Artificial intelligence has moved well beyond being a simple productivity tool. Today, platforms such as Microsoft Copilot, Zoom AIC, Anthropic’s Claude, and Google Gemini are functioning as active, native participants in the digital workplace — generating outputs, joining meetings, and interacting with both humans and other AI systems in real time.
“The mandate to deploy AI is urgent, but urgency must not lead to excessive risk-taking. Success requires balancing rapid innovation with risk discipline. We enable organizations to execute their AI strategies effectively while unlocking deep insights into their AI investments.”
– Dan Nadir, Chief Product Officer, Theta Lake
According to Theta Lake, this shift has given rise to a new category of communications known as “aiComms” — a term encompassing all human-to-AI and agent-to-agent interactions, and creating an entirely new set of user behaviors. As AI becomes embedded in daily workflows, enterprises face a pressing question: how are employees using it, what are their intentions, and who is governing these conversations?
The risk landscape surrounding aiComms is evolving rapidly and does not fit neatly into traditional compliance frameworks. Unlike conventional workplace communications, AI-generated exchanges tend to be verbose, sprawling, and difficult to investigate retrospectively. Compounding this, the intent behind problematic interactions is not always clear-cut.
Risk professionals must now contend with a spectrum that ranges from deliberate, malicious information gathering to well-intentioned but accidental data exposure. Add to this the risks of prompt manipulation, model hallucination, and the inadvertent leakage of sensitive data, and it becomes apparent why governance specialists are paying closer attention to how AI systems communicate within organisational environments.
Addressing these risks requires more than conventional security tooling. A robust aiComms governance framework begins with data enrichment — supporting existing systems such as Security Information and Event Management (SIEM) platforms by capturing AI conversations in their full context, preserving nuance, intent, and the behavioural signals that only become apparent over time. This over-time monitoring capability is critical, as many emerging risks do not materialise in a single interaction but instead develop across multiple exchanges.
A well-designed governance layer creates a feedback loop, channeling forensic learnings back into security guardrails so that defences evolve alongside the threats they are designed to counter.
In practical terms, AI interaction governance encompasses several interconnected capabilities. Unified data collection must span the full spectrum of interaction types — human-to-AI conversations, agent-to-agent workflows, and complex multi-agent pipelines. Data can be ingested through direct AI infrastructure integrations, Retrieval-Augmented Generation (RAG) and gateway connections, or via custom API ingestion.
Once collected, fragmented data must be normalised into a standardised, navigable timeline that allows investigators to replay conversations in their entirety. Retention policies, meanwhile, should be dynamically configurable to satisfy legal hold requirements and manage data liability effectively.
The forensic dimension of aiComms governance represents a meaningful departure from legacy approaches. Traditional flat log files are insufficient for the richness and complexity of modern AI interactions. Purpose-built forensic views enable compliance and security teams to identify policy violations that may have bypassed initial guardrails, profile high-risk channels and user behaviour patterns, and push critical alerts directly to SIEM, Security Operations Centre (SOC), and Security Orchestration, Automation and Response (SOAR) tools for efficient investigation.
This level of interoperability ensures that aiComms governance does not operate in isolation but integrates seamlessly into the broader enterprise security ecosystem.
Detection capabilities must also keep pace with increasingly sophisticated misuse patterns. Governance solutions are now being designed to identify unethical summary steering — attempts to compel an AI to omit or distort sensitive topics — as well as jailbreaking techniques intended to circumvent intended AI restrictions.
Compliance automation is another emerging priority, enabling the identification of missing disclosures or improperly shared attachments within AI prompts. Perhaps less discussed but equally important is the detection of AI notetakers operating as hidden participants in meetings, where appropriate policies must be applied even when their presence is not immediately apparent.
The broader ambition of aiComms governance is not to stifle innovation but to ensure it can proceed safely and responsibly. Organisations that invest in monitoring production AI interactions today are building the predictive risk detection infrastructure they will need tomorrow.
By integrating governance frameworks with SIEM platforms and refining guardrails continuously, enterprises can strike the balance between harnessing the efficiency gains of AI and maintaining the rigorous security posture that regulators and stakeholders increasingly demand. In a landscape where AI is no longer merely a tool but a participant, governance must evolve accordingly.
99% of organizations are expanding their use of AI this year. Yet, 88% cite challenges with governance and security. Join speakers and industry luminaries from SIFMA, RingCentral, Zoom, Webex by Cisco, Metrigy Analyst Group, and Theta Lake as they discuss the impacts on risk of AI in regulated organizations and the need to reimagine security and compliance in an AI-powered workplace. Walk away with insights on how to deploy AI securely, simplify governance, and unlock innovation while navigating the shifting compliance Regulatory Landscape.
The series kicks off June 16, 2026. More sessions featuring thought-leaders and experts are being added to the program.
“AI technology usage in the regulated workspace is increasing exponentially and creating myriad new governance scenarios,” said Melissa MacGregor, Deputy General Counsel and Corporate Secretary at SIFMA. “Firms need more than to just increase their technology and feature adoption, they need practical perspectives on potential risks and guidance on areas of AI governance to prioritize. I look forward to diving into that topic and those perspectives during my session at the Theta Lake AI Governance Series.”
To register for the Series, click here.
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