Enterprise AI Governance
Control, Compliance & Coaching
See how employees use AI, apply your policies and protect sensitive data on supported browser and desktop paths. Keep governance decisions with your accountable teams.
What Is an Enterprise Workforce AI Security Platform?
An enterprise Workforce AI Security platform is a purpose-built security and compliance solution that gives organizations visibility and control over how employees interact with AI tools. It addresses three interconnected problems that have emerged as AI adoption has accelerated faster than policy, procurement, and security processes can keep up: shadow AI usage (employees using AI tools that were never approved or reviewed), data leakage (sensitive information being shared with AI models without oversight), and compliance exposure (the inability to demonstrate to auditors that AI usage is governed and documented).
Aona combines discovery, configured policies, supported file controls and employee coaching through an installed browser plugin or native app. Coverage depends on the managed device, AI service and input path. Catalogue recognition is not observed usage or proof that every action is controlled.
Salesforce's November 2023 study reported that 55% of surveyed workers using generative AI at work had used unapproved tools. Cisco's 2024 study of privacy and security professionals reported 48% entering non-public company information into GenAI. These distinct survey populations are context, not measurements of your workforce or Aona customers.
A workforce AI security programme combines approved-use rules, supported technical controls and employee guidance. Security, privacy and business owners still decide acceptable use, review evidence and meet their legal obligations.
of surveyed workplace GenAI users used unapproved tools (Salesforce, 2023)
Source: Salesforce, November 2023of Cisco survey respondents entered non-public company data into GenAI (2024)
Source: Cisco Privacy Benchmark Study, 2024See AI use on your managed devices
Employees can adopt AI tools before formal review catches up. The Salesforce survey illustrates why an approved-tool list alone cannot establish actual employee use.
Aona records activity through its installed browser plugin or native endpoint app on supported paths. Review tool, user, data context and policy outcomes within the configured collection and privacy scope.
IT can distribute the browser plugin and Windows/macOS app with existing software deployment tools. Start with a defined cohort and verify its installation, activity and policy response before expanding. Network-based products can also inspect traffic routed through their supported paths.
- Inventory of observed AI use on deployed, supported paths
- Employee-level usage logs with data classification context
- Review newly observed tools against your approved-use policy
- Policy gap analysis: where is usage outpacing governance?
- Installed-client coverage; not agentless discovery
Set Guardrails That Actually Work, At the Browser Layer
An AI acceptable use policy is only as good as your ability to enforce it. Most organizations publish a policy document, send an all-hands email, and hope for the best. Aona makes policy enforcement automatic, real-time, and auditable, without relying on employees to remember what they read in a training module six months ago.
Set rules for approved tools and sensitive data, then validate the response on the intended client and input path. Controls require the configured browser plugin or native app; an unmanaged device without that client is outside the deployment.
Supported policies can warn, coach, redact or block. Select the response for the data and action in scope, and test the employee experience. A hard block does not give the employee a continue option.
- Allow/block/warn policies per AI tool, per team, per data classification
- Prompt-level filtering: intercept high-risk queries before submission
- Graduated enforcement: warn, require acknowledgement, or hard-block
- Policy version control with audit trail for compliance evidence
- Role-based policy exceptions for approved power users and research teams
Stop Sensitive Files From Leaving Your Organization via AI Tools
File upload is the highest-risk AI interaction pattern in the enterprise. When an employee uploads a contract, a spreadsheet, a presentation, or a source code file to an AI tool, they may be inadvertently sharing customer PII, proprietary intellectual property, financial data, or regulated health information with a third-party model provider whose data handling practices they have not reviewed.
Aona's File Scanner intercepts file uploads to AI tools and classifies the content in real time before the upload completes. Using a combination of pattern matching and semantic classification, the scanner identifies PII (names, emails, phone numbers, national IDs), financial data (account numbers, trading data, revenue figures), intellectual property (source code, product roadmaps, M&A documents), and regulated data categories including HIPAA, PCI-DSS, and GDPR-relevant content.
On supported upload paths, a configured policy can warn, redact or block. Review the recorded outcome and returned file where available. Aona does not provide manager-approval routing; escalation and approval remain part of your organisation's process.
- Real-time classification of uploaded files before submission to AI
- Detection of PII, IP, financial data, and regulated content categories
- Validate each AI tool, client and file-upload route
- Review available policy events within your collection scope
- Configure supported warnings, blocking and redaction
Educate Employees In the Moment, Not After the Incident
Security awareness training has a well-documented retention problem. Employees complete annual training, pass the quiz, and then make the exact same mistakes in the real world because generic training doesn't translate to specific situations. The most effective moment to teach someone about AI risk is the moment they are about to make a risky AI decision, not six months later in a classroom.
Aona's real-time coaching system intercepts risky AI interactions and delivers contextual, specific education at the point of action. When an employee is about to upload a file containing customer PII to an unapproved AI tool, Aona doesn't just block the action, it explains what PII was detected, why uploading it to this specific tool is a compliance risk, what the approved alternative is, and what the policy says about this scenario. The employee learns something true and actionable, right now, when it matters.
Coaching messages are designed to reduce policy violations over time, not just prevent individual incidents. Aona tracks which employees trigger repeated coaching events, enabling security teams to identify individuals who need additional support and demonstrating to compliance auditors that your organization has a proactive, not just reactive, AI risk management program.
- Contextual micro-interventions at the exact moment of risky behavior
- Explanations reference specific data detected, not generic warnings
- Links to approved alternatives and internal AI policy documentation
- Repeat-violation tracking for targeted follow-up training
- Coaching event logs for compliance audit evidence
The Business Case for AI Governance
Evaluate the controls, operational effort and evidence your organisation needs before expanding workforce AI use.
Reduce AI-Related Data Breach Risk
Sensitive prompts and files can expose customer, employee and business information. Apply supported controls before submission, then test the expected outcome. This reduces specific exposure paths; it is not a guarantee against breaches or a measured financial saving.
Cut Compliance Audit Time
Recorded AI activity and policy outcomes can support evidence collection. Agree the fields, time period and review process with your audit owner. A report supports that process; it does not establish compliance or a guaranteed reduction in audit time.
Enable Safe AI Adoption at Scale
The real cost of poor AI governance is not just breach risk, it is the productivity value lost when organizations respond to AI risk by restricting access rather than governing it. Aona enables organizations to confidently expand approved AI tool access, knowing that guardrails are in place. Employees get more access to the AI tools that make them productive; the organization gets the oversight it needs to do so safely.
FAQ
Frequently Asked Questions
What is enterprise AI governance?
How does Aona detect shadow AI?
Is Aona suitable for regulated industries?
How long does Aona take to deploy?
How does Aona compare to traditional DLP?
Bring your employee AI controls into focus
Choose a managed cohort, an AI tool and a sensitive-data rule. See the supported employee response and plan the rollout with your IT team.