Glean's Bid for Enterprise AI Dominance: The Underlayer Battle
By Libertarian • 2026-02-13 07:12:45
The enterprise software stack, once a predictable hierarchy of applications, is undergoing a profound transformation. As artificial intelligence moves beyond conversational interfaces to become the very fabric of organizational work, a critical battle is emerging for control of its foundational layer – the intelligence conduit that will orchestrate all enterprise activity.
TechCrunch AI recently highlighted Glean's strategic evolution from an enterprise search product into an “AI work assistant.” This pivot signifies a bold ambition: to establish Glean as the indispensable AI layer beneath all other applications within a company. Rather than merely answering questions, Glean aims to enable AI systems to actively perform tasks and integrate across disparate corporate data silos, fundamentally redefining enterprise productivity and information access.
The quest for a unified corporate knowledge base is not new. Decades of enterprise software development, from monolithic ERPs like SAP and Oracle to the explosion of SaaS applications such as Salesforce, Workday, and ServiceNow, have resulted in fragmented data landscapes. Early attempts at universal enterprise search, exemplified by the now-defunct Google Search Appliance, promised a single pane of glass but often fell short due to integration complexities and a lack of contextual understanding. The advent of large language models (LLMs) and generative AI has, however, introduced a paradigm shift, offering unprecedented capabilities for understanding, synthesizing, and acting upon vast amounts of unstructured and structured data, breathing new life into this long-held aspiration.
Today’s enterprise AI landscape is a fragmented tapestry. While major cloud providers and application vendors—Microsoft with Copilot, Salesforce with Einstein AI, Google with Duet AI—are embedding AI capabilities directly into their own ecosystems, these solutions often remain confined to their respective application boundaries. The true challenge lies in orchestrating intelligence across an organization's entire digital estate, which typically comprises dozens, if not hundreds, of distinct applications and data sources. This necessitates a neutral, comprehensive layer capable of indexing, understanding, and securing information from every corner of the enterprise, thereby powering truly “agentic AI” systems that can autonomously execute complex workflows rather than just generating text or answering simple queries.
Immediately, Glean's ambition addresses the pervasive “last mile” problem of enterprise AI: the struggle to connect powerful LLMs with an organization's proprietary, real-time data while respecting complex access permissions. By sitting beneath other AI applications, Glean promises to provide a unified, secure, and context-rich data foundation. This reduces the immense friction of context switching for employees, who currently navigate multiple applications to gather information. For instance, a sales representative could ask an AI assistant (powered by Glean) for a comprehensive customer brief that pulls data from Salesforce CRM, Slack conversations, Jira tickets, and internal documentation, all without leaving their primary interface. This aggregation capability promises significant productivity gains, potentially saving knowledge workers hours each week by streamlining information retrieval and synthesis.
In the long term, the company that successfully establishes itself as the foundational AI layer gains immense strategic control. This position is akin to an operating system for the enterprise, dictating how information flows, how AI agents interact, and ultimately, how work gets done. Such a layer becomes the central nervous system, holding the master index of corporate knowledge and the keys to an organization's collective intelligence. This carries profound implications for data governance, security, and the very architecture of future enterprise applications. The economic value of owning this layer is staggering; the enterprise AI market is projected to reach approximately $60 billion by 2028, growing at a CAGR exceeding 30%. A company that controls the foundational intelligence layer stands to capture a substantial portion of this value, influencing everything from application development to competitive advantage.
The primary beneficiaries of Glean's ascent, should it succeed, would be enterprises struggling with data fragmentation and AI deployment. They gain a robust, integrated foundation for their AI initiatives, potentially unlocking new levels of efficiency and innovation. Glean itself stands to become a dominant player, commanding premium valuations by becoming an indispensable utility. Furthermore, independent developers of “best-of-breed” AI applications could thrive by building on top of a standardized, comprehensive data layer provided by Glean, allowing them to focus on specialized AI models and user experiences rather than complex data integration.
Conversely, traditional enterprise search vendors that have failed to evolve beyond keyword matching face obsolescence. Point-solution AI companies that cannot seamlessly integrate with a foundational layer like Glean will struggle to demonstrate comprehensive value. The largest incumbents, such as Microsoft, Salesforce, and Google, also face a nuanced threat. While they possess vast resources and proprietary AI stacks, their inherent bias towards their own ecosystems makes it challenging for them to serve as a truly neutral, cross-platform AI layer. If Glean can establish itself as the vendor-agnostic intelligence fabric for multi-cloud and multi-application environments, it could bypass the walled gardens of these tech giants, carving out a significant and independent share of the enterprise AI market.
Over the next 18-36 months, we anticipate an intensified battle for this foundational AI layer. Glean’s immediate challenge will be scaling its integrations and demonstrating measurable ROI across diverse enterprise clients. Expect major cloud providers to redouble efforts to extend their own AI capabilities beyond their native application suites, potentially through aggressive acquisition strategies or by forging deeper integration partnerships. The market will likely see a push towards greater interoperability standards for enterprise AI, driven by customers demanding flexibility and avoiding vendor lock-in. Ultimately, the success of any contender will hinge on its ability to offer unparalleled data security, accuracy, and a genuinely comprehensive view of corporate knowledge, regardless of its origin.
