11 Leading Agentic AI Tools for Businesses

If you’re looking into more sophisticated AI tools to improve your business processes, you’ve probably heard of "agentic AI." 

This technology is designed to automate complicated workflows and make independent decisions—tackling problems that traditional automation or AI tools can’t handle.

Agentic AI refers to  AI systems designed to autonomously complete complex goals and manage workflows with minimal direct human oversight. Systems boasting agentic AI can perform independent decision-making, strategic planning, and adaptable execution to handle multi-step tasks. 

These capabilities enable agentic AI to function independently, proactively, and intelligently, addressing complex challenges in ever-changing environments.

More companies are choosing agentic AI

Gartner predicts that 33% of enterprise software will use agentic AI by 2028 33, compared to just 1% in 2024. This belief shows that agentic AI isn’t just another tech trend; it’s quickly becoming a must-have for staying competitive.

But with so many agentic AI solutions, how do you determine which fits your business needs? 

Consider a tool that:

• Works smoothly with your current systems
• Offers transparent decision-making
• Doesn’t need extensive technical know-how
• Shows real ROI

In this guide, we'll look at the leading agentic AI tools available today, highlight their key features and capabilities, and provide practical guidance to help you make an informed decision for your organization.

Agentic AI tools: Enabling dynamic actions at scale

More teams looking to automate their tasks and workflows are choosing agentic tools because these tools offer greater flexibility and intelligence, allowing for dynamic adaptation to complex and evolving needs.

Agentic AI systems combine many of the following capabilities: 

• Autonomous decision-making: Making independent decisions based on context and data without constant human intervention.
• Integrated multitasking: Combines various AI functionalities to perform complex tasks that would otherwise require multiple standalone agents.
• Adaptive learning: Continuously learns and adapts to new information and changing environments, improving over time.
• Contextual understanding: Possesses a deeper understanding of context, enabling more accurate and relevant responses.

Here’s an example of agentic AI: An AI agent might answer an IT-related question from an employee (such as how to request access to a specific application), but an agentic AI system can:

• Perceive and identify the problem 
• Figure out the right solution
• Take independent action
• Learn from interaction 

Each of these critical steps enables an AI agent to autonomously interact with customers, delivering timely and accurate assistance.  

Because agentic tools are so flexible, instead of creating separate tools for every challenge, agentic AI platforms can handle various business needs across departments—like IT service management, HR support, finance operations, and sales enablement.

For IT leaders, it means fewer isolated tools to juggle, improved efficiency, and more time to focus on strategic initiatives. Your teams can spend less time on maintenance and more time innovating, while employees across the rest of the company enjoy faster, more streamlined service.

Top features when selecting an agentic AI tool

When looking at agentic AI solutions for your business, there are some key features you’ll want to focus on. After all, there's no one-size-fits-all solution, especially when working with agentic AI. And while the features should be able to work for you now, the tool you select also needs to be able to grow and adapt to meet your future needs.

Here are some of the top features to look for when selecting an agentic AI tool:

Reasoning and planning

The real power of agentic AI is in its decision-making skills. Here’s what to look for: 

• Smart reasoning systems that can understand complex requests and figure out the best actions to take 
• Context-aware planning that considers business rules and goals 
• The ability to break down complicated workflows into step-by-step actions 
• Decision trees and logic flows that adjust in real-time  to adapt decision-making processes 

These features let the system handle tricky situations that usually require human judgment, like prioritizing urgent IT issues or determining the right approval path for requests.

Ease of use

Reportedly, only about one-quarter of employees feel confident in their usage of AI tools in their job. Even the most powerful AI tool provides little value if your team can't effectively implement and manage it.

As such, you should focus on: 

• User-friendly interfaces that are easy to navigate, no technical know-how needed 
• Ready-to-use templates and automation workflows for everyday business tasks 
• Clear guides and solid support to help you along the way 
• Simple deployment options that fit your IT setup

The right solution should enable quick time-to-value without requiring you to hire specialized AI talent or undergo extensive training programs.

Integration and compatibility

Agentic AI works best when it easily plugs into your existing enterprise systems. Here’s what to check for during your evaluation: 

• Ready-made integrations with popular business apps 
• APIs for custom connections 
• Security infrastructure compatibility 
• Flexible deployment options (cloud, on-premises, or hybrid) 

Look for tools that break down departmental silos, connecting ITSM, HR, finance, and other systems for service automation across teams.

Transparency and explainability

As AI starts making more decisions, it’s essential to understand how those decisions are being made. Look for tools that provide: 

• Clear audit trails to track AI actions and decisions 
• Explainable AI that can break down its reasoning 
• Debugging features to spot and fix problems
• Performance analytics to see how well it’s working 

This kind of transparency is especially key in regulated industries like healthcare and finance, where you need to maintain compliance and be able to explain automated decisions to auditors.

Security and compliance

Enterprise AI needs to meet strict security standards, especially when handling sensitive data across systems. Make sure your solution comes with: 

• End-to-end encryption for data in transit and at rest 
• Role-based access controls with detailed permissions 
• Compliance with key regulations like GDPR, HIPAA, and others 
• Regular security audits and vulnerability testing 
• Data residency options to meet regional requirements 

The most secure agentic AI tools bake security into their design from the start, instead of tacking it on later as an afterthought, with solid data handling practices to keep your company's information safe.

