AI Agents: What Businesses Should Know and How to Leverage Them

One of the most exciting parts of the recent advancements in artificial intelligence (AI) is what it means for the future of work. Up until now, all work has been performed mostly by humans with some automation, particularly in areas like manufacturing. With its latest advancements, AI is beginning to tangibly contribute to work, alongside humans. AI agents can complete tasks just as humans do and continue to become more advanced.

As organizations seek to augment their workforce with AI, it’s crucial to understand the capabilities of AI agents and how to implement this technology to benefit its key stakeholders—customers and employees. To stay ahead in the AI race, companies should start planning and building their AI agent frameworks now to bear the fruits of productivity gains, cost savings, and enhanced capabilities, which will likely be substantial.

Defining AI Agents

AI agents come in a variety of different forms. First, there are the more traditional AI agents that assist employees and CX leaders. For example, in the customer service industry, AI agents monitor every customer service interaction historically and augment human agents as necessary in real time. The AI has been trained on organization- and industry-specific data, including those past interactions that created optimal outcomes, so it can guide a human agent through an interaction, suggesting next best actions like what to say to a customer to lead the interaction to a successful conclusion. The AI agent can be embedded within an employee’s desktop interface, interacting with an employee through an ongoing chat conversation.

This type of AI can also serve as a business leader’s personal data analyst, monitoring business activities, spotting trends, and pinpointing areas for improvement. This effectively makes running a business more proactive, presenting leaders with critical insights and recommendations, rather than reactive, where leaders have historically had to search for insights and instigate actions manually.

AI agents can be trained to understand and speak just like human employees. This makes chatbots far more accessible and useful to an organization’s customers, sometimes making them indistinguishable from human employees. Combined with the highly effective training data from industry-specific CX data, this transforms self-service, enabling customers to resolve issues easily on their own. By offloading some of the work to bots, human employees can focus on higher-value, relationship-building work.

How AI Agents Achieve Autonomy

Gartner defines an AI agent as “a more advanced system that not only automates tasks but also possesses a degree of ‘agency,’ meaning it can operate autonomously, make decisions based on the data it processes, and learn from its experiences.”

One of the challenges still limiting AI agents is the ability to complete workflows across the multiple systems that may support an interaction. A human employee completing a task will often need to work across different systems of information. For example, if the employee is trying to answer a customer question, the answer might need to come from a different department in the organization. That employee can call the other department or open a different application to find the answer. The growth of cloud-based platforms makes this process much easier for AI agents. Cloud platforms consolidate information from across an organization and enable easier data sharing across teams.

Another potential challenge to autonomous AI agents is data security. Some organizations might not trust an AI agent to have access to unlimited information across the organization. Depending on the AI agent and how it was built, some AI agents could generate inaccurate or inappropriate information. This is especially critical if an AI agent can’t transfer a task to another AI or human agent when it doesn’t have the answer, so instead it makes up an answer. There have been several stories in recent months of chatbots for big name brands generating incorrect information. First, AI agents need to use purpose-built AI, trained on industry- and organization-specific data. Second, an AI agent needs to have the ability to know when it doesn’t have the answer to something and transfer to another agent or employee.

Fostering the Human and AI Partnership

Research from IBM found that 25 percent of companies are adopting AI because of labor shortages. AI agents are powerful tools to augment the workforce, filling labor gaps and supercharging employees.

As AI advances, AI agents could be seen as digital employees. To what extent they are considered employees will ultimately be up to businesses and how advanced these AI agents become. Regardless of an AI agent’s employment status, humans will work alongside AI. Furthermore, human agents will begin to take on new roles overseeing AI agents, including transferring skills to AI agents. Humans will begin guiding AI agents, giving them pointers during tasks to optimize their outputs. This will forever change the relationship between humans and technology into one that is much more collaborative.

How Organizations Can Implement AI Agents

Organizations should consider the following steps to ensure successful AI agent implementation:

• Consolidate operations onto a single cloud platform. This breaks down data siloes and enables AI to learn faster and perform better.
• Use purpose-built AI. AI should be industry-specific and organization-specific to ensure accurate and brand-appropriate outputs.
• Establish guardrails. Organizations need to define AI agent roles and set parameters on what they can access and what functions they can perform. Additionally, there should be human oversight, constantly monitoring to ensure AI agents are behaving appropriately.
• Create a strong change management plan. Organizations need to educate employees on new technology, especially if they will work alongside it, as with AI agents.
• Make it a cross-departmental initiative. AI implementation requires input from a variety of internal stakeholders, including CX, IT, HR and more. This ensures that AI implementation considers all parties involved and establishes a cross-departmental team for AI oversight.

AI agents have the potential to transform the way we work. The true potential in developing AI agents is not in automating individual tasks but in creating intelligent ecosystems that can automate entire workflows. It’s up to businesses to figure out what role these AI agents will play in their organization and how much autonomy they will have. Organizations looking to implement AI agent technology should seek a trusted AI vendor with industry expertise and purpose-built AI, trained on industry-specific data and built with the proper guardrails for security and brand constitution. Understanding the underlying technology is a big step to demystifying AI agents and speeding up the process to realize the immense benefits they offer. 

Barry Cooper is president of the CX Division at NICE. He is responsible for sustainable customer success across all customer-facing operations, including sales operations, professional services, customer support, and cloud operations.