The rapid evolution of enterprise Artificial Intelligence from simple question-answering chatbots to comprehensive systems that execute organizational tasks has raised a critical strategic question. Industry leaders are now examining who will ultimately control the foundational AI layer that powers these advanced workplace functions.
This issue was highlighted in a recent discussion with Arvind Jain, the co-founder and chief executive officer of Glean. The company, which originated as an enterprise search platform, has repositioned itself as a provider of what it terms an “AI work assistant.”
Strategic Shift in Enterprise AI
According to Jain, the focus is shifting from standalone AI applications to a centralized, underlying intelligence layer. This layer is designed to integrate with and support a company’s existing suite of software tools and other AI models. The core function of this infrastructure is to connect to a business’s proprietary data, applications, and workflows.
The objective is to create a unified system that can understand context, retrieve relevant information, and perform actions across different departments. This move signifies a broader industry trend where AI is becoming less of a discrete product and more of a pervasive, connective tissue within corporate technology stacks.
The Central Question of Control
The development of this foundational layer brings the issue of ownership and governance to the forefront. Jain’s commentary underscores a significant debate within the technology sector: whether this critical AI infrastructure will be managed internally by a company’s own IT and data teams, or provided and controlled by external vendors.
This decision carries implications for data security, customization, operational continuity, and long-term strategic flexibility. Companies must consider how much of their core operational intelligence they are willing to outsource. The choice between building proprietary systems or licensing integrated platforms represents a major strategic crossroads for enterprise leadership.
Industry Implications and Future Development
The discussion reflects a maturation in the enterprise AI market. Initial implementations often focused on narrow, task-specific tools. The current direction points toward platforms that require deep integration with a company’s unique digital environment, including its communications, documents, and specialized databases.
This evolution suggests that the value of AI will increasingly be derived from its ability to securely access and reason across an organization’s entire knowledge base. Consequently, vendors in this space are emphasizing their platforms’ capabilities in enterprise-grade security, access controls, and systems integration over standalone features.
Looking ahead, the competition to provide this underlying AI layer is expected to intensify. The coming period will likely see continued development from established enterprise software providers and specialized AI firms alike. Market analysts anticipate that clarity on deployment models, pricing structures, and measurable return on investment will be key factors as businesses move from experimentation to large-scale implementation. The resolution of the ownership question will fundamentally shape how organizations operate and compete in the coming decade.
Source: GeekWire
