Almost every business jumped on the generative AI bandwagon with their advanced chatbots and assistants. The problem with LLMs is and will always be their reactive nature as they depend on a human to write a prompt. With the introduction of agentic AI for enterprise use cases, artificial intelligence can now serve as an autonomous worker focused on achieving specific goals.

  • Gartner has found out that almost 40% of enterprise apps with have AI agents by 2026. (Source)
  • A study has revealed that 88% of US firms want to increase their AI budgets to adopt agentic AI. (Source)
  • PwC conducted an AI agent survey and discovered that 66% of organizations that have adopted agentic AI witnessed improvements in productivity. (Source)

AI agents represent a major paradigm shift in the domain of artificial intelligence and empower businesses to move beyond traditional LLMs. Enterprises can unlock new improvement in operational efficiency with agentic AI and create the foundation for completely autonomous business operations. Understanding how agentic AI works in enterprises and exploring the use cases of AI agents in business will help you make the most of their capabilities.  

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Unraveling the Utility of Agentic AI for Enterprise Applications

The usage of agentic AI in enterprises primarily focuses on deploying agents with reasoning capabilities that can execute multi-step workflows and coordinate with other agents and systems. You must know that the benefits of agentic AI for business extends beyond automation of single tasks. On the contrary, AI agents help with end-to-end process execution with zero to minimal human intervention.

While agentic AI offers promises for better productivity, it increases complexity that existing enterprise platforms cannot handle. Agentic AI systems include multiple agents that work on different functions for a single request. The problem is that only a few companies are actually ready to embrace AI agents. Businesses can capitalize on the full potential of agentic AI only by rethinking their approaches to data, systems, and governance. 

Enterprises have to operate with a new architecture to adapt to the new requirements that come with agentic AI. The three-layer architecture will focus on following areas,

  • Orchestration 

The orchestration layer will serve as the command center of all agentic system operations. It is responsible for managing multistep workflows, execution controls and context handoffs between agents in an application.

  • Observation

Enterprise agentic systems rely on the observation layer for analytics and obtaining real-time visibility. The observation layer works on metrics, audit trails and logs across agents, workflows and infrastructure. 

  • Governance

The uses of agentic AI for enterprise applications must also embrace governance to ensure seamless improvement in productivity. Governance layer in enterprise agentic AI applications ensures that agents get consistent and governed access to structured and unstructured data for different domains.

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Identifying the Areas Where Enterprises Can Use Agentic AI

The ideal scenarios in which enterprises can adopt AI agents should include multistep workflows and demand reasoning along with coordination across different systems. Agentic AI has already started delivering value benefits for enterprises across different industries.  

1. Customer Experience 

AI agents have been reinventing customer experience on all fronts with radical improvements. Agentic AI not only transforms the frontend but also the backend that powers customer support interactions. Companies are implementing agentic AI to redefine the backend in a way that aligns perfectly with the frontend experience. 

The use cases of AI agents in customer service range from autonomously routing service requests and detecting issues before they escalate to generating content. However, agentic AI can only generate repetitive and scalable outcomes by reshaping the frontend and backend systems driving customer experience.  

2. Marketing 

The benefits of agentic AI tools in the domain of marketing have gained a lot of traction in enterprise environments. As a matter of fact, AI agents have emerged as new intermediaries between brands and their customers. You must have noticed that consumers and B2B buyers rely on AI tools to get product recommendations, research, and comparisons.

The involvement of AI in marketing reduces the time between discovery and decision, thereby leaving little room for brands to influence their consumers. However, leading marketers will try to adapt through optimization of their content for large language models. The new digital marketing strategy of enterprises will work with the assumption that an AI agent is their first audience.

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3. Banking and Financial Services

Agentic AI can play a pivotal role in reducing friction in service, onboarding, financial planning, and compliance in financial services. Conversational agents can help bank customers in resolving their issues, provide personalized guidance, and assist with money transfers. 

The financial services industry is one of the best examples of why enterprises should modernize their platforms and data. Modular frameworks that are considered as industry standards will support the acceleration in a shift towards AI agents. At the same time, financial services companies must also facilitate scalable access to structured and unstructured data for better personalization. 

