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Businesses are increasingly using artificial intelligence agents to replace or augment the work of human customer service representatives. AI is not the first technology to bring change to the role—it’s evolved over the years to accommodate phone, email, chat, and social media—but the changes it is introducing are dramatic, with the autonomous agents taking on significant portions of the customer service load. Understanding how businesses can integrate agentic AI can make their customer service programs more efficient and more effective while improving customer satisfaction rates. Here’s what you need to know.
KEY TAKEAWAYS
- •AI agents are revolutionizing businesses in various applications across industries, from contact centers to financial services to healthcare and more. (Jump to Section)
- •Agentic AI receives human input and determines the best action to answer the question, complete the demand, or meet the need, making it useful for accomplishing tasks and acting as a personal assistant. (Jump to Section)
- •Limitations of AI agents include the potential for over-reliance on them and the risk of physical danger posed by using them in healthcare or self-driving cars. (Jump to Section)
What Is an AI Agent?
AI agents are task-driven virtual agents that replace or augment the work of human agents. Many can operate without human intervention for a wide variety of tasks. Automation backed by intelligence is a key part of AI agent functionality.
How Do AI Agents Work?
Agentic AI uses environmental and contextual clues to solve customer or individual problems. Think of how voice prompt systems work—a keyword in the customer’s spoken output generally acts as a trigger to determine a response. While traditional voice prompt systems tend to be robotic and limited, adding AI greatly increases the chances that the system will match the customer request with an accurate or appropriate response.
The AI determines what is needed and sets a series of tasks into motion. For example, it may request that items be ordered and shipped, that inventory be replenished, or that the situation be escalated to a human to address a more complex problem or serious customer dissatisfaction that the AI cannot resolve independently. This is accomplished with various technologies, including machine learning, generative AI, large language models, and neural networks. These advanced analytics-based systems are pre-trained on huge datasets and tested before being unleashed into the real world. Feedback helps improve accuracy over time.
Some autonomous AI agents are fairly simplistic and designed to accomplish basic tasks such as sending acknowledgment emails whenever someone fills out a form. Others incorporate historical data to make decisions or suggestions concerning the type of product the person may be calling about or a task that needs to be done. More advanced agents try to interpret needs and react in real time as a human agent would.
“Functions such as the user experience, form development, conversational interface development, API automation, intelligent document processing, mining, task mining, process design and execution, business rules management, and workforce management can all be enhanced with AI,” said Amardeep Modi, Vice President of Everest Group.
Key Features of AI Agents
AI agents are designed to fulfill different purposes, which means there’s a lot of variability of features among them depending on the task they’re meant to serve. Some of the most common features include the following:
- Self-Service: According to a recent global study conducted by Cisco, there is a link between customer satisfaction and effective self-service tools. With agentic AI, people can find what they are looking for without waiting for a rep to answer the phone or wading through a series of documents in a database.
- Autonomy: Agents are programmed to perform certain tasks without human intervention, approval, or supervision.
- Self-Improvement: As AI agents gain more experience, they can adapt their responses and actions to increase accuracy or understand context.
- Application Integration: Agents use APIs to access applications and carry out tasks. For example, they can open an email app to send data or an acknowledgment via email, open a calendar and book an appointment, etc.
- Multi-Step Tasks: Many AI agents are good at one repetitive task, but the latest generation has evolved to the point where agents can handle multiple talks. This might include taking orders and following them up with related tasks, like alerting shipping, acknowledging the order via email, and assigning follow-up tasks to others in the CRM system.
How Will Agentic AI Revolutionize Business?
It’s difficult to estimate the number of ways AI agents can transform a business, and more are being developed almost daily. To date, some of the most common applications include contact centers, financial applications, data collection and analysis, task and project management, personal assistance, and more.
Contact Centers
A recent Webex study found that only 25 percent of people were satisfied with their last contact center service experience, and 94 percent abandoned interactions due to poor experiences. Customer service applications for AI agents can improve on that. For example, the Cisco AI Assistant for Webex Contact Center leverages conversational intelligence and automation to enhance customer interactions, streamline issue resolution, offer more empathetic customer satisfaction, and enhance brand loyalty.
“Customer experience can make or break a brand,” said Jeetu Patel, Cisco’s Executive Vice President and Chief Product Officer. “In the next few years, a large majority of first-time calls will be handled by an AI Agent that will be just as interactive, dynamic, engaging, and personable as a human agent.”
Complex Task Assistance
New AI apps can handle complex tasks simultaneously, such as booking flights, hotels, and airport parking. Anthropic, for example, offers agents and agent development tools that access other applications and carry out a sequence of related tasks, including booking flights, scheduling appointments, researching online, and completing expense reports.
Financial Applications
AI agents are finding their way into banking and financial applications courtesy of AI startups and innovators like Snaplogic. The company helped Independent Bank Corp. of Michigan create AI agents to assist workers, automate processes for fraud detection, reduce IT help desk tickets by correctly handling inquiries, and make real-time adjustments to financial strategies based on evolving market conditions.
Data Collection and Analysis
AI agents are being used to find data on the web and from internal databases, forms submitted online, social media, and other sources. This eliminates immense manual labor in compiling data, combining spreadsheet data, and integrating data sources. AI is also used to slice, dice, crunch, bunch, and draw insights from data in conjunction with data science and analytics applications to expand their reach. For example, ChatGPT and other generative AI tools bring the internet into the realm of analysis.
