Take control of Shadow AI before it becomes a business risk
Identify unapproved AI use, reduce data exposure and give employees a practical framework for using AI safely at work.
Unapproved AI usage is already inside many organisations.
Employees often adopt AI to save time and improve output. Risk appears when the business can't see which tools are being used or what information is being shared.
Find current usage
Understand public AI tools, personal accounts, browser extensions and AI-enabled SaaS.
Assess data exposure
Identify where confidential, personal or regulated information may be shared.
Set practical rules
Give employees clear guidance on approved tools, restricted data and output checking.
Provide safer alternatives
Introduce approved platforms and workflows that support useful adoption.
Shadow AI creates risk when visibility and governance fall behind use.
Most unmanaged activity starts with good intentions. The business still needs to understand the tools, information and decisions involved.
Sensitive data exposure
Client, financial, HR or commercial information is entered into public tools.
Personal AI accounts
Employees use services outside approved business identity and access controls.
Browser extensions
AI add-ons may access documents, emails, web pages or internal systems.
Compliance gaps
AI use is not aligned with GDPR, contracts or sector requirements.
Unverified outputs
Teams rely on inaccurate or fabricated information without appropriate review.
Loss of visibility
Leadership can't see which tools are used, why they are used or where risk sits.
Visibility, policy, technology and education need to work together.
Blocking tools alone rarely resolves the underlying demand. A stronger approach gives employees useful routes to work safely.
The goal is to reduce unmanaged exposure while preserving the productivity benefits that encouraged employees to use AI in the first place.
Discover
Identify tools, accounts, browser features and employee workflows.
Usage viewAssess
Review data sharing, compliance, access and third-party platform risk.
Exposure viewControl
Introduce policy, approved tools, identity and technical safeguards.
Governance viewEnable
Train employees, support useful workflows and review adoption over time.
Adoption viewUnderstand where Shadow AI risk appears.
The review considers the tools employees use, the information involved and whether existing policy and controls provide enough direction.
Sensitive data exposure
Reduce the risk of confidential information entering unapproved AI tools.
Unmanaged accounts
Identify personal accounts and platforms outside business controls.
Browser extensions
Review AI plugins that can access documents, email and internal systems.
Compliance alignment
Connect AI use with GDPR, contracts and internal data protection policy.
Third-party AI features
Assess AI capabilities added to SaaS platforms already used by teams.
Policy uncertainty
Give employees clear guidance on approved tools, restricted data and responsibilities.
Output validation
Set expectations around checking accuracy, sources and business decisions.
A practical route from unmanaged use to secure adoption.
The work gives leadership visibility, employees clearer guidance and technical teams a defined set of controls.
AI usage discovery
Review tools, accounts, browser features, SaaS capabilities and workflows.
Risk review
Assess data sharing, third parties, compliance and unmanaged exposure.
Acceptable use policy
Define approved tools, restricted data, responsibilities and escalation.
Technical controls
Strengthen identity, browser governance, permissions and information protection.
Training and monitoring
Build awareness and review how AI usage changes over time.
Bring AI use into the open before setting the controls.
We first understand why employees use AI and which workflows matter, then shape the policy, technology and approved alternatives around that reality.
Discover usage
Build a view of tools, accounts, teams, workflows and information involved.
Assess exposure
Prioritise the behaviours and platforms creating the greatest risk.
Set governance
Define policy, ownership, approved tools and data-handling rules.
Introduce controls
Apply identity, browser, Microsoft 365 and information protection measures.
Educate and review
Train employees and update the approach as tools and behaviours change.
Security and AI adoption considered together.
Shadow AI crosses security, Microsoft 365, compliance and employee behaviour. Fifosys can connect those areas in one practical programme.
Practical discovery
The review focuses on real employee tools and workflows.
Security context
Data exposure, identity and access are assessed together.
Usable policy
Guidance is clear enough for employees to apply day to day.
Safer adoption
Approved alternatives help the business retain useful AI benefits.
Find out where AI is already being used across your organisation.
A readiness and Shadow AI review can establish current activity, exposure and the controls needed next.
Clear answers to common Shadow AI questions
Connect this work to the wider AI strategy.
Bring Shadow AI into the open before it exposes the business.
Tell us what you know about current AI use, where visibility is limited and what concerns you about company data. We will help you define the right response.
Understand tools, accounts and employee workflows.
Identify data exposure and governance gaps.
Create practical controls and safer alternatives.