Context Is the Next Competitive Edge in Enterprise AI

Insights from “Astreya Talks AI: Beyond the AI Roadmap,” featuring Debashree Chatterjee, VP of Enterprise AI Practices; Edward Betancourt, CTO; Abhilash Mana, SVP of Practices; and host Lauren Frazier, VP of Marketing.

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Walk the floor at Google Cloud Next or ServiceNow Knowledge and you’ll hear a hundred pitches about smarter models, faster models, cheaper models. But in order to deliver on any of these promises, the models need more context than many businesses may realize.

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"One theme that stood out for me definitely was that the conversation is shifting from model efficiency to enterprise context," says Debashree Chatterjee, Astreya's VP of Enterprise AI Practices, reflecting on this year's conferences. "We have lots of models. They are already efficient enough. What is challenging right now is to give the right trusted context to these models."

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Lack of context is why so many enterprise AI programs stall in pilot. The model works. The demo works.  But production halts because data is scattered across systems that were never designed to talk to each other. 

Stop fighting fragmentation

The instinct is to fix the sprawl. Consolidate everything into a data lake and let AI loose on it. Chatterjee has watched that plan age poorly.

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"Enterprise data and context will stay fragmented across the system. We cannot change that. We have to accept it. So our old architecture of copying data from multiple data sources and then centralizing it, I don't think that will stay valid for very long anymore."

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The platforms agree with her. Both Google Cloud and ServiceNow spent this year's keynotes signaling the same shift. ServiceNow's zero copy connectors and context engine, part of its Workflow Data Fabric, let you hand trusted context to a model without duplicating a single record. Google is pushing the same direction from the foundational layer.

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Astreya CTO Edward Betancourt describes what that looks like in practice: "You can plug in your BigQuery data sets to ServiceNow in a zero copy fashion, and your data stays on your side. ServiceNow is going to leverage it, execute the transaction, and you move on with your business."

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Your data stays put. The context travels. That is the architecture the next few years will be built on.

The edge belongs to whoever moves context fastest

Chatterjee's takeaway from Knowledge 26 doubles as a warning for anyone still shopping based on benchmark scores: "The next competitive edge is not who has the better model, but basically who would actually give the right context to these models. That's where our focus needs to be."

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This reframes the entire buying decision. With models are converging, context pipelines are where organizations will separate, and context work is unglamorous: entitlements, lineage, knowing which system holds the truth about a customer's payment history when three systems disagree.

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It also reframes how solutions should be designed. "We don't architect solutions driven by platform or a platform feature," Chatterjee says. "Rather, we have to solve based on the business outcome that we have to achieve. And then we see which platform, which platform feature, is the best fit."

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Start with the outcome. Find the context the outcome requires and pick the feature that delivers it. In Chatterjee’s account-closure example from the webinar, that meant a zero copy connector for context and an RPA tool for action, because the customer's core system predated APIs entirely. 

What this means for your roadmap

Host Lauren Frazier closed the webinar with this:: the winners will be "the ones who can give operational context faster."

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So before the next model announcement pulls your attention, ask yourself, can your AI see what your best operator sees? If the answer is no, more parameters will only help it guess with greater confidence.

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Astreya has spent the last two years building in the context engineering space, across ServiceNow, Google Cloud, Databricks, and the tools already running your operation. If you want to know what your context gap actually looks like, we can show you.

Book a free consultation.

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