AI Agents in Enterprise: How Will They Change the Way We Work?

Kathy Pham, vice president of AI at Workday, offers insights into AI agents and their influence on the workplace. She explains the concept of AI agents and their future implications for work, and provides practical guidance for leaders.

Kathy Pham January 28, 2025

In this article we discuss:

As AI systems become more sophisticated—capable of learning, memory, and acting independently to complete tasks—we are presented with new opportunities to enhance how work gets done within our organizations, especially our understanding of individual roles, their specific tasks, and how to personalize experiences. 

We conducted a global study revealing that 83% of professionals familiar with AI believe it will augment human capabilities, leading to increased productivity and new forms of economic value. This sentiment underscores a growing recognition that the future of work lies in how we use AI to elevate human potential.

One of the most exciting aspects is the evolution of agentic AI, commonly referred to as AI agents. In this article, we dive into AI agents, exploring what they are, how they’re reshaping the future of work, and how leaders should be thinking about leveraging them in their organizations. 

What Are AI Agents?

Let’s start by defining AI agents. AI agents are systems that perceive details of the surrounding environment, process and reason the next steps, and execute on those steps to achieve specific goals. They can even learn from their experiences, storing those learnings in memory to improve future iterations. 

This technology allows us to move beyond analyzing data and making predictions to executing tasks autonomously, combining agents and people to fulfill complex processes. It enables enterprise technology to anticipate user needs and proactively completes tasks. 

For users of enterprise systems, this means a simple, personalized experience. Behind the scenes, AI agents break down complex processes, consider individual context, and coordinate tasks to solve challenging business problems. This level of personalization is unprecedented, adapting to user expertise and specific organizational needs. These capabilities empower us to unlock solutions never before possible. 

We conducted a global study revealing that 83% of professionals familiar with AI believe it will augment human capabilities, leading to increased productivity and new forms of economic value. 

The Evolution  of AI Agents 

Before we explore the different types of AI agents, let’s understand what sets them apart from other large language models (LLMs). The evolution of AI agents has been driven by the rapid advancement of LLMs in recent years. LLMs have paved the way for increasingly sophisticated AI capabilities, from basic chatbots to AI assistants, copilots, and now a new frontier ofAI agents. 

chart comparing AI agents vs other large language models

AI agents have been in development since the 1960s, encompassing a wide range of capabilities. From basic rules-based agents to those that learn and adapt over time, these early innovations paved the way for the two types of agents most relevant to enterprise software today:

  • Task-based agents: These agents are designed to excel at performing specific tasks, often within a narrow domain. They can automate repetitive or complex tasks, freeing up human workers for other activities. A task-based agent might be used to process invoices, schedule appointments, or analyze large datasets.
  • Role-based agents: These agents are designed to support humans by understanding the role’s complexities and levels of access in an organization and by taking on specific tasks and responsibilities. For example, a role-based agent for a sales representative might automate data entry, generate personalized email responses, and provide customer insights, allowing the sales representative to focus on building relationships and closing deals. 

At Workday, we see the future of work in role-based agents. These agents understand the complexities of roles at the individual and organizational level, including governance structures, and take on a wider range of responsibilities to drive significant impact and unlock new productivity levels.

Role-based agents have a configurable skillset designed to assist individuals in their specific roles. Going beyond task-based agents, they focus on targeted responsibilities and personalized end goals, empowering employees to excel in their jobs.

Through learning user interactions, these agents become increasingly adept at anticipating needs and providing tailored support. This can boost individual productivity and  enhance overall organizational efficiency.

How AI Agents Are Tackling Enterprise Challenges

AI agents are poised to change everything from customer service and supply chain management to HR and finance. The key is to understand their potential and develop a strategic roadmap for implementation. 

Here are a few examples of how they can address common business challenges:

  • Streamlining HR processes: AI agents can automate processes such as sending personalized onboarding material, scheduling interviews for recruiting, and generating learning plans for performance management, freeing up HR professionals to focus on more strategic, people-centered initiatives.
  • Optimizing supply chain management: AI agents can analyze data to predict demand, optimize inventory levels, automatically reorder supplies, and improve logistics, leading to cost savings and increased efficiency.
  • Enhancing customer service: AI agent-powered chat can handle routine customer inquiries, providing personalized support and taking action on resolving issues while freeing up human agents to focus on more complex issues.
  • Improving financial planning and analysis: AI agents can enhance financial planning and analysis by identifying trends, generating predictions, and offering insights to support decision-making. Additionally, these agents can manage exceptions, create financial rules, and route rules to the appropriate roles.

AI agents are poised to change everything from customer service and supply chain management to HR and finance.

Key Considerations for Deploying Agents in Enterprise  

Deploying AI agents successfully requires careful planning and execution. Here are some high-level considerations to keep in mind:

  • Understanding the problem: Clearly define the challenge you’re trying to solve with AI agents. Are you aiming to streamline workflows, improve decision-making, or enhance employee experiences?
  • Adopting a user-centric approach: Design AI agents with the end user in mind. Ensure they are intuitive and easy to use and that they integrate seamlessly into existing workflows.
  • Establishing a data foundation: High-quality data is crucial for effective AI. Establish robust data governance practices to ensure your data is accurate, complete, and unbiased.
  • Building trust and transparency: Build trust by choosing AI solutions from providers with a strong track record in security, reliability, and ethical AI development. Additionally, create internal AI principles to guide the organization’s AI use. 
  • Mitigating risk: Continuously assess and mitigate potential risks associated with AI, including data privacy, bias, and the appropriate level of automation.
  • Connecting the dots: Leverage the power of AI by connecting different systems and data sources to gain valuable insights and drive intelligent automation.
  • Testing and monitoring: Rigorous testing and ongoing monitoring are essential to ensure AI agents perform as expected and continue to meet evolving needs. 

By keeping these points in mind, companies can successfully use AI agents while ensuring responsible and ethical deployment.

Beyond Deployment: Building and Managing Your Digital Workforce

To truly maximize the impact of AI agents, we need to think about how we build and manage them. This requires a thoughtful approach that considers not only the technical aspects but also the human impact.

It’s essential to start with a deep understanding of the problems we are trying to solve and the needs of our users. By prioritizing human-centered design and ethical considerations, we can create AI agents that seamlessly integrate into workflows and empower employees to perform at their best. These agents can become part of a new group of digital workers that complement our work. 

Building  AI agents is only the first step. To realize their potential, organizations need a robust system for managing, monitoring, and governing these digital workers. This is where an agentic system of record becomes essential, providing the necessary infrastructure to ensure that AI agents are deployed responsibly, securely, and efficiently.

Building a Better Future of Work with AI Agents

AI has forever altered our expectations for how we interact with machines, changing our user experience paradigms. As we look ahead, we can build AI agents that responsibly understand people’s roles and tasks. These systems will know the nuanced details of our systems, predict and reason next steps, and take actions to achieve our goals. At Workday we’re committed to building this future responsibility, and look forward to doing so with our extended community. 

Ready to shape the future of work with AI? Check out our Workday AI Masterclass and become an enterprise AI expert. 

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