AI Agents for Business: The Future of Automation

AI agents for businesses use advanced technologies such as machine learning, Natural Language Processing (NLP), domain-specific large language models, and Foundation Models (FMs) to execute tasks and solve problems. AI agents can also leverage other software platforms, collaborate with other agents, and learn from their experiences to improve their performance.

Unlike typical business automation workflows that need to be specifically designed using predefined rules, intelligent agents use a reasoning process that is similar to how humans think to handle ambiguous requests, understand the context of the task, weigh and choose the right option, and take the appropriate action. Many AI agents also have multi-modal capabilities that allow them to interact with a wider range of inputs, including text, voice, images, and video.

AI agents also known as autonomous agents can help organizations automate many tasks across departments, including IT, finance, marketing, logistics, and operations. As agentic AI continues to evolve, these agents will shift from task execution to more autonomous decision-making to proactively solving business challenges without human input. Benefits include:

• Operational efficiency: AI agents for small businesses and enterprises can help teams stay focused on high-value tasks by allowing AI to handle time-consuming repetitive tasks, improving worker performance by nearly 40%.
• Cost savings: By offloading high-volume, time-consuming complex tasks to AI agents, businesses can reduce their labor costs while eliminating costly manual errors. For example, Gartner predicts that AI will help contact centers reduce their costs by $80 billion within the next two years.
• Enabling data-driven decisions: AI agents for business can analyze vast datasets in real-time to uncover patterns and insights to power use cases like financial forecasting and supply chain improvements.
• Improving the customer and employee experience: AI agents can provide customers with personalized, always-on customer service, improving customer service metrics including CSAT scores. On the employee side, AI agents enhance the Employee Experience (EX) by reducing friction in day-to-day tasks. From quickly answering HR or IT questions to automating routine workflows, AI agents empower employees to get what they need—when they need it—without delays. This leads to higher productivity, less frustration, and a more engaged workforce.

For employees, AI agents can quickly answer questions about company policies, reset passwords, or help take busy work off their hands, reducing frustration and improving workplace morale.

Intelligent agents are incredibly versatile, making them a valuable addition to almost every business department. Here are just a few AI agents examples where AI is already making an impact.

1. Employee Support and HR

Similarly, using agentic AI in HR can improve the employee experience (EX) by making it easier for employees to engage with departments like human resources.

HR departments use AI EX agents to handle routine employee inquiries and tasks, freeing the HR team to focus on strategy and implementation. For example, AI agents work with employees to get answers about their benefits, request vacation time, file expense reports, and make changes to their tax withholdings.

Instead of waiting days for a response, an AI agent can answer their questions and make changes on the spot, allowing the employee to get back to work faster. AI agents can also help new hires onboard faster by providing information about company procedures, scheduling orientation meetings, collecting required documents, and provisioning equipment.

3. IT Support and ITSM

One area where employees need help most is tech support. By leveraging agentic AI in ITSM it can take care of many common support requests, such as password resets, software or hardware requests, and technical troubleshooting.

These agents are connected directly to the IT organization’s backend systems, allowing the agent to make a change or approve access without requiring IT staff intervention. This agent assist capability reduces resolution times and minimizes employee downtime, while freeing the IT team to focus on cybersecurity, provisioning resources, and planning technical initiatives.

In addition, in ITSM, AI agents proactively monitor network performance to detect issues and take action on the fly. For example, an agent that detects a storage issue can procure additional cloud storage or move data from an on-premise system to cold storage to free up space.

In another use case of AI in the IT industry, an IT agent might automatically restart services or apply known fixes for common issues. If it can’t fix the problem, it can then escalate the issue to IT staff with a complete log of all the actions it attempted so IT can focus on more advanced remediation strategies.

2. Customer Support

One of the leading applications for AI agents is the customer experience (CX), with AI CX agents able to handle customer inquiries 24/7 for a business across its website, mobile app, social media, and messaging platforms. Rather than make a customer wait for the next available operator, these agents can instantly improves customer relationships by greet the customer, answer account questions, tracking orders, and make product recommendations.

AI can also monitor a customer’s words, mood, and sense of urgency to predict their likelihood to churn. The AI agent service can either take action, such as offering a discount or elevate the issue to a live representative who can work with the customer to alleviate their issue.

By allowing AI agents for customer service to analyze customer data handle high-volume customer engagements, it makes human agents more available to handle the high-stakes customer interactions that can keep customers happy, increase customer lifetime value, and reduce poor reviews.

4. Software Development

AI agents are changing software development by automating code, detecting bugs and suggesting fixes in real-time. These development agents can help with code generation, documentation, and even test case creation to speed up release cycles and reduce human error.

