---
title: "U.S. Intelligence Community adapts to ubiquitous information through open-source AI-enabled multi-sector partnerships in the United States; open-source intelligence agency proposed"
sdDatePublished: "2026-08-28T05:11:00Z"
source: "https://www.ibm.com/businessofgovernment/reports/learning-across-the-divide"
topics:
  - name: "espionage and intelligence"
    identifier: "medtop:20000605"
  - name: "artificial intelligence"
    identifier: "medtop:20001298"
  - name: "computer security"
    identifier: "medtop:20000229"
  - name: "business service"
    identifier: "medtop:20001371"
  - name: "public officials"
    identifier: "medtop:20000596"
locations:
  - "United States"
---


U.S. Intelligence Community adapts to ubiquitous information through open-source AI-enabled multi-sector partnerships in the United States; open-source intelligence agency proposed

LEARNING ACROSS THE DIVIDE: Multi-Sector Partnerships in Intelligence

A consequential question in national security involves how government intelligence should adapt to a world of ubiquitous information. As Mr. Treverton’s report makes clear, the intelligence enterprise built for a world of scarce and secret information now has access to an overwhelming amount of open information. Moreover, the public-private divide that once separated official intelligence from other information has become far more porous. Author: Gregory F. Treverton, chair of the Global TechnoPolitics Forum A consequential question in national security involves how government intelligence should adapt to a world of ubiquitous information. As Mr. Treverton’s report makes clear, the intelligence enterprise built for a world of scarce and secret information now has access to an overwhelming amount of open information. Moreover, the public-private divide that once separated official intelligence from other information has become far more porous. These realities reflect the daily experience of intelligence leaders as opensource investigators, business intelligence firms, and artificial intelligence (AI) startups increasingly work in areas that intelligence agencies once considered theirs alone. Traditional tradecraft—such as placing spies under cover, controlling sources, and using classified channels—often do not meet today’s intelligence needs. Mr. Treverton brings a rare vantage point to the topic. His experience includes chairing the National Intelligence Council, directing research centers at RAND, and decades of engagement with the practice and policy of intelligence. Drawing on this background, he reframes multi-sector partnerships as far more than contracting arrangements. Working across the public-private divide gives the U.S. Intelligence Community an opportunity to redesign how it collects, shares, and uses information. Many past efforts to engage the private sector have focused on procurement processes; this report turns to the deeper cultural and organizational shifts required to go further. The report opens with an examination of how the open-source revolution has transformed the intelligence environment and what this change demands of the Intelligence Community. From there, the author explores multi-sector collaboration across several interconnected dimensions: the current state of contracting and its limits, the promise and risks of artificial intelligence, and models for public-private engagement drawn from decades of experience. He also examines the broader implications of treating intelligence as a public good. The report focuses on several topics. First, Mr. Treverton treats the shift from scarcity to abundance of information as a defining fact of the current era, contending that agencies serve policymakers best when they move beyond secrecy for its own sake. His account of open-source intelligence—its accessibility, its diversity of sources, and its vulnerability to noise and disinformation— gives leaders a clear-eyed framework for weighing its value alongsideits risks. Second, the report’s survey of past multi-sector models deserves attention. These efforts, some thriving and some short-lived, offer concrete lessons on how to establish lasting relationships among government, academia, and industry. Third, the report closes with a set of recommendations: creating a dedicated open-source intelligence agency, leveraging responsible use of AI as a tool to improve analysis, and facilitating easier interchange of talent between government and the private sector. These recommendations translate the report’s analysis into a practical agenda for action. This report represents a valuable contribution to a sustained body of work on government adaptation and innovation that the IBM Center has developed over many years, including most recently The Innovation Adoption Kit. We hope Mr. Treverton’s insights will offer value to a broad audience, which includes intelligence executives navigating the boundary between classified and open sources, policymakers who depend on timely and trustworthy analysis, and the wider community of scholars and practitioners thinking about how institutions can best adapt in an age of ubiquitous information.