AI communications governance refers to the integrated set of policies, controls, retention practices, supervision workflows, and evidence management processes that oversee business communications created, changed, or assisted by artificial intelligence. For regulated organizations, this framework ensures that AI-assisted emails, chats, collaboration messages, mobile communications, and customer-facing content are consistently captured, reviewed, stored, investigated, and produced as required. By establishing clear governance, organizations position themselves as trusted authorities in managing AI-driven communications risk
With generative AI now embedded in daily workflows, communication risk extends beyond employee-authored content to include the ways employees leverage AI to draft, summarize, translate, or generate business communications. This includes interactions with large language models and the creation of customer-facing materials, all of which require oversight within regulated environments.
For compliance, legal, risk, and IT teams, the central challenge is not simply employee use of AI, but the organization's ability to demonstrate a defensible record of activity. This includes evidencing what content was created, which AI tools were used, who reviewed or approved communications, where messages were sent, how long records were retained, and whether the organization can reliably produce this information during audits, investigations, or regulatory reviews.
Regulators are already applying existing obligations to AI-enabled workflows and modern communication channels. FINRA Regulatory Notice 24-09 reminds member firms that the use of generative AI and large language models may implicate existing regulatory obligations. Separately, the SEC’s off-channel communications enforcement actions reinforce the requirement that firms maintain and preserve required electronic communications so that records remain available for investigations and regulatory review.
Arctera research highlights a persistent policy-to-proof gap: while 80% of organizations report having a formal AI policy, only 55% log AI prompts and outputs, and just 29% automatically retain or archive AI-generated content. This operational disconnect underscores the need for AI communications governance to prioritize evidentiary controls over policy statements alone.
For regulated organizations, the priority is to operationalize AI communications policy by integrating it with systems and workflows that preserve evidence, enable supervision, and ensure communications are searchable, reviewable, and producible on demand.
Key takeaways
- AI communications governance applies AI governance principles to regulated business communications.
- It covers AI-assisted communications, AI-generated communications, retention, supervision, surveillance, investigation readiness, and regulatory evidence.
- The principal compliance risk is not employee use of AI itself, but the organization's potential inability to demonstrate what was created, approved, retained, reviewed, or escalated within its communications environment.
- Regulated organizations need policies, approved tools, defensible archives, audit trails, monitoring controls, and evidence workflows.
- AI communications governance must be embedded within existing regulated communications compliance programs, rather than treated as a standalone or conceptual AI policy.
AI communications governance is not an isolated policy exercise. It must connect the systems responsible for capturing, retaining, supervising, investigating, and producing communications, enabling teams to reconstruct events when AI is involved in the workflow. The practical standard is the organization's ability to reconstruct the communication record, not merely reference a policy.
AI communications governance definition
AI communications governance is a structured framework for managing business communications that are created, modified, summarized, translated, reviewed, or otherwise assisted by AI. It enables organizations to control AI use in communications, supervise those communications, and maintain records that meet compliance, legal, and investigative requirements.
A practical AI communications governance program typically includes:
- Policies for acceptable AI use in business communications
- Controls for approved and unapproved AI tools
- Review and approval workflows for AI-assisted content
- Capture and retention rules for AI-generated or AI-assisted communications
- Supervision and surveillance processes for compliance risk
- Audit trails showing who created, reviewed, modified, or approved content
- Evidence workflows for investigations, audits, litigation, and regulatory requests
For a broader view of how governance applies across enterprise data, see Arctera’s guide to information governance.
How it differs from general AI governance
General AI governance focuses on the responsible use of AI systems across the organization. It may cover model risk, data privacy, fairness, explainability, procurement, vendor oversight, security, and ethical use.
Broader AI governance frameworks provide useful context. The NIST AI Risk Management Framework is a voluntary, non-sector-specific, use-case agnostic framework designed to help organizations manage AI risks and promote trustworthy and responsible AI. AI communications governance applies that risk discipline to regulated messages, approvals, retention, supervision, and evidence workflows.
AI communications governance applies a focused lens to the use of AI within the communication process. It addresses AI-assisted emails, chat messages, collaboration posts, voice transcripts, customer replies, advisor communications, marketing content, support interactions, and employee messages, ensuring each is governed according to regulatory expectations.
This distinction matters because regulated communications are already subject to strict supervision, retention, monitoring, and evidentiary requirements. AI introduces additional risk by altering how communications are generated and how accountability is established.
In practice, AI communications governance asks questions such as:
- Was AI used to create, edit, summarize, or translate this communication?
