase history, preferences, and behaviors—to deliver personalized responses. They also provide human agents with key insights, including customer intent and sentiment, enabling more personalized interactions.
AI agents can analyze customer interactions to identify patterns and opportunities for improvement. They recommend tasks that can be automated, helping admins refine support strategies and proactively meet customer needs.
By handling a significant portion of customer requests, AI agents reduce the workload on human agents. According to McKinsey, AI agents can save companies between $75 billion and $1.6 trillion annually, primarily through improved customer service and reallocating resources to other critical areas.
With proper controls and the temporary use of data, AI agents are designed to provide accurate and secure responses, ensuring customer interactions are handled with care and precision.
AI agents not only resolve issues independently but also assist human agents, streamlining the path to resolution for your customers and ultimately providing a more elevated customer experience.
In the healthcare industry, AI agents can effectively respond to any health queries, assist in the process of scheduling appointments with patients, or connect patients to the appropriate department based on their health concerns.
AI agents can analyze and interpret vast amounts of medical data, making them an effective means of supplementing the work of healthcare professionals in diagnosis, predicting health outcomes, and recommending treatment plans that will help patients live longer and better.
In the finance industry, AI agents can provide customers with immediate access to information on their accounts and transaction history while providing support for any queries (common or uncommon). By responding to all nuanced queries, AI agents help enhance overall customer experience in the finance industry.
They are also capable of monitoring transactions in real-time for any signs of fraud or risks. By analyzing transaction patterns and detecting any anomalies, these agents can handle risk effectively and alert financial professionals should any financial crisis arise.
The manufacturing industry can make the most out of AI agents as well. By automating the process of inspecting the performance of equipment and predicting failures before they happen, they can help minimize downtime and maintenance costs.
In addition, AI can optimize production schedules by dynamically adjusting to changes in demand, resource availability, and equipment status, ensuring that manufacturing processes run as efficiently as possible.
AI agents can also be leveraged in the media and entertainment industry. From answering questions about specific content available within subscription plans to providing personalized content suggestions based on user habits and preferences, AI agents can enhance user experience by making it easier for viewers to discover new movies or shows they are likely to enjoy.
Branded as Agentforce, Salesforce has its own Agentic AI that showcases a major advancement in automating business and CRM management. The platform enables organizations to create and deploy autonomous agents that can handle several tasks like analyzing inputs, solving tasks through comprehensive reasons, and streamlining workflows that require minimal human intervention.
Amazon is pushing itself at the forefront of revolutionizing customer experiences. For instance, its own AI agent, Alexa, is designed to assist customers in their shopping experiences and provide responses that directly address their queries and concerns. It can also analyze customer feedback and predict customer behavior, both of which are crucial in providing tailored experiences and yielding higher customer satisfaction.
Lufthansa, a German airline, is utilizing AI-based agents to manage over 6 million customer interactions annually to give 24/7 support in real-time. These agents are tasked to handle routine tasks like monitoring flight status checks, aiding in booking procedures, and responding to any complex passenger queries that may arise. This is enabling the airline to reduce wait times and delays, thus improving overall customer satisfaction.
While AI agents can yield several benefits in operations, there are some challenges and considerations one must keep in mind while employing AI agents:
Developing and operating advanced AI agents requires acquiring, storing, and moving massive volumes of data. Organizations should be aware of data privacy requirements and employ necessary measures to improve data security posture.
In certain circumstances, deep learning models may produce unfair, biased, or inaccurate results. Applying safeguards, such as human reviews, ensures customers receive helpful and fair responses from the agents deployed.
Implementing advanced AI agents requires specialized experience and knowledge of machine learning technologies. Developers must be able to integrate machine learning libraries with software applications and train the agent with enterprise-specific data.
Training and deploying deep learning AI agents require substantial computing resources. When organizations implement these agents on-premises, they must invest in and maintain costly infrastructure that is not easily scalable.
Like the integration of any technology into your business, of course, you want AI agents to consistently deliver on its designated functions while minimizing unnecessary costs. Some of the best practices for integrating AI agents into your operations are similar to onboarding a new employee: monitor early outputs closely and gradually increase the complexity of tasks as the agent becomes more proficient.
Setting clear objectives, mainly through process thinking, is crucial to ensure that the AI agents deliver on your expectations. Just like with a human employee, an AI agent is unlikely to meet expectations without clear understanding. It is best to avoid vague goals and focus on achievable targets within the agent’s capabilities and resources. Establish clear KPIs to track performance and use the insights to refine and enhance the model.
Continuously fine-tuning the LLM powering an agent isn’t practical, but refining the data it uses to make decisions and complete tasks is. In custom-built agents, improving memory techniques and data inputs can be done more frequently than adjusting the LLM itself. For those developing their own agents, these processes must be defined before deployment and fine-tuned over time to optimize performance.
Even if your AI agent is running perfectly, thoroughly inspect it in diverse scenarios, both before and after deploying it. Individually test all the components of the agent and ensure it is drawing data from relevant external systems.
Like a new employee, agents will need time to familiarize themselves with your organization and its processes. Start slowly by assigning tasks and closely monitoring results. Offer extensive oversight until the team is confident the agent can work independently. Designate oversight roles within a governance framework, ensuring your human-in-the-loop system allows for intervention and that the agent incorporates and prioritizes human feedback.
Strong access controls are essential, along with comprehensive network and infrastructure security. To protect the agent from unauthorized access and attacks, encrypt and anonymize its data where appropriate. Moreover, ensure secure coding, ongoing monitoring, incident response, and assurance practices are in place to safeguard your AI systems.
Despite being in its rudimentary stage, AI agents are emerging as the new trend that will be driving us towards reimagining customer engagement.
Retailers that adopt AI agents are highly likely to position themselves at the cutting edge of a market that rewards personalization, efficiency, and a strong sense of meeting customer demand with supply.
At the same time, incorporating AI agents into daily operations requires an urgent sense of responsibility to deploy and utilize them ethically and transparently. Customer privacy is as important as customer experience, and you can’t have one without the other. In essence, success in the retail industry is contingent on prioritizing both simultaneously and putting the customer first every step of the way.
Fill the form and discover new opportunities for your business through our talented team.
.png)
.png)
.png)
.png)
.png)
.png)