The contest to own the enterprise AI underlayer represents the next frontier in business technology, fundamentally reshaping how organizations access and leverage their intelligence. Enterprises must critically evaluate their AI strategy, considering whether to invest in an independent, unifying intelligence layer to avoid future fragmentation and unlock the full transformative potential of AI.
TechCrunch AI recently highlighted Glean's strategic evolution from an enterprise search product into an “AI work assistant.” This pivot signifies a bold ambition: to establish Glean as the indispensable AI layer beneath all other applications within a company. Rather than merely answering questions, Glean aims to enable AI systems to actively perform tasks and integrate across disparate corporate data silos, fundamentally redefining enterprise productivity and information access.
The quest for a unified corporate knowledge base is not new. Decades of enterprise software development, from monolithic ERPs like SAP and Oracle to the explosion of SaaS applications such as Salesforce, Workday, and ServiceNow, have resulted in fragmented data landscapes. Early attempts at universal enterprise search, exemplified by the now-defunct Google Search Appliance, promised a single pane of glass but often fell short due to integration complexities and a lack of contextual understanding. The advent of large language models (LLMs) and generative AI has, however, introduced a paradigm shift, offering unprecedented capabilities for understanding, synthesizing, and acting upon vast amounts of unstructured and structured data, breathing new life into this long-held aspiration.
Today’s enterprise AI landscape is a fragmented tapestry. While major cloud providers and application vendors—Microsoft with Copilot, Salesforce with Einstein AI, Google with Duet AI—are embedding AI capabilities directly into their own ecosystems, these solutions often remain confined to their respective application boundaries. The true challenge lies in orchestrating intelligence across an organization's entire digital estate, which typically comprises dozens, if not hundreds, of distinct applications and data sources. This necessitates a neutral, comprehensive layer capable of indexing, understanding, and securing information from every corner of the enterprise, thereby powering truly “agentic AI” systems that can autonomously execute complex workflows rather than just generating text or answering simple queries.
Immediately, Glean's ambition addresses the pervasive “last mile” problem of enterprise AI: the struggle to connect powerful LLMs with an organization's proprietary, real-time data while respecting complex access permissions. By sitting beneath other AI applications, Glean promises to provide a unified, secure, and context-rich data foundation. This reduces the immense friction of context switching for employees, who currently navigate multiple applications to gather information. For instance, a sales representative could ask an AI assistant (powered by Glean) for a comprehensive customer brief that pulls data from Salesforce CRM, Slack conversations, Jira tickets, and internal documentation, all without leaving their primary interface. This aggregation capability promises significant productivity gains, potentially saving knowledge workers hours each week by streamlining information retrieval and synthesis.
In the long term, the company that successfully establishes itself as the foundational AI layer gains immense strategic control. This position is akin to an operating system for the enterprise, dictating how information flows, how AI agents interact, and ultimately, how work gets done. Such a layer becomes the central nervous system, holding the master index of corporate knowledge and the keys to an organization's collective intelligence. This carries profound implications for data governance, security, and the very architecture of future enterprise applications. The economic value of owning this layer is staggering; the enterprise AI market is projected to reach approximately $60 billion by 2028, growing at a CAGR exceeding 30%. A company that controls the foundational intelligence layer stands to capture a substantial portion of this value, influencing everything from application development to competitive advantage.
The primary beneficiaries of Glean's ascent, should it succeed, would be enterprises struggling with data fragmentation and AI deployment. They gain a robust, integrated foundation for their AI initiatives, potentially unlocking new levels of efficiency and innovation. Glean itself stands to become a dominant player, commanding premium valuations by becoming an indispensable utility. Furthermore, independent developers of “best-of-breed” AI applications could thrive by building on top of a standardized, comprehensive data layer provided by Glean, allowing them to focus on specialized AI models and user experiences rather than complex data integration.
Conversely, traditional enterprise search vendors that have failed to evolve beyond keyword matching face obsolescence. Point-solution AI companies that cannot seamlessly integrate with a foundational layer like Glean will struggle to demonstrate comprehensive value. The largest incumbents, such as Microsoft, Salesforce, and Google, also face a nuanced threat. While they possess vast resources and proprietary AI stacks, their inherent bias towards their own ecosystems makes it challenging for them to serve as a truly neutral, cross-platform AI layer. If Glean can establish itself as the vendor-agnostic intelligence fabric for multi-cloud and multi-application environments, it could bypass the walled gardens of these tech giants, carving out a significant and independent share of the enterprise AI market.
Over the next 18-36 months, we anticipate an intensified battle for this foundational AI layer. Glean’s immediate challenge will be scaling its integrations and demonstrating measurable ROI across diverse enterprise clients. Expect major cloud providers to redouble efforts to extend their own AI capabilities beyond their native application suites, potentially through aggressive acquisition strategies or by forging deeper integration partnerships. The market will likely see a push towards greater interoperability standards for enterprise AI, driven by customers demanding flexibility and avoiding vendor lock-in. Ultimately, the success of any contender will hinge on its ability to offer unparalleled data security, accuracy, and a genuinely comprehensive view of corporate knowledge, regardless of its origin.
The contest to own the enterprise AI underlayer represents the next frontier in business technology, fundamentally reshaping how organizations access and leverage their intelligence. Enterprises must critically evaluate their AI strategy, considering whether to invest in an independent, unifying intelligence layer to avoid future fragmentation and unlock the full transformative potential of AI.