Personal Assistants
AI agents can perform functions normally done by humans—for example, many of the tasks and services performed by personal assistants. Users can ask their phones or computers to take specific actions, like sending emails, booking flights, canceling appointments, or sending flowers. Auto-GPT, for example, is used by some to create personal assistants based on GPT-4.
Task Management
AI agents can help keep track of which tasks are completed, which are in progress, and which need to be done or redone. For example, BabyAGI creates autonomous AI-powered task management, and AgentGPT can create, complete, and learn from various tasks.
Crypto Applications
AI agents are being incorporated into blockchain technology. These agents can use cryptocurrencies to complete purchases and enhance their capabilities, opening up opportunities for agents to deal with financial transactions. How effective are they? In one public example, an AI agent convinced a venture capitalist to invest $50,000.
Software Coding
Some believe that generative AI (GenAI) can be used to develop software code, signaling the end of the software developer. However, initial results have been less than promising, and only 27 percent of GenAI users report using it to create software programs.
“ChatGPT is not reliable for software development,” said Michael Azoff, Chief Analyst at Omdia, who doesn’t recommend using GenAI for that purpose. “There are other tools out there specifically designed for coding. AI is not about replacing developers or other IT functions. It’s about augmenting them by providing useful tools.”
That said, agentic AI can help developers in other ways. For example, it can help compile software modules based on existing components, like compiling shopping cart and payment options into a new eCommerce application.
Driving
On the futuristic side, AI agents could someday be used in self-driving cars. The driver or vehicle manager could instruct the agent to take the car to a specific location or bring it to the garage for service. However, much work still needs to be done in image recognition, LIDAR interpretation, decision-making, and vehicle control.
Chat
While automated chat has been around for a while, AI is making it a more sophisticated experience by enabling it to respond to emotion, better understand context, and eliminate the more robotic aspects of traditional chat applications.
Healthcare
In healthcare, AI agents are being used for remote patient monitoring, freeing up nursing and medical staff and alerting them when something serious occurs or it is time for a checkup. Similarly, these agents can compile and summarize healthcare data for individuals and large groups. The resulting data analysis might raise the accuracy of diagnoses and promote better patient outcomes.
Manufacturing
The industrial sector is ahead of many other areas in deploying AI agents. Many operate as the software equivalent of an industrial robot, helping organize product assembly, transportation, floor management, data collecting and analysis, and workplace safety compliance.
For example, water heater manufacturer A.O. Smith harnesses AI agents from UiPath. Business Process Optimization Manager Diana Swain uses AI agents to extract, interpret, and process data from forms, PDFs, images, handwriting, scans, and checkboxes using UiPath Document Understanding. AI agents can recognize content, and pre-trained machine learning models add a higher level of intelligence, interpretation, and the ability to trigger actions based on content identification.
“We were having lots of document problems due to bad handwriting, documents written in different formats and platforms, and legacy and new applications being used for invoicing,” Swain said. “Document understanding has already freed up 7,200 hours per year that can be used for more strategic and fulfilling work.”
Limitations of AI Agents
While agentic AI can bring many benefits and a better experience, there are also a few potential downsides. Here are some of the most common:
- Overreliance (Use it or Lose it): If people delegate everything to AI agents, they may lose sight of their own capability to perform those actions, fail to pass those talents onto the next generation, and basically become so dependent on agents that nothing gets done when there is an outage.
- Malicious Acts: Nearly every science fiction movie with an AI plot has the AI going rogue or being infiltrated. If a nefarious insider or hacker surreptitiously changes the code, or the AI gets smart enough to change its own code, an autonomous AI agent could do things that might be seen as malicious.
- Corrupt and Insecure Models: The widespread use of AI agents can cause security and privacy issues. The models behind AI can be corrupted or hacked or, at times, provide misinformation. They might also violate privacy rules, and some users might use them in ways that open the organization to attack.
- Physical Safety: AI agents are putting lives on the line in healthcare and in self-driving vehicles, where one small error can have serious consequences.
How to Prepare for AI Agents in the Workplace
Some organizations may resist the presence of AI agents due to the risks they introduce, but AI agents are coming, and they’re destined to be deployed in many areas of work and life. The following tips can help you prepare:
- Implement Them Slowly: AI agents should initially be added where they can accomplish the most gain for the least cost. This will allow the organization to become comfortable with the technology and plan to implement it more broadly.
- Offer Staff Training: Personnel need to be educated on how to use AI agents, what the guardrails are, and how to stay in control.
- Define an Effective Use Policy: Drafting and implementing good policy, distributing it broadly and training staff on its use, and enforcing it organization-wide can prevent or mitigate many security and ethical challenges AI agents pose.
Bottom Line: Balance Productivity with Oversight for AI Agents
AI agents can replace humans in certain functions. They can augment human activity, eliminate drudgery, and complete tasks faster than humans–but like generative AI tools, they should always be viewed as a tool to augment human efficiency, not as a replacement. Businesses that embrace their use can benefit from their potential to revolutionize the workplace. However, they should be closely monitored to ensure they don’t stray from their intended purpose.
Read our article about the use of AI in contact centers to learn more about real world applications for this dynamic technology.
