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Use Case

Govern and Secure Enterprise AI Use

Govern and secure enterprise AI use with clear policies, approved tools, controls on sensitive data and oversight of how AI outputs are used.

The Challenge

Why AI Use Needs Governance

Staff adopt AI tools quickly. Without rules, sensitive data can leak and unchecked outputs can mislead.

Data Leakage

Confidential information pasted into public tools.

No Policy

No rules on acceptable use.

Unchecked Outputs

AI answers used without review.

Is This Relevant?

Is This Use Case Relevant to Your Organization?

The people, moments and signals that usually bring this need to the surface.

Relevant Teams

  • Security and IT leaders
  • Legal, privacy and compliance
  • Business leaders

Common Triggers

  • Rapid staff adoption of AI tools
  • A data leak involving AI
  • Customer or regulatory questions about AI use

Warning Signs

  • No AI acceptable-use policy
  • Unknown AI tools in use
  • Sensitive data in public AI tools

Typical Environments

  • Business applications, documents and knowledge bases
  • Cloud and on-premises data platforms

Benefits

What Better Looks Like

Intended benefits. Actual results depend on your environment and starting point.

Clear Policy

Rules on which tools and data may be used.

Protected Data

Controls that keep sensitive data safe.

Responsible Use

Staff trained to use AI well.

Our Approach

A Practical Approach

Start small, prove value, then scale with the right controls. Each stage is tailored to your environment.

Assess

Review data, systems, security, policies and candidate use cases.

Prioritize

Rank what you find by business impact, effort and risk, and agree where to start.

Design

Agree priority use cases, the architecture and guardrails.

Implement

Build pilots and integrate AI with business systems and data.

Validate and Optimize

Measure accuracy, value and user adoption against agreed goals.

Technology

Technology Options

Where technology fits in the approach. Specific platforms and partner status are confirmed for each engagement.

AI Models and Platforms

Large language models and AI services from established providers.

AI Security and Governance

Access controls, logging and policy tools for AI use.

Before You Start

What to Consider Before Getting Started

A little preparation makes the first assessment faster and its findings more reliable.

  • Approved tools and their data handling
  • Classification of data AI may use
  • Monitoring and enforcement options
  • Training and communication
  • Who will own the work and act on recommendations
  • Engagement model and ongoing support

Measuring Success

How to Measure Success

Illustrative measures. Agree a baseline first, and keep targets separate from measured results.

Approved Tool Usage

Use of approved AI tools.

Policy Exceptions

Uses outside policy.

Blocked Data Uploads

Sensitive data stopped from leaving.

Staff Trained

Employees trained on AI use.

Our Approach

How We Deliver Results

How Signisys works, from the first assessment to handover and beyond.

Learn More

01

A Defined Methodology

Every engagement follows the Signisys delivery methodology, with agreed stages, checkpoints and handover.

02

Agreed Baseline

Each engagement records your starting point first, so progress is measured against where you began.

03

Skills Matched to the Work

Each engagement is staffed for the platforms and skills in scope, agreed with you during planning.

04

Clear Success Measures

Success measures are agreed at the start and reviewed with you at every checkpoint.

FAQs

Frequently Asked Questions

Common questions about this use case.

Do we need an AI policy if we do not use AI officially?

Yes. Staff are likely using AI tools already, so clear rules and approved options reduce risk.

Will governance stop people using AI?

The aim is safe use, not none: approved tools and clear rules let people benefit while protecting data.

What information is needed to get started?

Current AI tool use, data classification, existing security and privacy policies, and your goals for AI.

Which environments does this apply to?

Business applications, documents and knowledge bases, on cloud or on-premises platforms.

How is progress measured?

Agree a baseline for measures such as approved tool usage, policy exceptions, blocked data uploads and staff trained, then track them over time.

Related Content

Related Outcomes, Use Cases and Guides

Where to go next: the outcome this use case supports, nearby scenarios, technology partners and practical guides.

Technology Partner

Adobe Solutions and Services

Problem Explainer

What Causes Uncontrolled AI Use? Common Problems and Warning Signs

Coming soon

How-To Guide

How to Govern and Secure Enterprise AI Use: A Practical Step-by-Step Guide

Coming soon

Checklist

Govern and Secure Enterprise AI Use Checklist: What IT Teams Should Assess

Coming soon

Decision Guide

How to Choose the Right Approach to Govern and Secure Enterprise AI Use: Options and Trade-Offs

Coming soon

Govern AI Use

Share your current challenges and priorities with Signisys to explore an approach suited to your environment.

Book a Consultation

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