Maybe your team is dealing with a surge in case volume, but it is stretched thin. Or you would work to provide 24/7 support, but tight budgets make it difficult. Or you are under pressure trying to reduce response time, yet your customers keep expecting more in less time. But how do we overcome these challenges and make the most of them to boost productivity? That’s where AI agents come into play.
AI agents are no longer a futuristic term. They are woven into the fabric of IT business solutions today. AI agents are reshaping every business, from autonomous bots defining the manufacturing sector to virtual assistants streaming daily operations.
In this blog, we will understand AI agents and look into some applications of AI agents in real-world.
What are AI agents?
AI agents are intelligent systems that help automate tasks with little to no human intervention. They are designed to make decisions, adapt to new situations, and learn from experiences. They are used in various industries to interact with customers, respond to queries, and resolve issues like human agents.
They can use tools, plan steps, self-correct errors, collaborate with teams, and reason through issues with minimal human oversight.
These advanced abilities allow AI agents to work at more profound levels of specialization, expanding businesses’ use cases. With the help of multi-agent systems, each individual AI agent collaborates with other AI agents across departments, performing tasks sophisticatedly.
Difference between AI agents and AI Copilots
AI agents seem to overlap with other AI-powered technologies, such as AI copilots. Both AI-powered technologies naturally respond to user queries and simplify processes using LLMs and NLP.
However, the major difference is that copilots are limited in execution and action compared to AI agents, which act more advanced than their peers.
Levels of independence
AI copilots are designed to work alongside users, assisting them when required. Some copilots also respond proactively to customer queries. AI agents can operate silently, executing stand-alone entities running in the application’s background without user input.
For example, when a warehouse manager uses Copilot in inventory management, it suggests restocking of raw material based on past sales trends. On the other hand, AI agents automatically monitor stock levels, forecast demand and automatically place orders with suppliers. By automating stock replenishment with autonomous agents, you can ensure optimum stock levels and high profitability.
Coordination:
AI agents and copilots can work in harmony with the latter acting as an interface for agents. A user can interact with the copilot to initiate a task. When the task exceeds the copilot’s immediate capabilities, it triggers an AI agent. The agent executes the task and shares the final response with the user via the copilot.
Specialization:
The copilots and AI agents can be customized to utilize specific features and functions. However, AI agents go a few steps further in managing more complex tasks within their specialty. Both AI tools offer significant value when combined as part of multiagent systems, allowing teams to choose between helpful hand or hand-off automation.
Applications of AI Agents in Real-World
AI agents have several applications that help businesses automate processes, drive sales, and enhance customer experience. Here, we will examine some of the applications of AI agents in various business vertices.
Applications of AI agents in Sales:
AI agents provide innovative solutions that enhance efficiency in all areas of sales processes. From lead generation to customer service, they handle everything. AI agents analyze large data sets and identify potential leads based on customer engagement, behavior, and demographics. They use predictive analysis and prioritize high-quality leads, saving time by focusing on qualified prospects.
Customer engagement: Enhancing customer engagement is one significant application of AI agents in sales. Based on user interactions over the web, AI agents deliver tailored content and understand preferences based on purchase intent. They send personalized emails and messages to customers, keeping them in the loop about the products and services.
Scaled Outreach: With external data and CRM, AI agents autonomously build personalized communications, gather information from prospects, and answer nuanced questions regarding the product or service to drive sales.
Sales Follow-up:
Manual monitoring and traditional follow-up methods can be time-consuming and result in frequent opportunity losses. AI agents simplify this process by sending automatic follow-ups to customers based on their recent interactions. An AI agent can identify the most effective timing and process the follow-up by analyzing information from past communications, ensuring no opportunity slips.
Applications of AI agents in HR:
AI agents make HR processes more efficient and simplified. They automate the recruitment process through candidate screening, selection, and onboarding. They can compare resumes for the applied job role, providing an efficient and fast way to switch between candidates in a fraction of the time.
In addition, AI agents can access the calendars and suggest a time for interview scheduling when both parties are available. As the candidate gets selected for the interview, the onboarding process is also automated with essential paperwork, providing training materials and policies at their own pace.
AI agents also build interactive onboarding for newly joined employees, keeping them engaged and comfortable with the workspace. Moreover, AI agents keep track of the employee’s progress and provide insights on training areas, allowing HR to deliver essential support and resources to help the employees reach predictive approaches to work while achieving satisfaction.
Another application of AI agents in HR is that they simplify payroll processes and help administration by performing regular compliance checks and automating payroll processes precisely, leaving no room for human errors.
Applications Of AI Agents In the Supply Chain:
AI agents play an essential role in logistics and supply chain management. They analyze data based on historical data in the database, market trends, and other relevant factors to predict future demands for services or products.
This allows businesses to optimize inventory levels and reduce the likelihood of stockouts and overstock. AI agents also keep track of stock levels and maintain optimal stock levels, which is essential for production planning, timely procurement, and improving customer satisfaction.
AI agents also enhance transportation and delivery optimization by analyzing real-time data from traffic patterns and planning delivery schedules to the most efficient routes. They also assist fleet management by analyzing vehicle performance data and predicting maintenance needs. With these capabilities, AI agents help reduce downtime, labor costs, and efficiency.
These are some of the applications of AI agents in various industries. Do you want to leverage the power of AI agents for your business? Enter Digital Clerx, Saxon AI’s next-gen enterprise verticalized agents accelerator to empower your teams with more autonomous process automation. Our agents work alongside your team and give them their time back to focus on high-value tasks while efficiently handling repetitive tasks.
Want to see how AI agents can work for your business in real-world scenarios?
Book free live demo of Digital Clerx.