- Was the AI tool approved for business use?
- Did a human review or approve the content before it was sent?
- Was the final communication captured and retained?
- Can the organization reconstruct the full communication context?
- Can compliance teams detect risky, misleading, or non-compliant content?
- Can legal or investigation teams produce defensible records?
Why communications governance matters in regulated industries
In regulated industries, communications are not just business records. They are evidence of conduct, advice, approvals, disclosures, decisions, and customer interactions.
That makes communications governance especially important for sectors such as financial services, healthcare, insurance, life sciences, public sector, energy, and other industries where employees communicate under strict legal, regulatory, and policy obligations.
AI-assisted communications elevate compliance risk when organizations lack visibility into how content is created, reviewed, retained, and supervised. For instance, a financial advisor might use AI to draft a client message containing unsupported performance language; a customer support agent could summarize a complaint using AI but omit relevant context; a healthcare or benefits team may draft responses with AI that introduce inaccuracies; or a marketing team might generate customer-facing claims before legal or compliance review. In the absence of robust governance, organizations may be unable to demonstrate that such communications were accurate, approved, retained, and accessible for compliance or investigation.
Effective AI communications governance helps organizations:
- Protect sensitive and regulated information.
- Maintain consistent communications policies.
- Capture communications across approved channels.
- Reduce the risk of off-channel and unsanctioned use of AI tools.
- Preserve records with context and metadata.
- Support supervision, surveillance, and escalation
- Improve audit, investigation, and discovery readiness.
Why AI-Assisted Communications Create New Compliance Risks
AI-assisted communications introduce new compliance risks by altering both message content and the underlying creation process. Traditional compliance programs were designed for human-authored messages, approved channels, established surveillance policies, and defined retention schedules. The integration of AI increases complexity and requires updated controls.
Messages may now include AI-generated language, AI-assisted edits, automated summaries, translations, or suggested replies. While the final communication may appear routine, the underlying process can involve tools, prompts, drafts, or data sources that are not visible to compliance teams.
This is where the policy-to-proof gap becomes operational. If prompts, outputs, AI-assisted drafts, and final communications are not logged, retained, or integrated into review workflows, compliance teams may have formal rules for AI use but lack the evidentiary record required to review, escalate, investigate, or defend communications when needed.
AI-generated communications can introduce inaccurate or misleading content
AI-generated content can appear polished and credible even when it contains errors, unsupported claims, or misleading language. In regulated communications, that creates a serious risk.
Potential examples include:
- An AI-drafted client message that includes unsupported or exaggerated performance language
- A customer response that includes inaccurate account, policy, coverage, or eligibility information
- A healthcare or benefits communication that includes inaccurate clinical, coverage, or plan details
- A marketing or sales claim generated before legal or compliance review
- A summary of a complaint, conversation, or meeting that omits context needed for review
Organizations cannot assume AI-assisted content is compliant based solely on its appearance. Governance controls must specify when human review is required, which communications need approval, and how potentially risky content is escalated for further assessment.
AI-assisted communications can blur authorship and accountability
AI can obscure authorship and accountability for communications. An employee may use an AI tool, incorporate its suggestions, edit the output, and send the final message through either approved or unapproved channels, complicating responsibility tracking.
That raises several compliance questions:
- Who authored the communication?
- Was AI used in the drafting or review process?
- Was the output reviewed by a qualified employee?
- Were any claims, recommendations, or disclosures changed?
- Is there an audit trail showing what happened?
For regulated organizations, accountability remains essential even when AI is involved. AI communications governance must clearly define the roles of employees, supervisors, compliance reviewers, and approved systems at each stage of the communication process.
Customer-facing AI communications increase regulatory and reputational risk
Customer-facing communications carry greater risk because they can influence decisions, expectations, complaints, disclosures, and trust. When AI is used to generate or assist customer-facing messages, organizations need controls that reflect the potential impact of those communications.
Examples include:
- AI-assisted responses to customer complaints
- AI-drafted financial, insurance, or healthcare communications
- Chatbot or agent-assist content used in customer service
- AI-generated marketing claims
- Personalized customer messages based on account or profile data
The risk extends beyond the possibility of AI generating incorrect content. Organizations may also be unable to demonstrate how messages were created, reviewed, approved, retained, and supervised, which is critical for compliance.
Unapproved AI tools can create off-channel communications risk
Use of unapproved AI tools can create significant gaps in communication oversight. Employees may transfer business content into consumer AI tools, use AI to summarize sensitive messages, or generate drafts outside approved systems, increasing exposure and reducing control.