4. Retail and Commerce 

Enterprises can also loop up to AI agents for reshaping the path between products and shoppers. Agentic AI systems can help customers in discovery, research, and comparison of products without using traditional websites and marketplaces. As a matter of fact, AI agents will be responsible for driving one-fourth of ecommerce sales in the United States by 2030. 

The advantages of agentic AI for enterprise use cases in commerce will redefine the shopper journey. On the other hand, retailers will have to pay attention to their customers and the agents working on their behalf. Enterprises will have to figure out the ideal places where they can participate in agentic commerce and maintain their visibility to agents and humans.

5. Sales 

One of the prominent areas in enterprise operations where you cannot ignore AI agents is sales. You will find many use cases for agentic AI in different stages of the sales lifecycle of a business. AI agents can redefine lead generation and prospecting, operational planning and visibility, and promote high-velocity guided selling.

The only way for enterprises to use agentic AI for their sales processes requires identifying high-value use cases. On top of it, enterprises must also reimagine processes and refine their data to transform the potential of AI agents into performance. If implemented in the right way, AI agents can make the job of frontline sellers a lot easier while enhancing resilience.

6. ERP Operations 

The applications of AI agents in transforming ERP operations in an enterprise also deserve a spot in a guide to AI agents for enterprises. You can see the value of agentic AI for business ERP in the way agents transform passive platforms to dynamic engines capable of autonomous decision-making and execution. Employees can work with AI agents and manage platforms that offer facilities for rerouting workflows and initiating decisions.

The enterprise operations that will notice immediate gains include core finance and planning processes. It is also important to know that many companies are still in the early stages of experimenting with AI agents for ERP operations. The common roadblocks for adoption of AI agents in enterprise operations include limited internal skills, unclear operating models and data quality issues.

Where Will Agentic AI Generate Business Value for Enterprises?

Agentic AI systems can create business value in many ways, especially with growth opportunities for some industries. You can notice agentic commerce gaining momentum and slated to become one of the fastest growing areas in ecommerce. AI agent also ensures automation of coordination work between different systems, thereby transforming labor costs into software expenses. Most important of all, agentic AI also accelerates decision making, improves operational efficiency and enhance customer experiences with more personalization. The combined impact of these use cases of AI agents will have a positive and long-term impact on businesses.

Final Thoughts 

The examination of different ways in which you can use agentic AI for enterprise applications proves that agentic AI is still in the latent stages. AI agents have the power to ensure autonomous automation of traditional enterprise workflows across various operations. Businesses must recognize the fact that agentic AI will deliver more value by redesigning complete workflows rather than automating specific tasks. Learn more about agentic AI and the best practices to incorporate it in enterprise operations now.

FAQs

What are the top agentic AI platforms designed for enterprise use?

The top agentic AI platforms designed for enterprise use include Microsoft Copilot Studio, Salesforce Agentforce, and IBM WatsonX Orchestrate. Microsoft Copilot Studio is the top pick for companies that depend heavily on Microsoft 365, Teams and SharePoint. Salesforce Agentforce serves an ideal choice for companies involved deeply in the Salesforce ecosystem.

Which companies offer agentic AI solutions tailored for large businesses?

Google, IBM, Microsoft and Salesforce are some of the companies offering agentic AI solutions for large businesses. These companies offer ecosystem-native AI platforms, allowing businesses to embrace AI agents with limited friction. 

How can agentic AI improve workflow automation in enterprise settings?

Agentic AI can improve workflow automation in enterprise settings by focusing in intelligent automation rather than rules-based processes. AI agents don’t just respond to prompts and take specific goals and break them into subtasks. Subsequently, agents process the unstructured data and execute multistep actions by using different tools to achieve their goals.

What are the top agentic AI certification programs available online?

The Certified AI Agents Manager (CAIAM)™ certification program by Future Skills Academy is the best agentic AI certification program. It is a self-paced certification course that offers a deep dive into the world of agentic AI. You will get the opportunity to learn more than the fundamental concepts of agentic AI in this certification program and build hands-on skills with the guidance of experts. 

About Author

James Mitchell is a seasoned technology writer and industry expert with a passion for exploring the latest advancements in artificial intelligence, machine learning, and emerging technologies. With a knack for simplifying complex concepts, James brings a wealth of knowledge and insight to his articles, helping readers stay informed and inspired in the ever-evolving world of tech.