AI Agents and Agentic Actions for Enterprises
AI is revolutionizing the business world, with AI agents at the forefront of this transformation. These agents are software programs designed to perform tasks autonomously or semi-autonomously, each tailored to accomplish specific goals through advanced programming and logic.
So, let’s explore how AI agents work and how they are poised to reshape the world as we know it.
Key Benefits of AI Agents
AI agents offer significant advantages in the B2B industry across various operations. Here are some key benefits:
- • Efficiency: They automate repetitive processes and handle mundane tasks, significantly boosting human productivity.
- • Accuracy: AI agents reduce errors compared to human operators, enhancing overall precision.
- • Scalability: These agents can scale extensively without requiring a corresponding increase in human resources. They are multi-tenanted from the outset, allowing different tenants to deploy the same agent at scale to maintain a competitive edge and drive business growth.
- • Cost-effectiveness: Integrating AI agents into B2B workflows reduces operational costs by automating mundane tasks traditionally performed by humans. Thus freeing up humans to perform more creative tasks.
- • Customer Satisfaction: They improve the customer experience by delivering quick, personalized service.
Some favourite use cases in B2B are:
- • Analysing and forecasting data in CRM.
- • Supply chain management.
- • Financial analysis and forecasting.
- • Inventory management.
- • Administrative activities.
- • Travel booking and employee onboarding.
AI agents can also exist for B2C use cases. Some popular B2C use cases might be:
- • Conversational AI bots for eCommerce, contact centres,
- • eCommerce recommendation.
- • Sales assistant agents
- • Virtual shopping assistants
- • Content generation for marketers
- • Agents for scheduling and activities
How do AI Agents work?
AI Agents work based on the following schematic:
- 1. Perception: Instructions and prompts fed to AI agents
- 2. Decision-making: AI agents leverage LLMs to organize communication, reasoning, and informed decisions based on prompts, learned patterns, and predefined algorithms
- 3. Action: AI agents then use all the information gathered to go after “outcomes” by using Composio to execute their actions via function calls to APIs, RPCs, etc.
- 4. Learning: Agents constantly learn from past experiences and adapt for future performance improvements.
How does Composio facilitate Agentic Actions?
Composio is a platform offering AI Agents and LLMs tools designed to streamline and optimize their interaction with various APIs and services. It supports integrations with popular applications like Google Apps, GitHub, and Slack, as well as system tools such as Code Interpreter, File Manager, and Databases. Composio handles user authentication, enabling your agents to seamlessly connect with these tools and perform actions on behalf of your users. It supports a range of authentication protocols, including OAuth1.0/OAuth2.0, API Key, and Basic Authentication.
The above pictorial on Agents can be flattened out by adding Composio to represent the outcome.
Implementing AI Agentic Actions
Implementing AI agents presents certain challenges and evaluations. It is not just about adopting innovative technology; it is about ensuring team alignment and defining clear goals, as in
- • evaluating business readiness,
- • establishing clear objectives,
- • preparing data, and
- • selecting an appropriate platform.
Additionally, considerations for data privacy, security, and ethical issues are also essential.
AI Agents and Agentic Actions for Enterprises
CIOs/CTOs should assess and evaluate the company’s AI readiness, examining how AI aligns with the company strategy, technological infrastructure, team capabilities, and training.
Employees’ buy-in and readiness to adopt innovative technology are crucial.
Use this checklist to gauge your readiness:
| Criteria | Description |
| Business Strategy | Has a vision and strategy been defined to adopt AI technology |
| Tech Setup | Does the company have the requisite infrastructure and technology capability to pursue an AI initiative? |
| Team Skills | Are the employees in the company willing and trained to adopt AI? |
Setting Clear Goals
AI agentic actions are not for everyone. However, initial studies by the analyst community have found that AI agents are particularly effective in process-oriented tasks. These tasks follow a specific methodology and must adhere to well-defined industry processes. To determine if AI agent actions are indeed necessary for your company, consider these questions:
- 1. What issues will AI agentic actions address for your business?
- 2. How will AI agentic actions add value to your operations?
- 3. What are your expected outcomes from AI agentic action implementation?
- 4. How will you measure and evaluate success?
Your goals should adhere to the SMART criteria: Specific, Measurable, Achievable, Relevant, and Time-bound. This approach enables progress tracking and ensures you are on the right path.
Measuring Success
Implementing AI agenting actions is the initial step. Evaluating their performance and assessing their business value is crucial for ongoing success.
Key Metrics for AI Agent Success
Tracking appropriate metrics (observability) is essential to gauge AI agentic action effectiveness and can be based on important indicators:
| KPI | Measurement Focus | |
| Effectiveness | Are AI agentic responses correct and taking the right actions | |
| Response Time | How fast are the agent’s actions | |
| User Satisfaction | Is the User (customer) satisfied with the action provided | |
| Cost Savings | Measure the cost savings without considering human supervision. | |
| Revenue | Is it increasing the customer’s revenue? | |
Align these KPIs with your business objectives to ensure your AI agents meet your goals.
Composio strives to enable these right out of the box, making it easy for enterprises to use KPIs to measure success.
Continuous Improvement and Optimization
AI agentic action implementation requires ongoing attention and refinement. Regular KPI assessments reveal areas for improvement.
Update your AI agents with new data consistently to maintain their relevance. This practice helps them adapt to changes in the business environment and user behaviour.
Stay informed about emerging AI technologies that could enhance your agents’ capabilities. Keeping pace with AI and machine learning advancements ensures your agents remain competitive.
Conduct periodic audits of your AI agents to identify and address any ethical or privacy concerns. Maintaining ethical standards and protecting user data builds trust and encourages the adoption of AI solutions. Pay attention to the EU AI Act, especially if AI agentic actions are used in Europe.
In conclusion, user feedback is extremely critical. User insights can highlight areas for improving AI agentic actions. The goal is to streamline business operations, enhance user experiences, and drive growth. Therefore, continue refining and optimizing your AI agents as part of your ongoing AI agentic action development process.
Enterprise companies
To empower your agents, use Composio Quick Start to see how agentic actions can be enabled in a few lines of code. Bring your agent and use our guide and tools.