That can create several governance problems:
- Business communications may not be captured.
- Sensitive information may be exposed.
- AI-generated drafts may not be retained.
- Compliance teams may lack visibility into prompts or outputs.
- Investigators may be unable to reconstruct the full record.
- Policies may exist but lack technical enforcement.
AI communications governance must address both approved channels and unapproved workflows. Organizations need visibility into where AI is used, which tools are authorized, and how AI-assisted communications are captured and integrated into compliance processes.
For more on capturing communications at the source, see Arctera Capture and Arctera’s capture integrations.
How AI Communications Governance Fits into Regulated Communications Compliance
AI communications governance should not be managed as a separate initiative from the broader compliance program. It must extend existing compliance controls to encompass AI-assisted content, emerging communication channels, and evolving evidentiary requirements.
In financial services, this matters because AI adoption is being evaluated through existing regulatory expectations. The FCA has described its approach to AI as evidence-based, with a focus on balancing the benefits and risks of AI in financial services. That supports treating AI-assisted communications as part of the operating compliance program rather than as a separate policy exercise.
Many organizations have established policies and systems for communications retention, surveillance, supervision, legal hold, eDiscovery, and audit response. AI communications governance updates these controls to address environments where both employees and systems may use AI at multiple points in the communication lifecycle.
For related information on compliance programs, see Arctera’s overview of compliance management solutions.
Where AI communications compliance fits into existing compliance programs
AI communications compliance should connect to the same governance areas that already support regulated communications:
- Communications policies
- Acceptable use policies
- Records retention schedules
- Supervision and surveillance programs
- Data loss prevention and privacy controls
- Investigation and discovery workflows
- Legal hold and audit response processes
- Employee training and attestations
This integrated approach reduces the risk that AI policies remain unimplemented within the systems responsible for capturing, retaining, supervising, and producing business communications.
How AI governance connects to communications policies and supervision
AI governance should define what employees are allowed to do with AI. Communications governance should define how those AI-assisted outputs are managed once they become business communications.
That means communications policies should clarify:
- Which AI tools are approved for business use
- Which communications may or may not be AI-assisted
- Which content types require human review
- Which customer-facing messages require approval
- Which channels must be captured and supervised
- Which prompts, drafts, outputs, or final messages must be retained?
- How policy violations are escalated
Surveillance teams should assess whether current keyword lists, policies, and review processes are sufficient for AI-assisted language. AI can generate content that avoids obvious keywords yet still introduces risks such as misleading claims, omissions, or substandard recommendations.
For a deeper look at supervision workflows, see the Arctera Supervise product and the Arctera Surveillance solution page.
Why regulated communications compliance needs to account for AI-assisted content
Regulated communications compliance relies on managing what employees and systems communicate, the channels used, and the preservation of records. AI-assisted content impacts each of these areas and requires corresponding controls.
Organizations may need to account for:
- AI-generated drafts that become final business communications
- AI summaries of regulated conversations
- AI-assisted edits to customer-facing messages
- Prompts that include sensitive or regulated information
- Final messages sent through email, chat, collaboration, mobile, or social channels
- Review and approval records for AI-assisted content
The objective is to determine which AI-assisted interactions qualify as business records, require supervision, and must be retained as evidence, rather than indiscriminately preserving all experimental prompts.
How employee AI policies support defensible communications governance
Employee AI policies are important, but they are just one part of governance. A policy is defensible when it is backed by training, approved tools, technical controls, monitoring, retention, and audit trails. Your AI communications policy should explain:
- Approved and prohibited AI use cases
- Rules for customer-facing communications
- Restrictions on sensitive, confidential, or regulated data
- Review requirements for AI-assisted content
- Responsibilities for authorship and approval
- Consequences for unapproved tool or channel use
- How employees should document AI-assisted work when required
Policies must be reviewed and updated regularly to align with evolving AI tools, communication channels, and regulatory requirements.
How AI Communications Governance Relates to Communications Retention
Keeping communications is a key part of AI communications governance. If AI-assisted business messages are not captured and kept, they may not be available for supervision, investigations, audits, legal discovery, or regulatory needs.
AI does not diminish the requirement to retain records. In many cases, it increases the need for clear retention rules, as communications may now include drafts, summaries, prompts, outputs, approvals, and final messages distributed across multiple systems.
