3 use cases for Agentic AI

Agentic AI is rapidly reshaping the way businesses operate, offering powerful automation, enhanced productivity, and smarter interactions through intelligent agents. By connecting Large Language Models (LLMs) to business tools and workflows, organizations can significantly streamline complex tasks. You might find yourself asking, “What can agentic AI do?” or “What are some uses for agentic AI?”. Here are three use cases that showcase the practical value of adopting agentic AI:

1. Instant App Development from Figma Files

Imagine drastically reducing the time and effort it takes to turn a design into a functional app. With agentic AI, designers and developers can upload a Figma file directly to a platform like Cursor. With just a click, Cursor utilizes intelligent AI agents to automatically interpret the design, generate code, and build a ready-to-deploy application. This significantly accelerates the development process, allows for rapid prototyping, and reduces the time-to-market for digital products, giving businesses a substantial competitive edge.

2. Automated Security Compliance with Claude and Okta (or any IAM!)

Maintaining secure password policies is crucial for enterprise cybersecurity, yet manual management can be cumbersome and error-prone. Even automated processes can leave some gaps or issues. By leveraging agentic AI with Claude integrated directly into Okta, security teams can automate the process of identifying users whose passwords meet certain criteria for age or require rotation. Claude intelligently identifies these users, and can trigger automated messages in Slack, prompting timely password resets. This approach enhances security compliance, reduces risk, and frees IT resources to focus on more strategic initiatives. Ultimately, this can save organizations millions in time spent on password reset tickets. 

3. Enhanced Lead Follow-up and Engagement with HubSpot (or your CRM of choice)

Effective outreach before, and follow-up after, events like Identiverse is essential for maximizing networking opportunities and business relationships. By connecting an LLM directly with CRM platforms such as HubSpot, organizations can quickly identify contacts from last year's event whom they've recently engaged with. The agentic AI then automatically generates personalized follow-up messages, inviting these contacts to reconnect at the upcoming event. This automated yet highly personalized outreach significantly improves engagement, strengthens business relationships, and ensures no valuable connection falls through the cracks.

Conclusion

These three use cases demonstrate the transformative impact of agentic AI across diverse business functions—from product development to security management and relationship nurturing. By seamlessly integrating intelligent AI agents into everyday operations, enterprises can unlock new efficiencies, enhance security measures, and foster deeper customer connections. The result is not only a streamlined workflow but also a significant strategic advantage in today's competitive landscape.

It’s also critical to ensure that your LLMs and AI agents are getting the right level of access to your enterprise tools & data to unlock these use cases. Too little, and they won’t be able to effectively complete the tasks you’re asking them to do. Too much, and you could be exposing yourself to undue security risks. Tools like Natoma provide agent access gateways to help manage authentication and authorization for your AI agents.