AI Security & Governance
AI Security & Governance for Small and Growing Businesses
Give employees a safer way to use AI. We help businesses discover unmanaged use, protect sensitive information, establish clear rules, and apply practical controls without blocking useful work.
THE GOAL IS NOT “NO AI.”
The goal is approved AI your business can see, secure, and manage.
Why governance matters now
AI adoption is already happening—whether the policy exists or not.
Most unapproved AI use begins with good intent: an employee wants to work faster, prepare a better response, or make sense of a document. The risk appears when convenience moves faster than visibility, access controls, data rules, and review.
VISIBILITY
You cannot protect AI use you cannot see.
Browser-based tools, embedded assistants, plug-ins, and free accounts can enter daily work without a normal software review. Discovery gives leadership a real starting point.
GUIDANCE
A ban is not the same as a usable policy.
Employees need plain-language examples of approved tools, prohibited information, required review, and how to request a new use case.
CONTROL
A business license does not configure itself.
Identity, permissions, sharing, retention, security settings, and data protection still need to match the organization and the information AI can reach.
A manageable operating model
Five layers turn AI guidance into daily practice.
Governance works when policy, technology, and people reinforce one another. Each layer answers a different question the business needs to manage.
Policy & acceptable use
Define which tools and use cases are approved, what information is restricted, and where human review is required.
Identity & permissions
Connect AI access to managed identities, appropriate roles, least privilege, and reliable account lifecycle practices.
Data protection
Understand sensitive information, oversharing, retention, and the controls available to protect prompts, files, and outputs.
Approved tools & vendors
Evaluate business AI platforms, contracts, administrative controls, integrations, data handling, and organizational fit.
Oversight & response
Assign owners, document exceptions, review usage, measure outcomes, and create a path for reporting or responding to problems.
Practical AI governance deliverables
Turn AI risk decisions into policies, controls, and guidance people can actually use.
A useful governance engagement should leave the business with more than a risk report. It should define which tools and use cases are approved, how sensitive information should be handled, where human review is required, and who remains responsible as AI use changes.
AI usage & risk review
Visibility into current tools, use cases, accounts, information, and ownership.
Approved-tool framework
Clear criteria for approving, limiting, piloting, or rejecting an AI platform.
AI acceptable-use policy
Plain-language rules employees can understand and leadership can maintain.
Data & access recommendations
Prioritized actions around permissions, oversharing, sensitive data, and accounts.
Employee AI guidance
Role-relevant examples, review expectations, prohibited uses, and reporting paths.
Governance operating plan
Owners, review cadence, tool-request process, exceptions, and next-step controls.
Write rules around the moments employees actually face.
A useful AI policy is not a legal-sounding document employees forget. It gives people a safe answer to “Can I use AI for this?” and a clear path when the answer is not obvious.
Approved tools
Which platforms, accounts, features, and business use cases employees may use.
Restricted information
What client, employee, financial, health, legal, security, or proprietary information must stay out.
Human review
Which outputs must be checked before they influence customers, decisions, records, or public communication.
Ownership & disclosure
Who remains accountable for the work and when AI assistance should be documented or disclosed.
New tool requests
A simple way to request useful platforms and use cases before employees work around the policy.
Incidents & exceptions
How to report accidental data entry, unsafe output, unexpected behavior, or a needed exception.
Securing AI applications & agents
Connected AI introduces security problems a normal chatbot does not.
When AI can search company knowledge, call tools, trigger a workflow, or take action, security must account for untrusted instructions, connected data, downstream systems, and the scope of the agent's authority.
01
Prompt injection
Malicious or untrusted instructions can influence an AI system in ways the designer or user did not intend.
02
Sensitive information disclosure
Prompts, connected knowledge, or generated output can expose information to the wrong person or system.
03
Improper output handling
Applications can pass AI output into emails, websites, code, or other systems without treating it as untrusted.
04
Excessive agency
An agent can be given more access, tools, or decision-making authority than its limited task requires.
05
AI supply-chain risk
Models, data sources, plug-ins, connectors, and dependencies expand the vendors and components that require review.
Designed with current AI-specific risks in mind.
OWASP's GenAI security work highlights risks such as prompt injection, sensitive information disclosure, improper output handling, excessive agency, and supply-chain exposure. The controls still need to be tailored to the application and its real business impact.
Microsoft 365 & Copilot governance
Secure AI by strengthening the environment around it.
Microsoft 365 Copilot works within the identity, permissions, and information architecture of Microsoft 365. That makes existing access and oversharing important parts of AI readiness.
Identity & Access
Microsoft Entra / Managed Accounts / Least Privilege
Information Protection
Permissions / Sensitivity / Sharing / Retention
AI Data Security
Microsoft Purview / DLP / Supported AI Visibility
Device & App Control
Intune / Defender / Approved Access Paths
The governance process
See it. Classify it. Govern it. Reinforce it.
AI governance is not a one-time policy project. We identify how AI is being used, classify the risks, define practical rules and technical controls, and help reinforce them through employee guidance, regular review, and clear ownership.
Discover
Identify tools, accounts, use cases, connected data, and where employees already rely on AI.
Classify
Separate low-risk productivity from sensitive, regulated, customer-facing, or decision-impacting use.
Define
Create approved-tool rules, acceptable use, ownership, review requirements, and exceptions.
Control
Configure appropriate identity, access, sharing, data, device, monitoring, and platform settings.
Reinforce
Train employees, review new requests, respond to incidents, and update governance as AI use changes.
Connected AI services
Security shapes the next step—it does not replace it.
PLAN IT
AI Consulting & Strategy
Choose the right use case and define a practical adoption roadmap.
PROTECT IT
AI Security & Governance
Define approved tools, access, data safeguards, review, and accountability.
AI security FAQs
Practical answers for managing AI at work.
The safest policy is one people can understand, follow, and revisit as tools, use cases, and business risks change.