Agentic AI in Enterprise Workflows: Real-World Use Cases

In the midst of the Fourth Industrial Revolution, where the boundaries between the physical, digital, and biological worlds are rapidly blurring, and a fast-paced business landscape continues to accelerate, Tom Coshow, Senior Director Analyst at Gartner, says: “Organizations have long wanted to promote high-performing teams, improve cross-functional collaboration, and coordinate issues across team networks. Agentic AI has the potential to perform as a highly competent teammate by providing insights from derivative events that are often not visible to human teammates.”

In their 2025 Top Strategy Technology Trends [1], Gartner predicts that by 2028, 33% of enterprise software applications will include agentic AI, and at least 15% of day-to-day work decisions will be made autonomously through agentic AI, up from 0% in 2024. With its ability to analyze derivative events and offer insights that human teams may miss, agentic AI has the potential to transform the way we approach teamwork, decision-making, and collaboration. 

Keep reading to explore how agentic AI is reshaping the enterprise workflows, making businesses smarter, faster, and more efficient.

What is Agentic AI? 

Agentic AI moves beyond passive tools to autonomous, decision-making systems capable of executing complex tasks. Unlike traditional automation, which follows predefined rules, agentic AI has the ability to sense its environment, plan actions, use external tools, and make independent decisions while adhering to safety guidelines.

As Bryan Goode, Corporate Vice President at Microsoft, mentions in his recent LinkedIn post [2], agentic AI is already adding value in enterprise workflows. New capabilities like “agent flows” and “reasoning” in Copilot Studio are enabling AI agents to perform more complex tasks — such as aggregating and prioritizing product feedback from platforms like Reddit or analyzing market research data to optimize campaigns. These advancements help organizations build richer automations that enhance efficiency and decision-making.

Organizations are incorporating agentic AI into AI assistants, software platforms, IoT devices, and robotics, unlocking new efficiencies. However, with autonomy comes responsibility — organizations must establish strong governance, ensure data quality, and mitigate risks such as unmonitored AI proliferation and security threats. As agentic AI continues to evolve, businesses that strategically implement and manage it will gain a significant competitive edge.

Benefits of Using Agentic AI in Enterprise Workflows

“AI agents will become the primary way we interact with computers in the future. They will be able to understand our needs and preferences, and proactively help us with tasks and decision-making.” — says Satya Nadella, CEO of Microsoft.

A McKinsey study [3] reported that banking, high tech, and life sciences are among the industries that could see the biggest impact from AI as a percentage of their revenues, with potential annual value ranging from $200 billion to $600 billion across different industries.

Agentic AI is redefining enterprise workflows by moving beyond simple automation and rule-based AI. Unlike traditional conversational AI, which is often limited to predefined responses, agentic AI can autonomously make decisions, adapt to changing contexts, and handle complex, multi-step workflows. This significantly reduces human workloads while enhancing efficiency, collaboration, and user experience.

Figure 1: Traditional workflows vs. agentic AI workflows 

Source: OneReach.ai

Increased Efficiency via  Autonomous Decision-Making

One of the biggest advantages of agentic AI is its ability to increase efficiency by making independent decisions. For instance, if an employee needs help with a password reset, an AI agent can proactively guide them through solutions — offering alternatives like resetting multi-factor authentication or connecting with a live agent only when necessary. This streamlines IT support and minimizes human intervention, saving time for both employees and service desk agents.

Enhanced, Seamless Human-AI Collaboration

Agentic AI fosters seamless collaboration by interpreting nuanced language and multi-agent conversations. Unlike traditional AI, which may struggle with complex requests, agentic AI understands context, solves problems autonomously, and reduces repetitive tasks for employees — allowing them to focus on more strategic and creative work. Agentic systems also rely on Human-in-the-Loop (HitL),  a powerful tool that allows people to pick up tasks when agents need help and contribute to ongoing improvements to how the system learns and behaves. 

Improved Real-Time Analysis and Adaptation

Agentic AI has the ability to dynamically adjust its approach based on real-time data. For example, when creating a knowledge base article on software troubleshooting, an AI agent can generate an outline and ask follow-up questions to refine the content. This adaptability ensures that tasks are completed with full context and accuracy.

