BETA
Updated: Mar 2
BETA
Updated: Mar 2
Evolving
Last Update: 2/17/2026
Your role’s AI Resilience Score is
41.0%
Median Score
Changing Fast
Evolving
Stable
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
What does this resilience result mean?
These roles are shifting as AI becomes part of everyday workflows. Expect new responsibilities and new opportunities.
AI Resilience Report for
Intelligence Analysts
They examine information to find important details and patterns, helping to keep the country safe by predicting potential threats or dangers.
This role is evolving
The career of an Intelligence Analyst is labeled as "Evolving" because AI is increasingly being used to handle data-heavy tasks, like sorting through reports and finding patterns, which helps analysts work faster and more efficiently. However, human skills such as judgment, creativity, and interpersonal communication are still crucial, as AI can make mistakes and needs oversight.
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View analysisChat with CoachLatest newsMore career infoAnalysisChatNewsMoreThis role is evolving
The career of an Intelligence Analyst is labeled as "Evolving" because AI is increasingly being used to handle data-heavy tasks, like sorting through reports and finding patterns, which helps analysts work faster and more efficiently. However, human skills such as judgment, creativity, and interpersonal communication are still crucial, as AI can make mistakes and needs oversight.
Read full analysisContributing Sources
We aggregate scores from multiple models and supplement with employment projections for a more accurate picture of this occupation’s resilience. Expand to view all sources.
AI Resilience
AI Resilience Model v1.0
AI Task Resilience
Changing fast5.6%
5.6%
Anthropic's Economic Index
AI Resilience
Stable73.6%
73.6%
Will Robots Take My Job
Automation Resilience
Evolving47.8%
47.8%
Medium Demand
Labor Market Outlook
We use BLS employment projections to complement the AI-focused assessments from other sources.
Learn about this scoreGrowth Rate (2024-34):
-0.7%
Growth Percentile:
22.8%
Annual Openings:
7,800
Annual Openings Pct:
48.0%
Analysis of Current AI Resilience
Intelligence Analysts
Updated Quarterly • Last Update: 2/17/2026
What's changing and what's not
Intelligence analysts today often use AI and advanced software to help with data-heavy tasks. For example, one report notes that AI is already being used to “label imagery and sort through vast troves of data, helping humans see the signal in the noise” [1]. In practice, analysts use tools (like data-link software) that can automatically find patterns and connections in massive databases.
In a U.S. drug-trafficking case, an AI system found “twice as many” involved companies and many more suspects than human analysts did, and even produced summaries of evidence, saving “countless work hours” [2] [2]. Similarly, software such as Palantir’s analytics platform helped investigators link people, places, and events from different records in days instead of months [3]. Police departments also employ AI-assisted systems (for example, to scan license plates or analyze phone and social-media data) to flag suspects or crime hotspots faster [4] [4].
These examples show that many routine data tasks are already being automated or augmented by AI: the software does the heavy lifting of sorting and visualizing data, while people interpret the results.
At the same time, many key parts of the job still need human skills. Collecting human intelligence by talking to people, observing in the field, or interrogating suspects remains mostly human work. Analysts must use judgment, creativity, and social skills that AI lacks.
Experts warn that AI models often “hallucinate” (make things up) or reflect bias, so any AI suggestions must be checked by a person [2] [4]. In other words, think of current AI tools as helpful assistants, not replacements: they can scan millions of reports or calls for clues, but humans still review the findings and conduct interviews. As one official put it, you treat AI “like a crazy, drunk friend” – it can give clever ideas, but it can’t be fully trusted without human oversight [2].
Sources
AI in the real world
Law enforcement agencies have strong reasons to adopt AI, so its use is growing where practical. Many departments face huge volumes of data and not enough staff to process it. For example, Axios reports that some police forces are already piloting AI tools that turn body-camera audio into written reports, “shaving hours off paperwork” and helping with staffing shortages [4].
By automating report-writing and scanning video or voice data, AI can free analysts and officers to focus on investigations. Intelligence agencies feel a similar pressure: one news story says U.S. spy agencies are “scrambling” to use AI to handle “exponential” data growth, or risk being overwhelmed [2]. When AI tools work well, they bring big efficiency gains.
In a high-profile case, U.S. agencies paid about £4.8 million a year for an AI analytics system that caught criminals faster than cheaper alternatives [3]. In effect, the financial cost of AI can be offset by the time and cases it saves.
However, adoption isn’t instant. Some hurdles slow it down. Cutting-edge AI systems can be expensive to build and buy, and officers need training to use them properly.
There are also important legal and ethical questions. Civil-liberties groups and oversight bodies warn that unchecked AI could amplify bias or invade privacy, so they push for clear policies and human review [4] [2]. In practice, this means agencies often adopt AI tools slowly and carefully: they invest when the benefits (faster analysis, solved cases) are clear, but they also set rules to ensure fairness and accuracy.
Overall, AI tools are commercially available and can save labor costs, but agencies balance those economic benefits with the need for human judgment and public trust. The upsides of AI include handling massive data and streamlining reports, especially in light of tight budgets and staffing; the downsides include cost, training, and ethical concerns. In the end, experts agree that while AI can take on many routine tasks and improve efficiency, intelligence analysts’ uniquely human skills – critical thinking, empathy, creativity and judgment – will remain crucial [2] [4].
The technology is seen as an assistant rather than a replacement, making the job faster and richer without fully taking it over.
Sources
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More Career Info
Career: Intelligence Analysts
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Employment & Wage Data
Median Wage
$93,580
Jobs (2024)
117,900
Growth (2024-34)
-0.7%
Annual Openings
7,800
Education
High school diploma or equivalent
Experience
Less than 5 years
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Operate cameras, radios, or other surveillance equipment to intercept communications or document activities.
2
Interview, interrogate, or interact with witnesses or crime suspects to collect human intelligence.
3
Gather, analyze, correlate, or evaluate information from a variety of resources, such as law enforcement databases.
4
Gather intelligence information by field observation, confidential information sources, or public records.
5
Study communication code languages or foreign languages to translate intelligence.
6
Predict future gang, organized crime, or terrorist activity, using analyses of intelligence data.
7
Develop defense plans or tactics, using intelligence and other information.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
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