Security & Compliance · AI Security · Shadow AI · Data Governance

Your Employees Are
Already Using AI.
Is Your Data Going With It?

AI summarization tools, writing assistants, and research platforms. Employees are pasting company data, client information, and proprietary documents into these tools every day, without policies, without governance, and without anyone knowing. TechWise finds out what’s happening, classifies what can and can’t be shared, and puts controls in place before a data handling habit becomes a breach.

Talk About AI Security

Project phase 2–6 weeks · Ongoing monitoring available

● Shadow AI assessment, find what’s already in use

● Data classification before any AI deployment

● Continuous monitoring after go-live

● Chicago · Philadelphia · Los Angeles

Why This Can’t Wait

The AI Risk Isn’t Coming.
It’s Already Here.

Most companies are focused on whether to adopt AI. The more urgent question is what’s already happening without a policy. Shadow AI: employees using unapproved AI tools with company data, is the fastest-growing data risk in growing organizations, and most leadership teams have no visibility into it.

The Shadow AI Problem

Every time an employee shares company data with an AI tool, that data may leave your control.

When an employee pastes a client contract into an AI summarization tool to summarize it, that data enters a third-party system outside the company’s control. When a salesperson uses an AI tool to draft a proposal using proprietary pricing, that information may be used to train a public model. Most organizations have no visibility into how many of these events happen daily, or what data is leaving.

The Copilot Problem

Copilot sees everything the user can see. Wrong permissions means wrong exposure.

Microsoft Copilot is trained on everything in your Microsoft 365 environment, emails, files, Teams conversations, SharePoint documents, filtered only by what the user has permission to access. If permissions are misconfigured before deployment, Copilot will surface sensitive data to people who shouldn’t see it. Most organizations deploying Copilot haven’t cleaned up their permissions first.

The Policy Gap

Employees want to use AI. Nobody has told them what they can share.

Most organizations don’t have an AI usage policy. Employees are making individual decisions about what’s safe to share, decisions that vary by person, by team, and by day. Without a clear policy on approved tools, acceptable use, and data handling, the risk is entirely dependent on individual judgment. TechWise builds the policy against the actual AI tools employees are using, not a generic template.

The Compliance Problem

Regulators and insurers are starting to ask about AI governance.

HIPAA covered entities using AI tools to process patient data, defense contractors feeding proprietary information into AI models, and companies subject to data protection regulations, all face compliance exposure from ungoverned AI usage. Cyber insurance underwriters are beginning to add AI governance questions to renewal questionnaires. Getting ahead of this is significantly easier than responding to it after a finding.

Two Phases

Two Phases: Find What’s Happening.
Then Govern What Happens Next.

AI security is a project and an ongoing service. The project phase finds what’s happening and puts governance in place. The ongoing phase monitors what happens after, because the AI landscape changes faster than any one-time assessment can keep up with.

01 Project Phase · 2–6 Weeks

AI Security Foundation

TechWise assesses the current state of AI usage across the organization, identifies what data is at risk, cleans up the permissions foundation, and puts governance in place before any further AI deployment. Delivered as a written set of findings, policies, and configurations, not just recommendations.

→ Shadow AI assessment: which tools employees are using and what data is being shared

→ Permissions audit and cleanup: who has access to what, and whether AI should see it

→ Data classification: what can be shared with AI tools, what can’t

→ Data loss prevention policies, controls on what data can be shared with AI tools

→ AI usage policy: approved tools, acceptable use, data handling rules

→ Guest account remediation: external accounts that shouldn’t have AI access

→ Identity governance: who has access and whether AI exposure is appropriate

→ AI readiness certification: documentation of what was assessed and configured

02 Ongoing Phase

AI Security Monitoring

After the foundation is in place, TechWise monitors AI tool usage continuously, enforcing policies, flagging violations, and updating governance as new tools emerge and the regulatory landscape evolves. The AI environment a company has today is not the one it will have in six months.

→ Continuous monitoring of AI tool usage across the organization

→ Policy enforcement: approved versus unapproved tools flagged in real time

→ Data flow monitoring: what information is going into which AI models

→ Quarterly AI security posture reviews

→ Policy updates as AI tools and regulations evolve

→ Ongoing user training, not a one-time session

→ Integration with security monitoring for AI-related events

Before You Deploy Copilot

Copilot Doesn’t Create
Permission Problems. It Reveals Them.

Microsoft Copilot is one of the most powerful productivity tools available to growing companies, and one of the most dangerous to deploy without preparation. It surfaces everything the user can access. If that includes sensitive data they shouldn’t have access to, Copilot makes that immediately visible.

What TechWise Does Before Deployment

Clean the permissions foundation before Copilot can see it.

→ Permissions audit, who has access to what across SharePoint, Teams, and OneDrive

→ Oversharing identified and remediated, documents, folders, and sites with excessive access

→ Sensitivity labels applied, so Copilot knows what’s confidential and what isn’t

→ Guest account review, external users who shouldn’t influence Copilot outputs

→ AI readiness certification delivered before deployment begins

What Happens Without Preparation

Copilot surfaces what’s already accessible, including what shouldn’t be.

→ Employees discover salary documents they had SharePoint access to but never knew existed

→ Confidential client files surface in Copilot responses to users who work in adjacent departments

→ Executive communications appear in Copilot summaries for people without appropriate clearance

→ Copilot adoption stalls because trust in the tool collapses after the first exposure incident

Key Concepts

Shadow AI, Data Governance, and AI Policy.
What Each One Means.

These terms appear in board presentations, compliance frameworks, and cyber insurance questionnaires. Here is what each one means in practical terms for a company evaluating its AI risk exposure.

