Glean CEO Arvind Jain highlights the strategic battle over who owns the core AI layer within enterprises. He warns that ceding control to external tech giants risks data sovereignty and competitive advantage, urging companies to consider building or owning their intelligent coordination platform. The decision will define organizational competitiveness for the next decade.
Amid the global race to harness artificial intelligence, a crucial strategic question is emerging that concerns both technology leaders and executives: Who will own and control the AI layer within corporations? This is not merely a technical debate but an existential question concerning digital sovereignty and future competitiveness. In an exclusive discussion with TechCrunch AI, Arvind Jain, CEO and co-founder of Glean, a company specializing in AI-powered enterprise search, addressed this issue in detail. Jain explains that the answer to this question will define the shape of organizations for the coming decade, as the AI layer transforms from a supporting tool into the core neural infrastructure that manages knowledge and decision-making.
Jain describes the "AI layer" as the foundational platform that connects all of a company's applications, data, and analytical capabilities, enabling them to operate as a unified, intelligent entity. Traditionally, companies purchased separate software for CRM, HR, and accounting, but AI creates a need for an intelligent coordination layer that understands context across all these systems. The danger, according to Jain, is that companies might allow major external platforms to control this vital layer, making them hostage to algorithms and agendas that may not align with their specific interests.
Arvind Jain explains that tech giants offer ready-made, easily integrated AI solutions, tempting companies to adopt them. However, he warns that this approach could cost companies their strategic autonomy and data sovereignty. Once a company's core processes become dependent on an external platform, it becomes extremely difficult to abandon or modify it. Furthermore, sensitive company data and intellectual property could become part of a public training model, eroding its unique competitive edge.
The impact of this issue extends far beyond IT departments. It concerns the heart of strategic decision-making. If the AI layer is owned and managed internally, a company can tailor it to understand its unique industry, customer preferences, and internal success secrets. This creates an "organic" AI that grows with the company. In contrast, external solutions may provide short-term efficiency but produce generic insights similar to competitors using the same platform. In the future market, the difference between a leading company and a laggard may be its ability to extract unique signals from its proprietary data through an owned AI layer.
The AI layer is the software framework and infrastructure that integrates AI models and APIs with a company's existing systems (like CRM, ERP, and databases). Its function is to understand, query, analyze, and generate insights from all enterprise data, presenting it to employees through conversational interfaces or intelligent dashboards.
Key risks include: loss of control over sensitive data, difficulty customizing for precise needs, costs tied to third-party services, the danger of vendor lock-in where switching providers becomes nearly impossible, and receiving generic, undifferentiated insights.
Yes, it has become more accessible with ready-made AI platform tools and open-source resources. It doesn't necessarily require building models from scratch but can focus on integrating and customizing existing models and securely connecting them to company data. Companies like Glean position themselves as an intermediate solution that provides the core infrastructure while keeping control and sovereignty with the company.
The debate over AI layer ownership is not a distant technicality but a pressing strategic imperative. As Arvind Jain articulates, the choice between convenience and control will fundamentally shape a company's agility, innovation capacity, and market position. While external platforms offer a fast start, they may mortgage a firm's future autonomy. Building or owning the core AI infrastructure, whether fully in-house or through a sovereign partnership model, represents an investment in long-term competitive resilience. In the age of AI, the most valuable asset may not just be the data a company holds, but its sovereign ability to intelligently orchestrate and learn from it.
Source: TechCrunch AI | Analysis & Editorial: AI Tools Oasis
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