With that, let's explore the top agentic AI tools on the market right now.

1. Moveworks

Moveworks delivers an enterprise-grade AI Assistant designed to transform employee support and automate complex workflows across your organization. As an agentic AI platform, Moveworks goes beyond simple chatbot functionality and can understand context, make decisions, and take action autonomously.

Key features

• Agentic Reasoning Engine: Understands employee requests in natural language, determines intent, and executes multi-step processes to resolve issues without human intervention
• Cross-system orchestration: Works across IT, HR, facilities, finance, and other enterprise systems through 100+ pre-built integrations
• Contextual understanding: Personalizes responses based on the employee's role, location, department, and previous interactions
• Autonomous resolution: Directly executes actions in connected systems, from password resets to software provisioning and beyond
• Out-of-the-box implementation: Delivers value on your AI investment in weeks rather than months, with no need for extensive training or building custom AI models

Best use case

Moveworks is an excellent fit for large enterprises looking to automate employee support across different departments. It’s especially useful for companies with complex tech stacks and multiple service areas that want to deliver consistent, high-quality support without hiring more staff.

The platform is designed for enterprise-scale deployment, with the security and compliance features regulated industries require, including financial services, healthcare, and government.

See how Moveworks can transform your employee experience with agentic AI.

2. Microsoft Copilot agents

Microsoft Copilot agents extend the capabilities of Microsoft's Copilot AI assistant, allowing organizations to build custom AI agents that automate specific business processes within the Microsoft 365 ecosystem.

Key features

• Microsoft 365 integration: Natively works with Microsoft applications including Teams, Outlook, SharePoint, and more
• No-code agent creation: Enables business users to build task-specific agents without programming expertise
• Personalized workflows: Creates customized experiences based on user roles and permissions
• Natural language interaction: Allows employees to make requests in conversational language
• Built-in security: Leverages Microsoft's enterprise security framework

Best use case

Microsoft Copilot agents are ideal for organizations already heavily invested in the Microsoft ecosystem and want to enhance productivity through automation. They work best for companies seeking to automate specific tasks within Microsoft applications rather than cross-platform processes that span multiple vendors.

3. OpenAI Operator

OpenAI Operator builds on the company's advanced language models to enable agentic capabilities that can interact with various tools and APIs to complete complex tasks autonomously.

Key features

• Flexibility: Connects to and operates external tools and APIs to accomplish tasks
• Action validation: Implements guardrails to ensure safe and appropriate actions
• Reasoning chains: Breaks down complex problems into sequential steps
• API-driven architecture: Enables integration into various applications and workflows
• Advanced language understanding: Uses OpenAI's advanced language models for deeper understanding

Best use case

OpenAI Operator is suitable for developers and organizations working on custom AI applications that need advanced reasoning and action capabilities. It’s particularly effective for complex analysis and decision-making tasks, though it generally requires technical expertise to set up and utilize due to its API-driven nature.

4. Aisera

Aisera offers Agentic AI that combines conversational AI with workflow automation to deliver autonomous resolution across various enterprise functions.

Key features

• Multi-domain capability: Automates processes across IT, HR, customer service, and sales operations
• Semantic search and knowledge management: Uses enterprise knowledge bases to provide accurate information
• Autonomous resolution: Handles routine requests without human intervention
• Predictive intelligence: Anticipates issues and provides proactive support
• Integration ecosystem: Connects with hundreds of enterprise applications and systems

Best use case

Aisera is well-suited for medium to large organizations seeking to automate customer and employee service across multiple departments. It works well for companies with high support ticket volumes that want to reduce resolution times and support costs while maintaining service quality.

5. CrewAI

CrewAI is an open-source framework that brings multiple AI agents together to collaborate on solving complex problems, much like how human teams work on projects.

Key features

• Multi-agent collaboration: Enables multiple specialized agents to work together on complex tasks
• Role-based architecture: Assigns specific roles and responsibilities to different agents
• Flexible LLM support: Works with various large language models, letting you choose the best fit
• Human-in-the-loop options: Supports varying levels of human oversight and intervention

Best use case

CrewAI works well for organizations with complex workflows that benefit from breaking tasks into discrete steps handled by specialized agents. It's a valuable tool for research, data analysis, content creation, and other creative or analytical processes that require multiple perspectives and capabilities.

6. Adept

Adept focuses on building AI that can operate enterprise software systems through its action-oriented approach to agentic AI.

Key features

• UI automation: Enables AI to navigate and use software applications through their interfaces
• Multimodal understanding: Processes text, images, and application interfaces to understand context
• Enterprise software focus: Specializes in automating workflows within common business applications
• Cross-application capabilities: Works across multiple software programs to complete complex processes

Best use case

Adept is valuable for organizations looking to automate interactions with existing software systems without extensive API integration. It's good at tasks like data entry, report generation, and cross-system workflows, reducing the need for manual switching between multiple interfaces.