Arctera supports policy-driven communications retention through Arctera Archive and broader Records and Retention Optimization workflows.
Why AI-assisted communications must be captured and retained
AI-assisted communications should be captured and retained when they constitute business records, regulated communications, customer interactions, approvals, advice, or other content subject to legal or compliance obligations.
Retention supports:
- Audit readiness
- Regulatory production
- Internal investigations
- Litigation response
- Supervision and escalation
- Evidence of policy compliance
- Reconstruction of the communication context
If communications are not captured and retained, organizations may be unable to demonstrate what was communicated, who participated, whether messages were approved, or if policies were followed.
How retention policies apply to AI-generated business communications
Retention policies should address AI-generated and AI-assisted communications based on content, context, channel, and regulatory obligation.
Organizations should consider:
- Whether the AI-assisted output became a business communication
- Whether the communication was sent internally or externally
- Whether it included regulated, confidential, or customer-specific information
- Whether it involved advice, approvals, claims, complaints, or disclosures
- Whether the communication was reviewed or escalated
- Which retention schedule applies to the final record
Retention policies must be both practical and defensible. They should specify which records are to be retained, the applicable retention periods, when legal holds are triggered, and which systems are accountable for preservation.
The role of a compliance communications archive
A compliance communications archive is a managed repository for business communications that supports retention, supervision, audit, investigation, and discovery workflows. For AI communications governance, the archive helps ensure AI-assisted business messages are preserved with the context needed to understand and produce them later.
A defensible archive should help organizations:
- Preserve communications with metadata and context
- Apply retention schedules consistently
- Support search, review, and export
- Maintain audit trails
- Reduce reliance on manual collection
- Support supervision, investigations, and eDiscovery
The archive is particularly critical when AI-assisted communications are distributed across email, messaging, collaboration platforms, mobile, voice, file sharing, and AI tools.
Retention risks across email, chat, collaboration, and mobile channels
AI communications governance must account for the channels employees actually use. AI-assisted communications may appear in email, chat, collaboration platforms, SMS, voice transcripts, customer service systems, social media, and AI tools.
Common retention risks include:
- AI-assisted drafts created outside approved systems
- Business messages sent through unsupervised channels
- Missing metadata or incomplete conversation history
- Summaries retained without the underlying communication context
- Inconsistent retention across email, chat, and mobile channels
- Difficulty connecting related messages across systems
A unified approach to capture, retention, supervision, and discovery helps close operational gaps and supports compliance across all communication channels.
How Governance Supports Investigation Readiness
AI communications governance directly impacts investigation readiness. When communications are captured, retained, and contextualized, investigation teams can reconstruct events with greater speed and confidence.
When governance is insufficient, investigators may face missing records, fragmented systems, ambiguous authorship, incomplete data, or uncertainty regarding AI involvement in communications.
Arctera supports legal, compliance, and investigation workflows through Arctera Discover.
How governed communications improve search and discovery
Good governance of communications makes search and discovery easier because records are captured regularly and kept with the context needed to understand them. Investigation teams may need to search by:
- Sender, recipient, participant, or reviewer
- Channel or communication source
- Date, time, or conversation sequence
- Keywords, phrases, or policy indicators
- Attachments, links, or related files
- Review status or escalation history
- AI-assisted content indicators, where available
When communications are governed from the outset, investigation teams can focus on substantive issues rather than reconstructing records from incomplete or fragmented sources.
Why investigation teams need a complete communication context
A single message rarely tells the full story. Investigation teams often need the surrounding context: what came before, what changed, who approved it, which channel was used, and whether the communication was part of a broader pattern.
For AI-assisted communications, context may include:
- The final message
- Related drafts or summaries, where retained
- Approval history
- Review notes
- Metadata and timestamps
- Channel and participant information
- Related conversations across platforms
Without this context, teams risk misinterpreting events or overlooking policy violations.
AI-assisted content can affect internal investigations
AI-assisted content can affect investigations in several ways. It may obscure authorship, introduce inaccurate summaries, normalize risky language, or make it difficult to determine whether a message originated from an employee, AI, or both.
For example, an investigator reviewing a customer complaint may need to know whether a response was written by an employee, generated by AI, edited by a supervisor, or sent automatically through an approved workflow. A compliance reviewer may need to know whether an AI-assisted message contained unapproved claims or omitted required disclosures.
AI communications governance gives teams the records and audit trails needed to answer those questions.
Reducing investigation risk with defensible records
Defensible records mitigate investigation risk by enabling organizations to demonstrate that communications were captured, retained, reviewed, and produced in accordance with policy.