By integrating with version control systems and development environments, Agentic AI can flag security vulnerabilities or performance bottlenecks before they hit production making engineering teams more efficient and codebases more reliable.

5. Sales Support

Long before a top salesperson can seal the deal, many hours must be spent engaging prospects and qualifying leads. AI sales agents can work as a virtual assistant that guides prospects through the funnel so sales staff can focus on closing. For example, when a potential customer fills out a website form or requests a demo, an AI sales agent can immediately follow up via email or chat to provide more information, answer common questions, and gauge the prospect’s interest level.

These agents can also tap into a business’ CRM data, the prospect’s browsing behavior, and publicly available data to tailor their outreach and determine a lead score. Leads that meet specific criteria can then be automatically forwarded to human salespeople for high-touch follow-up, while others may continue to be nurtured by the AI sales agent until ready to convert, keeping sales teams focused on their most promising opportunities for conversion.

6. Marketing Automation

Marketing teams leverage AI marketing automation agents to supercharge their efforts by analyzing customer behaviors to segment audiences, target ads, and create hyper-personalized campaigns.

AI agents for enterprises and small businesses alike allow lean marketing teams to deliver the right content to the right people at the right time. As the agent learns more about each customer segment, it can adjust ad buys, timing, and creativity in real time to optimize clickthrough rates.

For example, an agent can personalize email content and send times for each subscriber to maximize engagement. It can then dynamically suggest products or content based on the most likely next step of the subscriber, boosting cross-sell and upsell opportunities.

7. Logistics

An AI logistics agent can leverage predictive analytics to analyze historical sales, market trends, and third-party data like weather and social media sentiment to forecast product demand. These agents can then help businesses optimize inventory levels by automatically ordering the right stock or redeploying products from one location to another.

AI logistics agents can also monitor supply chain data in real time to alert managers about a potential disruption, such as a supplier delay so that the logistics team can find another supplier.

AI agents are coming soon, with Gartner predicting that AI agents for enterprises will be found in a third of software applications in the next three years, up from 1% in 2024, while enabling 15% of day-to-day work decisions to be made autonomously.

Enterprise AI agents can already automate many routine tasks across an organization. As agentic AI continues to advance, AI agents will proactively look for opportunities to fix user issues, launch campaigns, order materials, and order equipment upgrades. In addition, expect to see greater use of multi-agent systems where different agents collaborate and communicate with each other, not just users.

Best Practices for Deploying AI Agents

To get started with AI agents, pinpoint the tasks or processes that consume significant time or resources and could benefit from automation. Engage stakeholders from different departments to uncover pain points where intelligent agents might help. Prioritize use cases that are high-impact but feasible, such as IT support, and define the KPIs you’ll use to measure performance.

Once you select your use case, work with an enterprise agentic AI platform partner that can offer domain-specific AI agents so you can accelerate deployment and achieve value faster. Your partner will be able to help you:

• Collect, clean, and label domain-specific data to tune the AI agent
• Maximize pre-trained models for your domain, in addition to conducting any additional training based on your specific data
• Connect the AI agent to your data platforms and systems so it can access and update information as needed
• Test and iterate the AI agent to ensure accuracy and performance
• Roll out and scale use of the AI agent, which may include user training and gaining employee buy-in

Choosing the Right AI Agent for Your Business

Not all AI agents are created equal. Here’s what to look for in your agentic AI agent evaluation process:

• AI-native architecture: Look for AI agent solutions that are built natively on AI rather than retrofitted from traditional automation tools. This will provide higher accuracy, lower latency, and better performance, ensuring tasks are completed efficiently and cost-effectively.
• Platform agnosticism: This will allow AI agents to scale across diverse environments, including hybrid, private cloud, and on-premises systems while maintaining strong data governance.
• Universal interface across heterogeneous systems: The AI agent platform should provide a universal interface across diverse enterprise systems to ensure smooth workflows across different AI tools and platforms.
• Industry-specific agents: AI agents should be trained for industry-specific use cases like finance, healthcare, and government to ensure higher accuracy and compliance.
• Proactive and autonomous interaction: The most advanced AI agents go beyond reactive responses to engage proactively and complete tasks autonomously with minimal human input.
• Security and compliance frameworks: Enterprise AI agents should adhere to robust security, reliability, and privacy standards to ensure compliance with evolving cybersecurity requirements.

AI agents will lead the next era of digital transformation by helping businesses elevate the customer and employee experience, increase productivity, and transform operations. To experience how AI agents can improve in your business productivity, Book a custom AI demo today.