7. Beam

Beam positions itself as a platform for Agentic Process Automation, helping enterprises automate complex workflows through AI agents that can reason, learn, and take action.

Key features

• Multi-agent intelligence: Integrates several AI agents to deliver comprehensive automation
• AI-native agent OS: Offers accuracy, reliability, and flexibility in a unified platform
• Enterprise integration: Connects with existing business systems and processes

Best use case

Beam is tailored for Fortune 500 companies and scale-ups aiming to reduce operational costs and enhance efficiency through workflow automation. It's also made for organizations with complex processes spanning multiple departments and systems.

8. UiPath

UiPath combines robotic process automation (RPA) with agentic AI capabilities to create in-depth business process automation solutions.

Key features

• RPA integration: Combines traditional automation with AI-powered decision-making
• Process mining: Identifies automation opportunities through data analysis
• AI-powered automation: Enhances robotic processes with intelligent decision-making
• Low-code development: Enables business users to create automations with minimal technical expertise

Best use case

UiPath can automate document-heavy processes and workflows that mix structured and unstructured data. It’s beneficial in industries like finance, insurance, healthcare, and others where managing numerous forms and strict compliance requirements is essential.

9. Orby

Orby offers an enterprise AI automation platform focused on improving efficiency through generative process automation, which increases automation scope while simplifying workflow definitions.

Key features

• Multimodal Large Action Model: Enhances understanding and action capabilities
• Neuro-symbolic programming: Combines neural networks with symbolic reasoning
• Rapid deployment: Reduces automation development costs and implementation time

Best use case

Orby works for enterprises seeking to scale automation initiatives efficiently. Its platform works particularly well for organizations that need to automate operations while maintaining flexibility to adapt to changing business needs.

10. Kore.ai

Kore.ai provides conversational AI and digital assistants with workflow automation capabilities for enterprise applications.

Key features

• Enterprise virtual assistants: Creates domain-specific assistants for various business functions
• Workflow automation: Integrates conversational interfaces with business process management
• Multi-channel deployment: Works across messaging platforms, voice assistants, and enterprise systems
• Intent discovery: Automatically identifies common user requests and process patterns

Kore.ai is particularly effective for customer-facing and employee support applications that require natural language interaction and process automation. It's designed for large enterprises seeking to automate service operations while maintaining a conversational interface.

11. Anthropic Claude 

Anthropic's Claude is an AI assistant designed with agentic abilities to autonomously perform a variety of tasks, from answering questions to managing complex workflows. It leverages advanced language models to provide intelligent, context-aware support and decision-making.

Key features

• Dynamic task management: Using advanced natural language understanding, allowing it to autonomously direct its processes and tool usage.
• Autonomously execute actions: Without needing explicit, step-by-step instructions and offers robust analytics 
• Monitoring capabilities: Enables it to continually optimize performance
• Integrations with existing systems: Ensures it can handle complex interactions and adapt to evolving needs
• Agentic computer use capability (Beta):  Claude LLMs can autonomously work with computer systems to get tasks done, and is capable of interacting with tools that can manipulate a computer desktop environment.

Best use case

Claude is suited for organizations needing advanced AI-driven task automation and decision support. It does well at complex analysis, multi-step workflows, and decision-making. Claude's agentic abilities make it valuable for research, content creation, and customer support, where it can autonomously manage and optimize certain processes.

How to choose the best agentic AI tool for you

Selecting the right agentic AI solution requires carefully considering your organizational needs and goals. Here's a structured approach to making this important decision:

1. Define your business requirements: Start by clearly identifying the specific processes you want to automate and the problems you need to solve. Consider both immediate pain points as well as long-term goals.

2. Assess your technical environment: Evaluate your existing systems, data sources, and infrastructure. The ideal solution should integrate easily with your current technology stack while providing flexibility and adaptability for future growth.

3. Consider implementation resources: Be realistic about your internal capabilities for implementing and managing an AI system. Some solutions require significant technical expertise, while others offer more plug-and-play deployment options.

4. Evaluate security and compliance needs: If you operate in a regulated industry or handle sensitive data, prioritize solutions with security features and compliance certifications that align with your requirements.

5. Calculate total cost of ownership: Look beyond initial licensing costs to consider implementation expenses, ongoing maintenance, and potential need for specialized talent. The most affordable option upfront isn't necessarily the most cost-effective in the long run.

6. Consider scalability: Choose a solution that can grow with your organization, supporting eventual additional use cases and users without requiring significant rearchitecting or new investments.

Transform your enterprise with agentic AI

Agentic AI automation allows IT leaders to improve efficiency, enhance employee experiences, and streamline strategic value to their organizations. 

Choosing the right solution for your needs lets you automate the more complicated tasks that used to take a lot of manual effort, giving your team more time to focus on innovation and growth.

When exploring these top agentic AI tools, think about more than just what they can do now. Consider how these AI-driven solutions fit into your long-term plans for intelligent automation. 

The right choice should be a solid foundation for growth, helping you scale automation across your business over time.

Learn how an agentic AI assistant can empower every employee and drive success for your business.