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There’s no limit with AI

Reimagine information with OpenText Aviator across key functional areas:

AI Resources

 
 
Blog

What's keeping CIOs up at night? Owning the AI agenda.

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Report

AI is redefining the role of the knowledge worker

This CIO white paper examines how AI changes the way we work

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Ebook

7 myths about AI and cloud—busted

What every CIO needs to know to move faster, smarter, and with confidence

Get the facts
Webinar series

Reimagine work with OpenText Aviator

Discover how organizations can bring humans and AI together to reimagine work

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Checklist

Address your biggest business challenges with AI

See how AI capabilities can help solve 7 different use cases

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Report

How to ensure your information is ready for AI

A new survey from Ponemon Institute shows senior IT leaders are finding a widening gap between AI strategy and execution—and at the heart of this challenge is information readiness

Read the survey results

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Frequently asked questions

AI can address many use cases in corporate settings. These are just a few examples: New sales staffers that need to quickly get up to speed on existing customers can use AI to pull structured and unstructured data from different repositories, eliminating the need for manual searches. A corporate help desk that needs to improve service quality and speed can use virtual agents to help users self-resolve common requests. A DevOps team that needs to cut software delivery time in half can use AI automation to translate manual test scripts into automated codeless tests.

OpenText™ Aviator suite of solutions help solve these and many other use cases.

One way AI agents can talk to each other is through Model Context Protocol (MCP), an open-source standard that seeks to allow for secure, two-way connections between AI systems and external tools, data sources, and services. It also provides a means for multi-agent coordination and collaboration. Essentially, it creates a standardized connection integration layer for agents to access tools. MCP is still an emerging standard, but such integration is needed to allow AI agents to work autonomously, therefore requiring less human involvement and freeing up workers for more strategic and creative tasks.

A digital knowledge worker is a knowledge worker whose performance is enhanced by business AI agents and personal AI assistants. They combine their expertise with data analysis, advanced analytics, and agentic AI to make real-time decisions, predict outcomes, and automate workflows.

OpenText™ Aviator suite of solutions help knowledge workers become digital knowledge workers so they can work faster and smarter.

Agentic AI can understand objectives, formulate strategies, and take independent actions while adapting to changes. By delegating tasks to AI agents, businesses can focus on strategic initiatives, problem-solving, and customer relationships.

OpenText™ Aviator solutions help businesses leverage AI-including agentic AI-to improve productivity, decision-making, and customer experiences.

How can we help?