AI is everywhere—transforming the workplace and driving efficiency, productivity, and deeper data insights. For financial services organizations, the question is no longer whether to use AI, but how and where to use it most effectively. At the forefront of those discussions is Digital Communications Governance and Archiving (DCGA). Gartner predicts that “By 2030, 70% of enterprises using DCGA solutions will adopt AI-driven features and processes, up from 40% in 2025, due to increasing data complexity and governance demands.”
When it comes to how these tools are being used, Gartner Peer Insights explains that “Organizations utilize DCGA solutions to proactively manage, monitor, collect, and archive communications content. They are critical to an organization’s efforts to meet a growing number of regulatory compliance mandates and an expanding scope of organizational communications governance and data insights.”
From Zoom transcripts to Microsoft Teams chats, digital whiteboards, and now AI‑generated summaries and responses (aiComms), financial services firms are overwhelmed. Compliance reviewers struggle to keep up with the vast volumes of complex, intertwined communications—often drowning in false positives and missing key contextual cues and meaning. This is where AI comes in.
AI is transforming the supervision of communications
94% of financial services firms report that they are using—or planning to use—AI‑based detection capabilities. As described in the Financial Industry Regulatory Authority’s report on AI Applications in the Securities Industry, AI technology offers firms the ability to capture and surveil large amounts of structured and unstructured data in various forms (e.g., text, speech, voice, image, and video) from both internal and external sources in order to identify patterns and anomalies. This enables firms to holistically surveil and monitor functions across the enterprise, as well as monitor conduct in a more efficient, effective, and risk-based manner.
This article explores AI in action—showing practical examples of how firms are using AI in DCGA tools to drive efficiency and enhance productivity while meeting their regulatory obligations.
1. AI for summarizing communications content
DCGA tools use AI to analyse diverse communication content, including extracting insights from images and supporting multilingual translation. By analysing conversations across various modalities and languages—including video, audio, chat and AI interactions—Theta Lake generates summaries that capture key details such as themes and participants.
With 82% of firms using at least four communication and collaboration tools, from Zoom, Slack and Microsoft Teams to Asana, Monday.com and Mural, the ability to summarize large volumes of text and visual information is particularly valuable for supervision. This efficiency reduces the time and manual effort required to extract essential information and risks. It allows firms to expedite compliance reviews where large volumes of communication data must be analyzed, prepare for regulatory inquiries with rapid insight into the context of interactions, and check data prior to sending to outside counsel.
2. AI for summarizing communications over time
AI can be leveraged to turn fragmented communications into coherent summaries allowing compliance reviewers to understand and act on data faster.
For example, Theta Lake automatically reconstructs and summarizes entire conversation histories into digestible snippets. These conversation summaries allow organizations to condense weeks- or months-long chats and multi-platform conversations making it easier for compliance teams to quickly review and understand the essence of hours of communications. The AI increase the speed of supervision, helping reviewers work more effectively and ensuring compliance teams can pinpoint risks with ease.
3. AI for detecting risks, concerns and items of interest in communications
AI is leveraged to detect risks across multiple modalities—including voice, video, chat, email, and AI intercations—interpreting contextual information like images, GIFs, and reactions.
To illustrate, Theta Lake leverages ML and NLP to identify compliance, privacy and security risks in what is spoken, shown, or shared. This allows firms to detect when a confidential report appears on a screen share, whether an AI notetaker is present, or if a required disclaimer was provided during a meeting. These detections can be highly refined; for example, a market abuse alert might only trigger when specific employee groups use emojis like 🚀 or 💰.
Because this multi-layered AI understands full context rather than just matching keywords, it is resilient to misspellings, transcription errors (e.g., “WhatsUp” vs. “WhatsApp”), or poor-quality OCR scans that traditional lexicon-based tools might miss. In addition, AI-driven behavioral analytics now go beyond detection to construct a comprehensive narrative – for example identifying clusters of MNPI triggers, anomalous communication patterns, and unexpected participant networks to fill the ‘contextual gaps’.
This precision enables more efficient and effective oversight by review teams, with dramatically less time wasted on false positives. It also enables firms to confidently roll out new communications and productivity features, ultimately reducing the reliance on unapproved communication tools.
4. AI for uncovering risky behaviors and content in AI tools
AI detections also provide governance oversight for the use of AI capabilities and tools that organizations support productivity such as Microsoft Copilot and Zoom AI Companion.
The prompts and responses from Generative AI chatbots may contain sensitive or confidential firm information like customer names, employee data, intellectual property, or other proprietary details. In some scenarios, prompts and responses may present cybersecurity risks such as attempts by employees to circumvent or compromise firm or third-party technical controls through jailbreaking prompts.
By leveraging Theta Lake’s forensic-level inspection of AI interactions, organizations can identify sensitive data exposure, monitor for missing disclosures, and detect risky user behavior. This comprehensive oversight allows firms to govern these ‘aiComms’ effectively, enabling employees to harness the efficiency of AI without compromising security or disrupting workflows.
5. AI for pinpointing where risks occur in communications
AI provides significant efficiencies for the review and analysis of cross-platform communications.
Employees routinely conduct conversations across a variety of platforms in and out of the office–starting a thread on chat and moving to email, social media, mobile, and beyond. Capturing and displaying these fragmented threads in a single, unified view mirroring the multi-platform reality of the modern workplace, allows compliance teams to review cross-platform interactions more efficiently.
Theta Lake’s visual interface uses AI to pinpoint where its AI detections have flagged specific risks, highlighting relevant sections of a conversation so reviewers can immediately focus on what matters.This “single pane of glass” interface directs reviewers to the exact moment a sensitive topic—like a confidential report—was discussed in a meeting, chat, or call or uploaded to an AI tool. By pinpointing where the risks occurred, enables a human reviewer to make the final decision on the action required.
6. Summarizing AI decisions for explainability
AI powers enhanced explainability, injecting transparency directly into the compliance oversight process. AI explainability features summarize exactly why a specific communication was flagged as risky, providing firms with the defensibility and comfort needed to trust and explain why an AI model detected what it detected.
For instance, Theta Lake uses a detection annotation feature to provide a plain-language rationale for the triggering of a particular AI risk detection directly in the platform. If a conversation triggers a collusion detection, the system might point to specific phrases like “keep this between you and me” or a “zipper-face” emoji as evidence of an attempt to obscure information.
The “audit-ready” summary generated when the AI identifies a risk, allows human reviewers to easily verify the alert and defend the decision to regulators.
AI in Practice
These practical examples demonstrate how AI in Digital Communications Governance and Archiving has moved into functional, everyday use. Firms are moving past the unsustainable manual review processes of the past and efficiently managing the complexities of modern communications to meet regulatory obligations. Leveraging AI for supervision allows compliance teams to maintain complete oversight of communications and AI interactions without sacrificing productivity, enabling firms to use the tools that support business growth rather than restricting them.
More details of AI capabilities can also be found in the UK Financial Conduct Authority’s AI Spotlight which showcases Theta Lake as an example of how AI can drive positive change in financial services.