Elevated Customer Service and User Experience

AI Agents improve customer service by handling routine inquiries, assisting support teams, and delivering personalized recommendations. In e-commerce, for example, an AI assistant can instantly retrieve order details, suggest relevant products, and reduce wait times by answering FAQs — enhancing the overall customer experience (CX).

Increased Productivity and Cost Savings

By automating complex decision-making, agentic AI streamlines operations across various industries. A McKinsey study [3] estimated that AI-driven automation could contribute over $400 billion in productivity gains across sectors, such as supply chain management, customer service, and financial reporting.

As businesses navigate an increasingly agentic AI-driven world, those that strategically implement agentic AI today will gain a significant competitive edge — unlocking greater efficiency, smarter decision-making, and seamless automation.

Real-World Use Cases Designed with OneReach.ai 

Learning sciences

A leading US-based learning sciences company partnered with OneReach.ai to transform customer service through agentic AI-led automation. The solution involved building a single chat entry point for dozens of customer segments across various web locations.

By implementing agentic AI with key technologies such as Text-to-Speech (TTS), Speech-to-Text (STT), intent recognition, a native voice stack, conversational reporting and analytics, and integration with the Salesforce agent UI and CRM, the company achieved a 45% reduction in chats transferred to human agents.

Figure 2: Project results 

Source: OneReach.ai

This strategic deployment not only enhanced customer experience and reduced operational costs but also demonstrated the power of AI in streamlining workflows across complex, multi-segment environments. With plans to expand omnichannel integration, the company continues to evolve its use of AI to further enrich customer interactions.

Retail

A Forbes-recognized company teamed up with OneReach.ai to implement an AI-driven communication strategy. This transformation included deploying AI agents to handle phone calls, integrating SMS for outbound marketing, and creating a new customer contact center.

Figure 3: Project results over the course of one year

Source: OneReach.ai

The keys to success lay in the seamless integration with legacy systems, overcoming technical debt, and focusing on customer experience. Future expansions are planned to further leverage AI solutions in internal service desk capabilities, enhancing point-of-sale options, enabling omnichannel text-to-pay, and integrating deeper with customer relationship management (CRM) systems to further improve the customer experience.

Telecommunications

A leading telecommunications provider turned to OneReach.ai in order to enhance its customer authentication process with an AI agent designed to replace traditional, time-consuming manual verification. 

The new agentic AI solution allowed customers to authenticate using their account credentials, significantly reducing human agent involvement while maintaining high security standards. This shift resulted in impressive improvements across multiple regions, with notable increases in Net Promoter Scores (NPS) and resolution rates. 

Figure 4: AI agent implementation resulted in significant improvements across multiple regions for the period Jan 2024–Oct 2024

Source: OneReach.ai

The use of OneReach.ai’s Generative Studio X (GSX) enabled rapid development and deployment of AI-driven skills, allowing the organization to iterate quickly and address high-impact use cases. As the organization looks to expand its AI capabilities further, including sales functionalities and deeper AI agent orchestration to enhance customer interactions and efficiency in 2025 & beyond.

Creating Smarter Business Workflows with Agentic AI

Agentic AI is transforming industries by fostering smarter decision-making and breaking down old workflows. But as Steve Jobs famously said, “Great things in business are never done by one person. They’re done by a team of people.” AI agents bring the most value when they are orchestrated together and collaborate with each other, offering greater control over the lifecycle and execution of business processes.

By orchestrating AI agents across an organization, businesses can build a dynamic, collaborative environment where AI works alongside people, constantly evolving and optimizing processes.

OneReach.ai’s GSX platform simplifies AI agent deployment and ensures seamless integration with existing IT tools and systems, enabling real-time AI Agents orchestration for optimal performance. It empowers organizations to model, implement, operate, monitor, and optimize their long-running processes.

Sources:
[1] Gartner Top 10 Strategic Technology Trends for 2025 

[2] LinkedIn, Bryan Goode, Corporate Vice President at Microsoft

[3] The economic potential of generative AI, Mckinsey Digital