Special Edition (October 2025)
How AI is affecting the OSINT industry + Challenges & Opportunities
Hi, this is the OSINT-Jobs.com Team. You probably expected the monthly OSINT roundup, but this month is a little different.
We’re excited to share initial results from our 2025 AI & OSINT Community Survey.
We reached out to active OSINT practitioners to better understand how AI has affected their work, what challenges they face, and the opportunities they see.
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First Insights: The 2025 AI & OSINT Community Survey
We reached out to OSINT practitioners across the community to learn how AI has affected their work and what challenges and opportunities they see.
Our team analyzed the data. But we’re not done yet. The more people take part, the more data we can analyze and the more accurate the insights become.
This survey is entirely run by us, and all insights are created for the community.
Anyone can use them for professional purposes. In line with our mission, we hope these findings help OSINT professionals grow their skills and advance their careers.
If you’d like to support our research, please share the survey below with colleagues and others working in OSINT. It’s anonymous and of course, completely free.
Take the survey now: OSINT Jobs Community Survey
Results & Analysis
About the Questionnaire
To collect responses, we designed a structured questionnaire built around key elements of the so-called ‘intelligence cycle’, from planning and collection to analysis and reporting.
Participants were asked about their professional background, years of experience, and the main focus of their OSINT work. They could then select how they use AI, how often, and in which parts of their workflow it provides the most value.
The survey also explored current challenges, skills gaps, and perceived risks or opportunities linked to AI adoption. Multiple-choice questions were combined with open text fields to allow respondents to share detailed experiences and examples.
By combining both quantitative and qualitative inputs, the questionnaire provided a balanced view of how AI is currently shaping OSINT work and where practitioners feel the biggest needs, gaps, and opportunities lie.
1. Who Took Part in the Survey
We received 31 responses from OSINT practitioners across a wide range of professional backgrounds.
The majority of participants identified as OSINT Analysts and Intelligence Analysts, followed by professionals from law enforcement and government, journalism, and threat intelligence research.
Experience levels varied, but most respondents have 5–9 years or 10+ years of experience in their respective fields. This shows that the insights collected come from seasoned professionals.
We also heard from students, researchers, and online investigators, adding valuable perspectives from those entering or exploring the field from different angles.
In total, these 31 responses provide a first snapshot of how AI is affecting the OSINT community. But to make the findings even more representative, we’re encouraging more practitioners to take part. Every additional response helps make the insights more complete and more useful for everyone in the community.
2. What Practitioners Focus On
When we asked respondents about the main focus of their OSINT work, a few clear themes emerged.
The largest share of professionals reported working on entity of interest investigations, due diligence / background checks, and corporate / financial investigations.
We also saw strong representation from those engaged in geopolitical analysis, mis/disinformation analysis, and fraud investigations highlighting OSINT’s vital role in these important areas.
Smaller but still important portions of respondents mentioned market and competitor analysis, human rights investigations, and cyber threat intelligence.
Overall, the data shows that OSINT is not confined to one niche. In fact, it’s a diverse field where practitioners use open data to solve problems in various areas.
3. The Top Challenges OSINT Professionals Face
Across all responses, a few clear challenges stood out. These are issues that many practitioners in the OSINT space will probably recognise.
1. Tool limitations and costs
Many professionals noted that the tools available today are often expensive, fragmented, or outdated, making it harder to maintain consistent workflows. Several respondents also mentioned frustration with data sources hidden behind paywalls, limiting access to critical information.
2. Data access and collection issues
As platforms restrict access to open data, analysts find it increasingly difficult to collect information from social media, private sources, and regulated environments. These limitations directly affect the depth and accuracy of investigations.
3. Information overload and validation
A recurring pain point was the struggle to manage, filter, and verify the growing amount of data available online. Practitioners highlighted the constant challenge of distinguishing reliable insights from noise, especially in fast-moving or high-stakes investigations.
4. Keeping up with rapid change and learning
The OSINT field evolves quickly. New tools, techniques, and platforms emerge almost weekly, making it hard for analysts to stay updated and maintain skills.
5. Privacy, security, and compliance concerns
Finally, practitioners expressed growing concerns about data privacy, ethical use, and compliance, especially as AI tools become part of daily workflows. Regulatory frameworks, particularly around EU and AI data laws are adding new layers of complexity that many teams struggle to navigate.