A defensible record may include:
- The communication content
- Relevant metadata
- Participants and channel information
- Creation and modification history
- Review and approval records
- Supervision alerts or escalation outcomes
- Retention and deletion controls
A robust governance model allows organizations to demonstrate that their evidence is complete, traceable, and reliable when required by regulators or investigators.
What Evidence Regulators Expect Organizations to Produce
Regulators, auditors, and legal teams often want more than a policy document. They may need proof that communications were captured, retained, reviewed, supervised, escalated, and produced in accordance with policy. For AI-assisted communications, that evidence requirement becomes more complex because teams may also need to understand whether AI was used, whether the tool or channel was approved, who reviewed the communication, and whether the full context can be reconstructed.
For AI-assisted communications, organizations should be prepared to demonstrate how AI use is governed across policies, processes, systems, people, and evidence.
Policies governing AI-assisted communications
Organizations must maintain policies that clearly define permissible AI use in business communications. These policies should be explicit enough to guide employee behavior and support compliance validation.
Policy evidence may include:
- Approved AI tools and use cases
- Prohibited use cases
- Rules for sensitive or regulated data
- Human review and approval requirements
- Customer-facing communication standards
- Authorship and accountability expectations
- Escalation procedures for policy violations
- Employee training and attestation records
Records of business communications and approvals
Organizations must be able to produce records of business communications, including approval workflows where applicable.
Relevant evidence may include:
- Original business communications
- Final approved messages
- Approval records
- Reviewer notes
- Communication histories
- Related attachments or files
- Metadata showing participants, timestamps, and channels
For AI-assisted content, the organization should determine whether drafts, prompts, outputs, summaries, or final communications are subject to retention requirements under applicable policies and regulations.
Audit trails showing who created, reviewed, or modified content
Audit trails establish accountability by documenting how content progressed through each stage and identifying all participants.
Audit trail evidence may include:
- Creator or sender information
- Reviewer and approver activity
- Modification timestamps
- Version history, where available
- Review comments
- Escalation history
- Administrative actions
- Policy changes affecting retention or supervision
This is especially important when AI-assisted content makes it hard to distinguish between drafting, editing, reviewing, and approving.
Evidence of supervision, monitoring, and escalation
Supervision evidence demonstrates that the organization is actively monitoring, reviewing, and escalating communications as required, moving beyond policy documentation to operational practice.
Supervision evidence may include:
- Monitoring policies
- Surveillance rules or lexicons
- Alerts and risk indicators
- Reviewer decisions
- Escalation outcomes
- Exception handling
- Quality assurance records
- Reports showing review activity
AI-assisted communications may necessitate updated surveillance methods to detect misleading claims, omissions, unapproved language, or atypical communication patterns. Retention and deletion controls ensure records are preserved for the required period and disposed of in accordance with policy.
Evidence may include:
- Retention schedules
- Archive records
- Legal hold status
- Deletion workflows
- Disposition approvals
- Retention audit logs
- System configuration records
- Exceptions or overrides
For AI-assisted communications, retention controls must specify which records are retained and how they relate to the main business communication record for compliance and evidence purposes.
How eComms Surveillance Changes with AI-Generated or AI-Assisted Content
eComms surveillance needs to change as AI becomes part of communication workflows. Traditional surveillance looks for risky language, banned phrases, or suspicious patterns. AI makes this harder because it can generate polished, varied, or context-specific language that does not always align with current keyword lists.
AI-assisted communications can still be risky even when they do not contain obvious keywords. A message may be misleading, incomplete, overly promissory, or inconsistent with approved language, yet still appear polished and compliant.
Why eComms surveillance must adapt to AI-assisted communications
AI-assisted communications change surveillance by altering how messages are created, edited, and shared. Employees might use AI to write messages faster, rewrite sensitive content, summarize complex talks, or create many responses at once.
Surveillance programs should consider:
- Whether existing policies detect AI-assisted risk effectively
- Whether reviewers can identify misleading or unapproved claims
- Whether AI-created content is captured across relevant channels
- Whether alerts include enough context for review
- Whether patterns of AI-assisted content create new conduct risks
For more on communications surveillance, see Arctera’s Supervision and Surveillance solution page.
Monitoring AI-generated communications for compliance risk
Monitoring AI-generated communications requires both content review and process visibility. Compliance teams need to understand not only what was sent, but whether the communication followed approved policies and workflows.