Shadow AI

Unapproved AI Tools Used With Company Data.

Shadow AI refers to AI tools that employees use without organizational approval or governance, AI writing assistants, summarization tools, research platforms, and hundreds of specialized AI tools. The risk is not the tools themselves. The risk is that employees are pasting company data, client information, and proprietary documents into these systems without policies governing what can be shared, with whom, or under what terms. Most organizations have no visibility into how frequently this happens or what data has left their control.

AI Data Governance

Controls on What Data AI Can Access and Share.

AI data governance is the set of policies, technical controls, and monitoring processes that determine what data AI tools can access, what employees are permitted to share with AI systems, and how AI-generated outputs are controlled. For organizations with regulated data, protected health information, CUI, financial records, AI governance is a compliance requirement, not just a best practice. Data classification, DLP policies, and usage monitoring are the technical implementation layer.

AI Usage Policy

Approved Tools, Acceptable Use, Data Handling Rules.

An AI usage policy defines which AI tools are approved for use, what categories of data can be shared with AI systems, what employee responsibilities are when using AI tools, and what the consequences of policy violations are. Without a written policy, employees make individual risk decisions that vary by person and by day. TechWise builds the policy against the actual tools employees are already using, not a generic template that doesn’t match the environment.

Copilot Readiness

Permissions Cleanup Before AI Deployment.

Microsoft Copilot readiness is the process of preparing the Microsoft 365 environment before Copilot is activated. It includes a permissions audit to identify oversharing, sensitivity labeling to classify confidential content, guest account remediation, and DLP policy configuration. Copilot does not create permission problems, it reveals the ones that already exist. Deploying Copilot into an environment with misconfigured permissions surfaces sensitive data to people who shouldn’t see it.

Common Questions

Questions About AI Security
and Data Governance.

Shadow AI refers to AI tools employees use without organizational approval: AI writing assistants, summarization tools, research platforms, and hundreds of specialized AI applications. The risk is that employees paste company data, client information, and proprietary documents into these systems without policies governing what can be shared. Most organizations have no visibility into how frequently this happens or what data has left their control. A shadow AI assessment finds what is already in use before governance is put in place.

Microsoft Copilot is safe to deploy into a properly prepared environment. The risk comes from deploying it before permissions are cleaned up. Copilot surfaces everything the user can access, if permissions are misconfigured, it surfaces sensitive data to people who shouldn’t see it. TechWise conducts a Copilot readiness assessment and permissions cleanup before deployment to ensure the environment is governed correctly before the tool is activated.

Yes. HIPAA applies to any system that processes protected health information, including AI tools. Healthcare organizations that allow employees to input patient data into AI tools without a business associate agreement and appropriate data handling controls face HIPAA exposure. AI governance for HIPAA-covered entities includes data classification to identify PHI, DLP policies to prevent PHI from entering unapproved AI systems, and audit trails to document what was shared and with whom.

Data classification is the process of labeling data by sensitivity level, public, internal, confidential, highly confidential, so that security controls can be applied based on what the data is. For AI governance, classification tells Microsoft Copilot and DLP policies what can and cannot be shared with AI systems. Without classification, there is no technical basis for controlling what AI tools can access. TechWise implements sensitivity labeling through Microsoft Purview as part of the AI security foundation engagement.

Coverage for AI-related incidents varies by policy and is an evolving area of cyber insurance. Some underwriters are beginning to add AI governance questions to renewal questionnaires. Organizations with documented AI usage policies, data classification, and DLP controls are better positioned for coverage eligibility and claim validation than those with no governance in place. TechWise recommends treating AI governance as a cyber insurance readiness requirement and not waiting for underwriters to require it explicitly.

The project phase, shadow AI assessment, permissions audit and cleanup, data classification, DLP policy configuration, and AI usage policy, generally takes two to six weeks depending on environment size and the current state of permissions and data governance. TechWise scopes the engagement based on the organization’s specific situation before work begins. Ongoing monitoring follows the project phase and continues month-to-month.

Controlled Unclassified Information is information the US government creates or possesses that requires safeguarding under law, regulation, or policy. DoD contractors handling CUI face CMMC requirements that restrict how CUI can be stored, processed, and shared. Feeding CUI into commercial AI tools, AI writing and summarization tools, Copilot without proper configuration, or other AI systems not authorized under the contractor’s CMMC environment, is a potential CMMC violation. TechWise addresses CUI handling as part of CMMC and AI security engagements for defense contractors.

Ongoing AI security monitoring includes continuous tracking of AI tool usage across the organization, real-time policy enforcement flagging approved versus unapproved tools, data flow monitoring to identify what information is entering which AI models, quarterly AI security posture reviews, policy updates as new AI tools emerge and regulations evolve, and ongoing user training. The AI landscape changes faster than any one-time assessment can keep up with, ongoing monitoring is how the governance stays current.

Your Team Is Already Using AI.
Make Sure It’s Not Using Your Data Against You.

The conversation starts with a phone system assessment, inventorying what you have before recommending how to replace it. TechWise scopes the migration before any work begins.

Tell Us What’s Broken.
We’ll Tell You How to Fix It.

Every managed engagement starts with a free assessment of your environment: no scope surprises. Tell us what’s broken, what’s keeping you up at night, or what you’re trying to build. We’ll tell you exactly what it takes and which model fits.

  • Free environment assessment, before any scope is finalized

  • 30-minute call with a senior engineer, not a sales rep

  • Six engagement models, from project to enterprise SOC

  • Chicago · Philadelphia · Los Angeles

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