Together, these challenges reveal the realities of working in modern OSINT. Professionals must balance technical, ethical, and legal pressures while adapting to an environment that’s changing faster than ever.
4. How Often AI Is Used in OSINT Work
AI is no longer a niche add-on. It’s part of daily workflows.
More than half of respondents said they use AI-based tools every day, while others reported using them occasionally or weekly. Only a small fraction said they rarely or never use AI.
This shows that AI has already become a routine element in open source investigations.
5. How Practitioners View AI in OSINT
Overall, respondents expressed a mostly positive and practical attitude toward AI, though opinions varied.
Many described AI as a useful productivity and writing tool, especially for report drafting and summarisation. For these professionals, AI helps streamline workflows and save valuable time, particularly when working with large volumes of data or text.
Others viewed AI as valuable but imperfect, emphasising that it still requires human oversight and tradecraft. They noted that while AI is powerful, it can make mistakes and should be used with caution.
A smaller group expressed skepticism and trust concerns, particularly regarding bias, accuracy, OPSEC, ethics, and compliance. Some respondents worry about the trustworthiness of AI-generated outputs and the risks of overreliance.
At the same time, a significant portion of the community sees AI as essential and transformative, describing it as a “must-have” that boosts productivity and efficiency in day-to-day OSINT work.
A few respondents raised issues around costs and capability limitations, saying that top-tier systems remain expensive or not yet mature enough for advanced collection tasks.
While one respondent even mentioned being replaced by AI, this was an outlier. The overall sentiment remains optimistic, with most professionals actively using AI but remaining cautious about reliability and ethics.
These findings highlight a clear divide among the respondents. Enthusiasm for AI’s productivity gains on one side, and apprehension over accuracy, bias, and long-term implications on the other.
6. How AI Is Used in OSINT Work
Respondents were asked to select from a list of tasks we created based on the main stages of the intelligence cycle, showing where AI currently fits into their OSINT workflows.
The most common use was for collection tasks such as automating or enhancing data gathering from online and social media sources. This was followed by analysis tasks, where AI helps make sense of large datasets, summarise text, and extract entities or patterns.
AI is also used for processing and structuring data, turning unstructured information into usable formats.
In production tasks, respondents said AI assists with writing, summarisation, and presentation, helping analysts prepare reports faster and more efficiently.
A smaller share mentioned planning tasks like keyword identification and search strategy design, while a few noted organisation-specific uses that fall outside standard categories.
Overall, AI is clearly becoming embedded across the OSINT workflow. Not replacing tradecraft, but amplifying it.
7. Skills Most Commonly Lacking in OSINT Teams
When asked which skills are most often missing in OSINT teams, several clear patterns emerged.
The most frequently mentioned gap was technical proficiency, particularly in scripting, automation, and API-based data collection or processing. This appeared in nearly all responses, underscoring the growing need for technically skilled analysts.
A close second was the lack of standardised methodologies. Many teams struggle with consistent processes, naming conventions, and structured evaluation frameworks, which limits the reproducibility and reliability of OSINT work.
Language skills also stood out as a significant weakness. Respondents noted difficulties interpreting multilingual content and understanding nuanced language, both crucial for accurate analysis.
Other common gaps included data analysis, verbal reasoning, and verification skills such as geolocation. These indicate that while many professionals can collect data effectively, turning it into validated, meaningful insights remains a challenge.
Finally, a smaller number mentioned weaknesses in report writing and communication, particularly when summarising findings or presenting results to stakeholders.
Overall, the results show that technical and methodological skills dominate the list of missing competencies, but soft skills, including language and reasoning, are nearly as important. Together, they highlight the need for balanced, cross-disciplinary capabilities across OSINT teams.
Final Thoughts
The first results already paint an interesting picture of how AI is influencing today’s OSINT practitioner.
But this is just the beginning. With only 33 responses so far, every new submission adds real value and helps us build a clearer, more representative view of our industry.
We plan to update and expand this report as more practitioners take part. So if you haven’t filled out the survey yet — or know others who should — please take a few minutes to contribute and share it with your network.
Your input helps strengthen the entire OSINT community and ensures that the insights we share reflect real, evidence-based experiences from professionals like you.
👉 Take the survey
Thank you!