- HEADLINE + INTRO
Glean and the land grab for your company’s AI nervous system
Every large company is about to answer a deceptively simple question: who owns the brain that sits on top of all our data and tools? Not the LLM itself, but the connective tissue that knows your org chart, permissions, projects and processes – and then quietly automates work in the background. That is the layer Glean is trying to control. In this piece, we will not rehash TechCrunch’s podcast, but unpack what this battle for the enterprise AI layer really means, why it is happening now, and why the choice your CIO makes in the next 12–24 months will be very hard to unwind.
- THE NEWS IN BRIEF
According to TechCrunch’s Equity podcast, enterprise search startup Glean is repositioning itself as an AI work assistant that sits underneath other AI experiences inside a company. Founder and CEO Arvind Jain explained at Web Summit Qatar that Glean plugs into internal systems, respects existing permissions and governance, and then brings intelligence into the tools where employees already work.
TechCrunch reports that Glean, backed by major VCs, raised 150 million dollars at a 7.2 billion dollar valuation in June of last year, signaling strong investor belief that there is room for an independent AI platform layer even as giants like Microsoft and Google bundle AI into their suites. The conversation focuses on how enterprises are thinking about AI architecture, the current consolidation wave, and the difference between practical automation and overhyped AI agents.
- WHY THIS MATTERS
What Glean is chasing is not another chatbot; it is a strategic control point. In every generation of enterprise IT there has been such a point: the operating system on the desktop, the email and collaboration suite, the mobile device platform, the identity provider. The AI work layer is the next one.
Whoever wins that layer will effectively mediate access to knowledge, workflows and eventually decisions across the organisation. That is power. It is also margin: platform owners can take a cut of every adjacent tool, influence which vendors survive, and lock in customers for a decade.
In the near term, enterprises stand to benefit from this platformisation. Instead of each department wiring up its own LLM, retrieval system and permissions logic, a shared AI layer promises consistency: one place to define who can see what, one audit trail, one set of guardrails. Security teams get fewer unknowns; compliance teams get clearer documentation; CFOs get fewer overlapping pilots.
The losers, at least initially, are point-solution vendors that bet on AI features as their main differentiation. If Glean – or a rival – can simply expose a generic but smart assistant inside Outlook, Slack, Jira or Salesforce, then niche tools that mainly surface information via chat start to look redundant.
For internal IT teams, the risk is architectural lock-in. Choosing an AI layer is not like buying another SaaS dashboard. It embeds into your graph of people, documents, permissions and workflows. Ripping it out later could be as painful as migrating off your primary identity provider or CRM.
- THE BIGGER PICTURE
Glean’s repositioning fits neatly into three broader trends.
First, the shift from chatbots to agents and workflows. Large vendors are moving fast: Microsoft is pushing 365 Copilot deeper into business processes, Google is weaving AI into Workspace and its security stack, Salesforce has Einstein, Atlassian has Atlassian Intelligence, and Slack, Notion and others are racing to turn static UIs into action-driven assistants. The real value is no longer answering questions, but quietly completing tasks.
Second, the return of the middleware story. A decade ago, companies like MuleSoft, Okta and ServiceNow became critical by solving connective problems: integration, identity, ticketing. The AI era needs a similar middle layer – something that sits between raw models and end-user applications, understands the enterprise graph and orchestrates tools. Glean is essentially arguing that enterprise search is the natural starting point for that.
Third, consolidation. TechCrunch rightly highlights that enterprises are overwhelmed: too many models, too many pilots, too many vendors. History suggests that after every experimentation wave comes a consolidation phase where a small number of platforms standardise how things are done. It is not hard to imagine a future where a typical enterprise uses one or two AI orchestration layers, plus a handful of specialised apps.
Against this backdrop, Glean is positioning itself as the neutral brain that can sit across Microsoft, Google and everyone else. But neutrality is a fragile business model if the giants decide that owning the brain is non‑negotiable.
- THE EUROPEAN / REGIONAL ANGLE
For European organisations, the AI layer question is inseparable from regulation and digital sovereignty.
The EU’s GDPR already makes uncontrolled data flows to US clouds a legal headache, and the EU AI Act – politically agreed in 2023 and moving through formal adoption – will bring additional obligations around transparency, risk management and human oversight. An AI work assistant that touches HR data, contracts and customer records is squarely in the high‑risk zone from a compliance perspective.
That means European CIOs must ask not only: does this tool boost productivity? but also: where does it run, which models does it use, how are logs stored, can we prove that permissions are enforced and bias risks are managed? Providers that can offer strong data residency, robust audit trails and flexible deployment (including private cloud or on‑prem) will have an edge.
There is also a local competition angle. Europe already has strong enterprise search and knowledge platforms – for example, French‑based Sinequa or the search offerings from Elastic – and a growing ecosystem around open models such as Llama. These players can, in theory, evolve into AI work layers tailored to European regulatory and language realities.
Finally, many European companies are already deeply invested in Microsoft 365, SAP and ServiceNow. For them, bringing in a Glean‑like neutral layer means accepting additional complexity in exchange for avoiding single‑vendor dependency. Some will gladly make that trade; others will double down on their primary suite and live with the lock‑in.
- LOOKING AHEAD
Over the next two years, expect three things.
First, a brutal feature race. Glean and its direct competitors will need to prove they can go beyond clever retrieval and actually drive measurable business outcomes: fewer tickets, faster onboarding, shorter sales cycles. The bar will be set by whatever Microsoft and Google ship natively. If the bundled assistants become good enough for 80 percent of use cases, independents must own the remaining 20 percent that really moves the needle.
Second, a governance reckoning. Early pilots can get away with loose processes; large‑scale deployment cannot. Boards will start asking for AI usage reports, regulators will issue guidance, and auditors will request logs and documentation. Vendors that invested early in permissions, policy engines and explainability – themes highlighted on the TechCrunch podcast – will look prescient.
Third, consolidation and acquisition. It is plausible that one or more independent AI work layers will be bought by a cloud or SaaS giant that wants to accelerate its own roadmap. Conversely, we might see a few independents carve out sustainable niches by focusing on specific verticals (for example, healthcare, legal or industrial) where domain‑specific knowledge and strict regulation make generic assistants less attractive.
For technology leaders, the practical move in 2026 is experimentation with architectural intent. Do not just run random pilots; run experiments that help you answer a strategic question: do we want the AI brain to live inside our main suite, inside a neutral third‑party, or closer to our own infrastructure using open‑source components? Once that decision solidifies, everything else – vendors, contracts, skills – will follow.
- THE BOTTOM LINE
The fight Glean is entering is not about another AI feature; it is about who controls the nervous system of the modern enterprise. Independent platforms offer choice and potentially stronger governance, but they are swimming against a tide of bundled AI from incumbents that already own the desktop and the cloud. The decision your organisation makes on this layer will be hard to reverse. Before you sign a multi‑year contract, ask yourself: whose incentives do I want wiring together the brains of my company?