Monitoring practices may include:
- Reviewing AI-assisted communications for prohibited claims
- Detecting missing disclosures or required language
- Flagging unapproved tools or channels
- Monitoring customer-facing messages for accuracy
- Identifying patterns across employees, teams, or business units
- Escalating high-risk communications for review
The goal is not to stop every AI-assisted message. It is to identify where AI use creates compliance, conduct, legal, or reputational risk, especially when communications include inaccurate, incomplete, non-compliant, or unapproved claims.
AI tools can generate content that sounds confident but is inaccurate, incomplete, or inconsistent with approved messaging. This is especially risky in regulated industries where claims, recommendations, disclosures, and advice must meet strict standards.
Surveillance teams should pay attention to:
- Promissory or exaggerated claims
- Missing disclaimers
- Unapproved product language
- Misleading summaries
- Inconsistent customer guidance
- Statements that conflict with approved policies
- Communications that appear to bypass the required review
AI communications governance should link detection with escalation so that risky content is not just flagged but also reviewed and resolved.
Supervising communications across approved and unapproved channels
AI-assisted communications may occur across many channels. Some may be approved and captured. Others may be informal, mobile, personal, or unsanctioned.
Governance teams should identify:
- Which channels are approved for business communications
- Which AI tools are approved for communication-related work
- Which communication types require capture and retention
- Which channels are subject to supervision
- Where off-channel or unapproved AI use may occur
- How violations are detected and escalated
This is where capture, archiving, supervision, and discovery need to work together.
Using surveillance insights to improve governance controls
Surveillance should do more than find single risks. It should also help make the governance program better over time.
Surveillance insights can reveal:
- Policies that employees do not understand
- Business units with higher communication risk
- Channels where capture is incomplete
- Repeated use of unapproved language
- Emerging AI-assisted risk patterns
- Review workflows that need refinement
- Training gaps across teams
These insights help organizations move from just reacting to problems to always improving governance controls and compliance processes.
AI Communications Governance Checklist
Use this checklist to evaluate whether your organization is prepared to govern AI-assisted communications.
- Define acceptable AI use in business communications
- Identify approved AI tools and communication channels
- Capture and retain AI-assisted business records
- Monitor communications for policy and compliance risk
- Maintain audit trails and approval evidence
- Preserve investigation-ready records
- Review governance controls as AI tools and regulations evolve
For a deeper framework, read Arctera’s research report on AI communications governance.
Related Arctera Capabilities
AI communications governance needs more than written policies. Organizations need a connected foundation to capture communications at the source, preserve records with context, apply retention and supervision controls, and support investigation and eDiscovery workflows from the same governed record. The Arctera Unified Platform connects capture, archiving, supervision, and discovery across enterprise communications and data, enabling compliance, legal, risk, and IT teams to maintain more consistent governance workflows.
Communications capture across modern channels
Arctera Capture collects communications at the point of creation and preserves the metadata and context needed for downstream governance. This gives compliance teams a more complete record to retain, supervise, search, and produce.
Capture is a basic part of AI communications governance. Compliance teams cannot keep, supervise, or provide records that are not collected at the source.
Communications archiving and retention
Arctera Archive preserves communications in a governed archive, applies retention and disposition controls, and supports audit, compliance, and legal workflows from a defensible system of record.
This feature enables organizations to maintain AI-assisted business communications as part of a robust recordkeeping plan that meets compliance and legal requirements.
eComms surveillance and supervision
Arctera Supervise helps compliance teams identify, review, escalate, and resolve communications risk using policy-driven review workflows and contextual signals across governed communications.
As AI-assisted communications grow, supervision workflows are key for spotting risky claims, unapproved language, policy violations, and conduct risks across channels.
Investigation readiness and defensible discovery
Arctera Discover helps legal, compliance, and investigation teams search, reconstruct, review, and produce communications from governed records for litigation, regulatory matters, and internal investigations.
This capability supports this feature, which helps organizations rebuild events, understand communication context, and provide strong evidence when AI-assisted communications matter for investigations, audits, or legal cases.
Records and retention optimization
Arctera’s Records and Retention Optimization solutions help organizations manage retention obligations, reduce information risk, and support defensible disposition across enterprise communications and data. This becomes more important as AI increases both the volume and complexity of business communications that must comply with and be retained in accordance with rules.
Learn more about AI communications governance
To explore how organizations are approaching AI-assisted communications, compliance risk, retention, surveillance, and investigation readiness, read Arctera’s latest research on AI communications governance.