OPINION — There’s a profound assumption embedded in much of today’s conversation about AI and intelligence: better technology will solve our core problems. We need new infrastructure, better models, and faster processing—all tied to our unique data.
But step inside most intelligence workflows and a different reality emerges.
We are not constrained by what we can collect. We are constrained by what we can prioritize, interpret, and act on in time to matter.
The System Was Built for a Different Problem
The modern intelligence system was designed for a world defined by scarcity. Collection was difficult. Access was limited. Processing was slow. The intelligence cycle—collection, processing, analysis, dissemination—reflected those constraints. It imposed structure, discipline, and rigor on a problem set where information was hard to come by. That system worked because it matched the environment but the environment has changed.
Today, across open sources, commercial capabilities, and traditional collection, we operate in a world of persistent access and expanding data. AI is accelerating that shift, enabling faster processing, broader pattern recognition, and near-instantaneous assessments.
And yet, the underlying system—the way we task, integrate, evaluate, and deliver intelligence—has not fundamentally adapted.
The Constraint Has Moved
Much of the current focus remains on improving inputs: faster infrastructure, better models, more data. These are necessary but insufficient.
The constraint is no longer what we can collect or even what we can analyze. It is how effectively we prioritize what matters, integrate signals across sources, apply judgment at speed, and connect insight to decision in time to matter
In short, the constraint has moved from capability to tradecraft.
AI Is Compressing the Cycle—But Only at the Edges
AI is already changing parts of the intelligence workflow. Signals and geospatial intelligence processing that once took hours can now happen in minutes. Pattern recognition is functionally limitless and immediate. The era of the needle in the haystack is over. Draft assessments can be generated in seconds.
These capabilities are real but have not been fully implemented—nor can they be because the system still operates sequentially. Tasking decisions remain episodic; data integration is still a manual fight; and validation and coordination follow legacy timelines.
The result is a growing mismatch between what technology enables and what the system can absorb. We are accelerating pieces of the intelligence cycle without redesigning the cycle itself.
Tradecraft, Not Technology, Is Now the Limiting Factor
This is the call to action that will define the American Intelligence Community’s success in the next decade. If intelligence continues to operate as a linear process optimized for scarcity, then adding speed and scale at individual stages will produce diminishing returns.
The harder problem—and the more important one—is rethinking how intelligence is done:
- How do we move from periodic tasking to dynamic prioritization?
- How do we integrate AI into workflows as a default starting point, not an add-on?
- How do we preserve rigor while operating at machine speed?
- How do we ensure intelligence is informing faster, more diffuse, policy?
The Most Important Shift—Flattening the Intelligence Cycle.
The intelligence cycle was designed as a sequence: tasking, collection, processing, analysis, dissemination. Each step informs the next. Each stage has ownership. Each handoff introduces control—and delays.
This structure makes less sense today because collection is persistent, data is abundant, and processing is near-instantaneous. More importantly, policymaking is now dynamic—minute by minute—not defined by a once-a-day President’s Daily Brief and not constrained to the Oval Office.
How can we reimagine the intelligence cycle to account for these realities?
Let’s start by leveraging the real world and admitting that this change is not as radical as it sounds. During fast-moving crises, analysts often bypass formal cycles—pulling from multiple sources in real time, integrating signals as they arrive, and engaging directly with policymakers in an ongoing dialogue rather than through finished products.
For example, we did this out of necessity for counterterrorism operations over the last 25 years. Intelligence and operations were increasingly fused out of necessity. Collection and analysis informed action in near real time, and action reshaped collection and analysis priorities just as quickly. The formal cycle existed—but it was not how the work happened. Counterterrorism operational tradecraft set a model for where the system is heading.
The traditional cycle moves information through stages. The flattened cycle moves decisions through a system. The difference is subtle but profound.
In a flattened intelligence cycle:
- Collection and analysis are intertwined. Some of the best analysts I know were case officers serving in the field.
- Processing is not a step. It is largely automated with humans on the loop.
- Dissemination is not an endpoint—it is an iterative relationship with policymakers.
Flattening the intelligence cycle does not mean abandoning rigor or structure. It means redesigning the system to move at the speed of the real world, automating rote tasks, and putting our nation's best and brightest minds on the hardest truly-human tasks.
What Comes Next
This is the first in a series examining how emerging technology—particularly AI—is reshaping the intelligence system in practice.
In my following posts, I’ll focus on where this tension is most visible today, especially in collection and analysis.
The Cipher Brief is committed to publishing a range of perspectives on national security issues submitted by deeply experienced national security professionals. Opinions expressed are those of the author and do not represent the views or opinions of The Cipher Brief.
Have a perspective to share based on your experience in the national security field? Send it to Editor@thecipherbrief.com for publication consideration.
Read more expert-driven national security insights, perspective and analysis in The Cipher Brief
