The Intelligence Community (IC) has an opportunity now to influence how we talk about, and thus how we approach, AI use in our work by formally adopting the nomenclature “AI-in-the-Loop” rather than “Human-in-the-Loop.” The problem with human-in-the-loop is that it subordinates the human to AI; the term carries a built-in assumption that “the loop” belongs to AI and that humans will somehow be included. The term I am proposing omits the “human” we have become accustomed to, but it is a purposeful attempt to reflect what we want to achieve: using AI when and where we elect to do so.

AI-in-the-loop is not a new expression. Stanford’s Institute for Human-Centered Artificial Intelligence used the term as a centerpiece for a conference on the topic in 2022, arguing that humans should remain in charge while AI operates as part of a human-directed process.

This 2025 academic article makes the same distinction, arguing that “Human-in-the-loop (HIL) systems have emerged as a promising approach for combining the strengths of data-driven machine learning models with the contextual understanding of human experts. However, a deeper look into several of these systems reveals that calling them HIL would be a misnomer, as they are quite the opposite, namely AI-in-the-loop (AI2L) systems: the human is in control of the system, while the AI is there to support the human. We argue that existing evaluation methods often overemphasize the machine (learning) component’s performance, neglecting the human expert’s critical role.”

Much of industry discourse uses human-in-the-loop as an AI governance approach, but the debate over terminology remains unsettled. Researchers at The George Washington University argue this is partly because “Academia, government, and industry have not clearly defined the mechanisms by which humans are expected to oversee or collaborate with AI-enabled systems.” They add that “Inconsistent uses of terms like human-in-the-loop and human-AI teaming create confusion on what type of oversight and collaboration is intended,” calling this environment a “preposition salad.”

Forging new terminology for our AI usage is critical now as we seek to accelerate development and adoption in the IC while also supporting the burgeoning efforts to adopt AI securely. The IC has already set a standard for accelerated adoption in a secure environment while focusing on the human role.

ICD 505, as amended in 2025, on AI underscores the importance of IC personnel, noting that they “shall remain responsible and accountable for the analysis, decisions, and outcomes derived from insights gleaned using AI.” While the Directive does not mandate specific terminology, it requires users to “understand” and be accountable for AI use. It goes further in insisting that “personnel be able to review, challenge, and reject or replace AI-derived recommendations and findings when appropriate.” The President has since mandated that the IC publish a Standard on AI Assurance under ICD 505 and signed a memorandum on AI mandating “responsible acceleration of the use of AI across intelligence and warfighting domains.”

Intelligence agencies are moving to adopt internal AI policies to drive adoption while elevating the human role. For example, NGA has moved beyond simply adopting AI toward aspiring to become an AI-first organization where “AI does not replace human judgment. It amplifies it.”

While the human role is at the forefront, IC procurement is aiming for fast acquisition. CIA launched a new acquisition framework this year to speed adoption of innovative technologies, while NGA has elevated its Rapid Capabilities Office and has multiple major AI and advanced-analytics procurements moving toward solicitation.

An Array of Terminology Options

Practitioners and technologists may bristle at adopting a term that lacks "human," as noted above. This should not derail our efforts to better define our approach to AI. I have offered AI-in-the-Loop as an option that respected experts are promoting. But the IC can forge its own path by considering multiple options:

Human-Led AI (HLAI) — simple, direct, and clear about who leads the process

Human-Guided AI (HGAI) — emphasizes direction and oversight, though it may sound less decisive

Human-AI Teaming (HAIT) — widely used, though it can imply a more equal partnership than intended, and an awkward

acronym

Human-Directed AI (HDAI) — stronger than “guided,” emphasizing human authority

Human-Commanded AI (HCAI) — strong human primacy, though perhaps too military in tone for broad IC use

Human-Owned AI Workflow (HOAIW) — inelegant, but explicit that the workflow belongs to the human

Adopting new terminology now would be more than symbolic; it would help shape how we approach and use AI. We can ensure AI augmentation at the speed of mission as part of the human toolkit, not that humans are just “in-the-loop.” Indeed, the IC has used nomenclature adoption as a core part of improving mission performance and rigor at key junctures in the past.

After 9/11 and the invasion of Iraq, the IC shifted the terminology it used for adopting new or different tradecraft from our baseline techniques in analysis. The term Structured Analytic Techniques became official at CIA’s Sherman Kent School in 2005 as part of the Agency’s effort to promote these methods from the long-held category of “alternative” analysis into the mainstream of tradecraft. In my decades of experience in analysis, this change was more than a title change; the new terminology reshaped how analysts thought about their work. As a junior CIA analyst at the time, I remember a proliferation of structured analytic techniques that became so commonplace they were literally no longer alternative.

In the late 2010s, we shifted from “intelligence sharing,” a process that intelligence professionals I knew detested as giving away secrets for little to no gain, to “intelligence diplomacy,” a practice many of us willingly adopted to offer insights aimed at promoting US interests. The IC formally codified this approach in 2025 through ICD 405, Intelligence Diplomacy. The ICD distinguishes between mere intelligence sharing and intelligence diplomacy, noting that the latter must “be done in support of advancing a preferred policy objective.” The ICD goes further in noting that the intent is to “shape foreign leader perspectives,” a materially different approach than sharing alone. The Senate’s Intelligence Authorization Act in August 2026 endorsed Intelligence Diplomacy as “critical to advancing US foreign policy and national security goals,” and called for “elevating intelligence diplomacy as a tool of US statecraft” through continued investment.

The IC should act with deliberate speed to formalize AI-in-the-loop, or a related term, to set a tone of expectation and clarity for agencies and industry partners that even agentic autonomy must begin with human intent and be wrapped in human decision. We can do so in a presidentially required Standard on AI Assurance under ICD 505. Further, IC directors using an agreed-upon, more human-focused term and impressing on their workforce its importance would chart a path. IC acquisition shops’ requests to industry should also make this shift, giving industry clear guidance that development and implementation should include a workflow that explicitly highlights human ownership of AI adoption. Even when AI does the heavy lifting across data sets that humans can’t process alone at speed and scale, it must do it on our behalf.

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