Organizations racing to deploy agentic AI are discovering that raw model performance is only part of the equation — context engineering is the key to managing decades of unstructured, ungoverned data trapped inside legacy information management systems.

As Google Cloud Next 2026 signals a complete pivot toward the agentic enterprise, the deeper question for IT leaders is not which model to choose but how to supply agents with the governed, contextual data they need to act reliably at scale. That challenge sits squarely in the wheelhouse of Open Text Corp., a global leader in secure information management that has been building the context layer enterprise agents depend on, according to Waqas Ahmed (pictured, left), vice president of AI engineering at OpenText.

“Enterprise information is not just files on a drive,” Ahmed said. “It is organized, governed, tagged with context, tagged with metadata and integrated with the business applications and customer processes. To wire that into the AI providers and LLMs, you have to be able to build that context so you are not flooding the LLMs with extra information, but you’re giving them the right information at the right time.”

Ahmed and Yemi Falokun (right), global AI/ML partner engineering lead at Google LLC, spoke with theCUBE’s John Furrier at Google Cloud Next, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how OpenText and Google Cloud LLC are co-engineering a full agentic stack built on context engineering, data sovereignty and open interoperability standards. (* Disclosure below.)

Context engineering as the foundation for enterprise agentic AI

The OpenText and Google Cloud partnership, formally expanded in November 2025 to cover AI innovation, data privacy and sovereign cloud, reflects a shared conviction that enterprise AI success requires more than model access — it requires a governed data layer. OpenText’s generative AI journey with Google began in May 2023, when it started using what is now the Gemini Enterprise Agent Platform to build industry-specific solutions, including its Content Aviator, which lets users interact with decades of enterprise documents in a trusted, secured environment, Falokun noted.

“What they’re now doing is taking the foundation they’ve built from 2023 into the AI agentic era,” Falokun said. “We’re now deeply integrating the Gemini Enterprise Agent Platform so that we can allow our joint customers to deploy secure autonomous solutions at scale, leveraging those decades of information that they store on behalf of their users.”

The stakes of getting context engineering wrong are significant. Without it, agents operating inside sensitive workflows — such as HR onboarding or insurance claims — have no way to enforce security policies, reproduce deterministic outcomes or generate the audit trails that compliance teams require, Ahmed explained. This is precisely the gap OpenText Aviator Studio is designed to close with a no-code platform that allows customers to build, govern, and connect enterprise AI agents — and extend them across multi-application workflows beyond any single system.

“We believe that we should bring AI to the data and not data to the AI,” Ahmed said. “When you bring AI to the data, it means that you can still be in control of the permissions, the governance, the security, the access, the relationship between the data and the local intelligence can orchestrate across those entities, those stores, to find the right answer.”

The partnership also extends to data sovereignty, a concern increasingly central to global enterprises. OpenText supports private AI deployment patterns where the entire processing lifecycle remains within a customer’s sovereign environment, and Google Cloud reinforces this with regional services, customer-managed encryption, and a commitment not to use customer data for model training, Falokun said. On interoperability, OpenText has made its Content Aviator available within the Gemini Enterprise environment through both agent-to-agent integration and Model Context Protocol-based data connectors — meaning Google Workspace customers can access OpenText-hosted content through agents without writing any custom code.

“If you keep the agents locked up within their individual applications, all you have done is automated the existing applications for some efficiency, but that’s not the true power of the agentic enterprise,” Ahmed said. “The true power is in the choreography and orchestration across silos, across applications where data provides the intelligence and AI executes the actions to provide productivity, insights and competitive advantage.”

Stay tuned for the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Google Cloud Next.

(* Disclosure: OpenText sponsored this segment of theCUBE. Neither OpenText nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE