Your employees are already using artificial intelligence.
They use it to summarize documents, rewrite emails, analyze spreadsheets, generate proposals, review contracts, produce code, prepare presentations and find answers more quickly.
In many organizations, this adoption began before a formal AI strategy, an approved platform or clear internal policies were established.
The result is often called shadow AI: employees use consumer AI applications, personal accounts or unapproved services to complete legitimate business tasks.
The intention is usually positive. Employees want to work faster and produce better results.
The risk begins when confidential business information is copied into tools that the organization has not reviewed, approved or configured.
Your data may not literally be published for the world to see. However, it may leave the systems, access controls, contractual protections and governance framework established by your organization.
According to the Findstr design team, the question is no longer whether employees will use AI.
The real question is:
Will they use it inside an environment your organization can see, structure and control?
The Answer in Brief
Businesses should assume that employees are already using artificial intelligence at work.
The appropriate response is not simply to prohibit AI. Organizations should provide an approved environment, establish clear usage rules, centralize access, protect sensitive information and help employees understand which data can—or cannot—be submitted to an AI system.
Findstr provides a structured enterprise AI environment designed to connect organizational knowledge while giving the business greater visibility and control over AI usage.
Your Employees Are Probably Already Using AI
Artificial intelligence has become too accessible and useful to remain confined to formal technology projects.
A Canadian study published by IBM in September 2025 reported that 79% of Canadian office workers were using AI tools, while only approximately one in four relied on enterprise-grade AI solutions.
Microsoft research published in the United Kingdom in October 2025 found that 71% of employees had used unapproved consumer AI tools at work, with 51% continuing to use them every week.
Earlier research from Microsoft and LinkedIn also found that 78% of people using AI at work were bringing their own AI tools into the workplace rather than relying exclusively on tools supplied by their employer.
These figures send a clear signal.
AI adoption is not waiting for every organization to complete its policy, procurement and governance processes.
Employees are moving ahead because the technology helps them work.
When an organization does not offer an approved pathway, people often find their own.
What Information Are Employees Sharing with AI Tools?
An employee does not need to upload an entire database to create a risk.
Everyday prompts may contain:
- customer names and contact information;
- employee information;
- confidential financial figures;
- sales forecasts;
- internal strategies;
- contracts and legal correspondence;
- source code;
- passwords or system details;
- product roadmaps;
- meeting notes;
- unpublished marketing plans;
- proprietary procedures;
- personal information;
- information belonging to clients or partners.
A simple request such as “summarize this agreement,” “improve this proposal” or “analyze this customer list” can contain information the organization would never intentionally publish or send to an unknown third party.
Once this information leaves the approved environment, the organization may lose visibility into:
- which service received it;
- where it was processed;
- how long it may be retained;
- who may have access to it;
- whether it may be used to improve a service;
- which contractual terms apply;
- whether the account is controlled by the employee or the organization;
- and whether the information can later be deleted or audited.
The problem is not necessarily the employee’s intention.
The problem is the absence of a structured pathway.
Does an AI Tool Automatically Make Business Data Public?
No.
Submitting information to an AI service does not automatically mean that the information is published online or made directly available to every other user.
However, privacy and data-use conditions can vary significantly between:
- consumer accounts;
- business accounts;
- enterprise agreements;
- application programming interfaces;
- free services;
- paid services;
- optional data-sharing settings;
- and different AI providers.
For example, OpenAI states that it does not use data from its business, enterprise, education and API offerings to train its models by default. It separately provides controls allowing individual ChatGPT users to turn off the use of conversations for model improvement.
This distinction is important.
An enterprise product configured under an organizational agreement is not necessarily governed in the same way as a free consumer account opened independently by an employee.
The organization must know which environment is being used and under which terms.
Without this visibility, it cannot confidently assess the risk.
What Is Shadow AI?
Shadow AI is the use of artificial intelligence applications, models or services without the knowledge, authorization or governance of the organization.
It is the AI equivalent of shadow IT, but potentially more difficult to detect because an employee can paste sensitive information into a public interface within seconds.
Shadow AI may include:
- using a personal AI account for company work;
- uploading internal documents to an unapproved service;
- connecting an AI application to a corporate email account;
- installing an unauthorized browser extension;
- using a free transcription or meeting assistant;
- creating unofficial AI agents;
- connecting external tools to internal data;
- generating content from confidential client information.
The service may be useful and reputable.
The issue is that the organization has not evaluated or approved how it is being used.
Why Simply Prohibiting AI Is Unlikely to Work
Organizations may be tempted to block every generative AI service.
This can reduce certain immediate risks, but a prohibition alone rarely addresses why employees are using the tools.
People use AI because they are trying to:
- meet deadlines;
- reduce repetitive work;
- improve written communication;
- analyze more information;
- respond to clients faster;
- or compensate for limited internal resources.
When employees see clear value but are given no approved alternative, usage may continue outside official channels.
The organization then loses even more visibility.
A more effective strategy is to combine:
- an approved platform;
- practical policies;
- employee education;
- access controls;
- appropriate model selection;
- monitoring;
- and a clear process for approving new use cases.
The goal should not be to push AI usage further into the shadows.
It should be to bring it into view.
Why AI Governance Matters
The National Institute of Standards and Technology’s Generative AI Profile recommends that organizations identify, evaluate and manage the risks associated with generative AI in alignment with their own objectives and priorities.
AI governance helps an organization determine:
- which tools may be used;
- which information may be submitted;
- which use cases require approval;
- which models are appropriate;
- how outputs must be reviewed;
- how access is granted or revoked;
- how usage is documented;
- and who is responsible when an issue occurs.
Governance is not only a security exercise.
It creates a shared understanding of how the organization wants artificial intelligence to support its people, knowledge and operations.
Without a framework, every employee makes these decisions individually.
With a framework, the organization can connect innovation to accountability.
Seven Ways to Better Protect Business Data
1. Provide an Approved AI Environment
Employees need a practical alternative to personal and consumer tools.
An approved portal gives them a clear point of access while allowing the organization to select the models, configurations and knowledge sources that meet its requirements.
2. Define Which Information Is Sensitive
Employees should not have to guess whether a document can be shared with an AI system.
The organization should clearly classify information such as:
- public;
- internal;
- confidential;
- personal;
- privileged;
- restricted;
- or prohibited from external processing.
The rules should be simple enough to apply during everyday work.
3. Centralize Access
Centralized access helps the organization understand which tools are available and who is using them.
It can also simplify:
- account management;
- access removal;
- model selection;
- budgeting;
- support;
- and policy enforcement.
One structured entry point creates a clearer signal than hundreds of disconnected accounts.
4. Separate Consumer and Enterprise Usage
Employees should understand that a personal AI account and an organization-managed environment may have different contractual terms, security settings and data controls.
Business information should remain within solutions that the organization has evaluated and approved.
5. Limit the Data Sent to a Model
Employees should provide only the information required to complete the task.
Names, identifiers, confidential figures and unnecessary document sections should be removed whenever possible.
The right context is more valuable than the largest possible context.
6. Review Connections and Integrations
An AI tool connected to email, cloud storage, a customer relationship management platform or an internal knowledge base may access far more information than an employee manually pasting a paragraph.
Every integration should be reviewed according to:
- permissions;
- data scope;
- retention;
- logging;
- authentication;
- vendor terms;
- and revocation procedures.
7. Train Employees Continuously
A policy stored in a shared folder is not enough.
Employees need concrete examples showing:
- what they can submit;
- what they should never submit;
- which platform to use;
- how to verify an AI-generated answer;
- and who to contact when they are uncertain.
AI changes rapidly. Guidance must evolve with it.
How Findstr Helps Bring AI Usage into View
Findstr is a secure enterprise AI platform designed to centralize access, connect organizational knowledge and structure how artificial intelligence is used across teams.
Instead of leaving employees to navigate a growing number of disconnected AI services, Findstr creates a common environment in which an organization can define a clearer pathway.
Depending on the organization’s configuration, Findstr can help structure:
- access to approved AI models;
- shared organizational assistants;
- connected knowledge sources;
- user permissions;
- common instructions;
- usage policies;
- team access;
- and governance practices.
Findstr does not treat employees as the problem.
Employees are already demonstrating that they see value in artificial intelligence.
The role of the organization is to provide an environment where that value can be realized without unnecessarily exposing its knowledge, client information or internal operations.
Findstr Does Not Send All Company Data to Every Model
Connecting organizational knowledge to an AI environment should not mean making every document available to every user or transmitting all information with every request.
A structured approach should respect:
- user permissions;
- the relevance of the information;
- the sensitivity of the source;
- the model selected;
- and the context of the request.
The objective is not to share everything.
It is to help the right knowledge find the right person, through the right model, within the right context.
Protecting Organizational Memory
When AI work is performed through personal accounts, the resulting prompts, assistants, processes and expertise may remain isolated.
If the employee changes roles or leaves the organization, that knowledge may leave as well.
A shared enterprise environment makes it possible to transform effective individual practices into organizational assets.
The business can preserve:
- useful assistants;
- approved instructions;
- validated processes;
- shared knowledge connections;
- and effective ways of working.
This turns scattered experimentation into structured intelligence.
The Question Every Organization Should Ask
The question is no longer:
Are our employees using artificial intelligence?
In many organizations, they already are.
The better questions are:
- Which tools are they using?
- What information are they sharing?
- Under which accounts and contractual terms?
- Which models are receiving the information?
- Who can access the results?
- What knowledge should remain inside the organization?
- How can employees use AI safely without losing its benefits?
Organizations do not need to choose between innovation and control.
They need to give innovation a clear, secure and structured pathway.
Find the signal. Connect the knowledge. Protect what matters.
Discover Findstr and speak with our team about structuring artificial intelligence within your organization.
Frequently Asked Questions
Are employees already using AI at work?
In many organizations, yes. An IBM study published in 2025 reported that 79% of Canadian office workers used AI tools, while only approximately one in four used enterprise-grade solutions. Microsoft research has also identified widespread use of employee-selected or unapproved AI tools.
Does entering information into an AI tool make it public?
Not automatically. However, the information may leave the organization’s controlled systems and be processed or retained according to the provider’s terms and the type of account being used. Organizations should review these terms before allowing confidential information to be submitted.
What is shadow AI?
Shadow AI is the use of AI tools, accounts or integrations without organizational approval or oversight. It may include consumer chatbots, browser extensions, transcription applications, coding assistants and unofficial connections to company data.
What business information should not be entered into an unapproved AI tool?
Employees should avoid submitting confidential company information, personal information, customer data, contracts, privileged communications, passwords, internal code and proprietary strategies unless the organization has approved the tool and the specific use case.
Is a business AI account different from a personal account?
It can be. Business and enterprise offerings may provide different contractual protections, administrative controls, security features and data-use settings. Organizations should verify the specific terms of each service rather than assuming that all account types are equivalent.
Should businesses prohibit employees from using AI?
A prohibition alone may drive usage into unofficial channels. A stronger approach is to provide approved tools, clear policies, training, access controls and an escalation process for new use cases.
What is AI governance?
AI governance is the framework an organization uses to select, approve, monitor and manage artificial intelligence. It defines acceptable tools, data rules, responsibilities, human review requirements and security practices.
How does Findstr help protect business data?
Findstr provides a structured enterprise environment for accessing approved AI capabilities and connected organizational knowledge. This approach can help businesses centralize access, clarify permissions and establish more consistent governance.
Does Findstr replace every AI model?
No. Findstr acts as an organizational layer through which selected models, assistants and knowledge sources can be connected according to the organization’s requirements.
Can Findstr help reduce shadow AI?
Findstr can give employees a common, approved pathway for using artificial intelligence. Providing a practical enterprise alternative can reduce the need for employees to rely on disconnected personal tools.
Sources
- IBM Canada — “Shadow AI Use Surges as Canadian Workers Outpace Employers in AI Adoption,” September 3, 2025. IBM reported that 79% of Canadian office workers used AI tools, while only one in four used enterprise-grade AI solutions.
- Microsoft — “Rise in Shadow AI Tools Raising Security Concerns for UK Organisations,” October 13, 2025. Microsoft reported that 71% of UK employees had used unapproved consumer AI tools at work and that 51% did so weekly.
- Microsoft and LinkedIn — 2024 Work Trend Index, May 8, 2024. The report found that 78% of AI users brought their own AI tools to work.
- National Institute of Standards and Technology — Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile. The framework provides guidance for identifying and managing generative AI risks.
- OpenAI — Business Data Privacy and Data Controls documentation, consulted August 1, 2026. OpenAI states that business and API data are not used for model training by default and provides separate controls for individual accounts.