In the coming years, AI is expected to dramatically accelerate the evolution of lawful intelligence, giving law enforcement agencies (LEAs) the ability to efficiently draw insight from data at unprecedented scale. Investigators will use intelligent systems to analyze data from large numbers of sources, such as lawfully intercepted data, location information, open source intelligence, and social media. AI automates analysis, correlating data points together to recognize the patterns and anomalies that reveal context and significance.
As the technology matures, it offers great promise as a resource multiplier for investigators, streamlining the process of transforming information into evidence. The emerging next generation of AI-based automation will be based on sophisticated, self-directed entities called AI agents that work toward specific goals autonomously, using human-like planning, perception, and decision making.
Like generative AI (GenAI) solutions, AI agents draw on large language models (LLMs) to understand and process language. Whereas GenAI is focused on generating outputs such as text, images, or code, however, AI agents interpret real-world dynamic data to self-direct their progress on tasks assigned by investigators. A semantic understanding of the data and its context is used to break goals down into smaller tasks, then assemble those tasks into workflows and complete them.
The Supporting Role of AI Agents in Investigations
By taking on tedious, time-consuming tasks, AI agents will improve the efficiency and effectiveness of human investigators, building on current capabilities. For example, sifting through massive collections of data for insights, investigators inevitably often run into investigative dead ends that consume their time and resources. By pursuing leads autonomously, AI agents eliminate that overhead and allow human investigators to think strategically.
Likewise, agents can prioritize sources of streaming or stored images and video, then analyze them in search of specific people and objects. They can apply algorithms for predictive analytics to identify and investigate potential public threats and criminal activity based on historical data. AI agents are well suited to monitoring online traffic to identify fraud, cyberattacks, and other activities. They can also pursue administrative goals, such as automating report generation and organizing case files efficiently. AI agents apply a variety of tools and technologies to their goals, including the following:
- Machine learning algorithmically enhances the accuracy of AI systems over time, to provide better understanding and prediction of criminal behavior and threats.
- Natural language processing interprets the meaning of recorded spoken audio, transcribes it for easier handling and querying, and analyzes those transcripts alongside other text sources such as email and social media.
- Computer vision interprets visual data such as video sources, maps, and satellite images for usages such as automated number plate recognition and forensic image enhancement.
- Data fusion and big data analytics ingests huge amounts of data from diverse structured and unstructured sources, analyzes it as a single coherent entity, and yields insights to advance investigations.
- Blockchain and digital forensics ensure data integrity and auditability, providing insight into its provenance and irrefutably documenting the digital signs of criminal activity.
Benefits and Cautions for a New Technology Era
New LEA efficiencies and greater reach and insight into digital footprints of interest will be possible with AI agents. At the same time, the autonomy behind those benefits holds potential downsides by distancing human investigators from the process. Maintaining the right balance between technology and human judgment will require ongoing collaboration among policymakers, technologists, and LEAs, among others. Legal guardrails that have yet to be established will need to preserve the benefit of AI agents to lawful intelligence while protecting civil society against missteps.
Agentic AI use cases will let analysts send out swarms of digital investigators to follow up on leads in real time, pursuing more avenues without dividing attention and resources. Unlike human investigators, the ability of AI agents to act on new data at any scale almost instantaneously makes it possible to look deeply into an open-ended number of data sources. Decisions by well-defined systems are based on objective data, reducing the effects of human error, bias, and prejudice. They advance cases with 24/7 operation, for continuous oversight and alerting to events of interest, while deciding on courses of action and pursuing them without requiring investigator resources.
To make these capabilities viable, a number of practical and ethical concerns must be overcome. Agents will require deep contextual understanding to make nuanced judgments without human involvement, and safeguards must be put in place to avoid overreach and negative outcomes from misinterpretation. Limited human intervention and oversight around autonomous systems raises potential concerns about accountability and ethical decision-making. They must also be well protected against adversarial attacks that might cause misinterpretation of evidence or misdirect investigations.
AI agents will certainly figure largely in the future of AI-driven investigations. SS8 is committed both to advancing the technology and to advocating for legal frameworks that ensure due process, data privacy, and protection.
About Dr. Cemal Dikmen
As SS8’s Chief Technology & Security Officer, Cemal plays an integral role in the company’s strategic direction, development, and future growth. A renowned expert and thought leader in the legal compliance and communications analysis domain, he has been a frequent speaker at various industry conferences over the past 10 years. Cemal holds BS, MS, and PhD degrees in Electrical Engineering. You can learn more about Cemal on his LinkedIn profile by clicking here.
About Syed Hussain
Syed has over 20 years of experience in cybersecurity, interception, and data intelligence, with leadership roles in both Engineering and Product Management. As Vice President of Product Management for SS8’s Lawful Intelligence Products, he brings deep technical expertise in nationwide security, law enforcement, and service providers. He has led the architecture and design of cloud-based interception for signaling, metadata, and content in 5G and Mobile Edge Computing. Syed represents SS8 in ETSI and 3GPP standard bodies, contributing to various standards and interface specifications. He holds a B.S. in Computer Science & Engineering. You can learn more about Syed on his LinkedIn profile.
About SS8 Networks
As a leader in Lawful and Location Intelligence, SS8 is committed to making societies safer. Our mission is to extract, analyze, and visualize critical intelligence, providing real-time insights that help save lives. With 25 years of expertise, SS8 is a trusted partner of the world’s largest government agencies and communication providers, consistently remaining at the forefront of innovation.
Intellego® XT monitoring and data analytics portfolio is optimized for Law Enforcement Agencies to capture, analyze, and visualize complex data sets for real-time investigative intelligence.
LocationWise delivers the highest audited network location accuracy worldwide, providing active and passive location intelligence for emergency services, law enforcement, and mobile network operators.
Xcipio® mediation platform meets the demands of lawful intercept in any network type and provides the ability to transcode (convert) between lawful intercept handover versions and standard families.
To learn more, contact us at info@SS8.com.
