Insyto Consulting Services

AI Governance & Security Consulting

Insyto helps leadership define how AI use cases are approved, how data and model risk are evaluated, and who owns policy and oversight. The engagement covers enterprise AI governance broadly; Microsoft Copilot readiness remains a separate platform-specific assessment.

Discuss AI governanceReview engagement deliverables
Decision pathwayINSYTO / CONSULTING
  1. 01AI use cases
  2. 02Data & risk
  3. 03Ownership
  4. 04Controls
  5. 05Governance plan
Decision-ready roadmap

Evidence and priorities guide the next decision; deployment is a separate scope.

When this engagement is useful

CIOs, CISOs, data leaders, legal and compliance stakeholders who need a repeatable decision process before AI adoption expands across business units and platforms.

  • Business teams adopt AI tools without a common approval or risk-review process.
  • Acceptable use, sensitive-data handling and accountability are unclear.
  • Technical controls are discussed before use cases and risk tiers are defined.
  • Leadership lacks a consolidated view of approved systems, owners and unresolved AI risks.

What Insyto reviews

We facilitate business, security, data and compliance decisions, review the current AI landscape and design a governance model proportionate to the organization and the use cases in scope.

Assessment domains
  1. AI use cases and risk tiersApproved, proposed and observed AI use
  2. Data and access riskEnterprise data, identities and AI platforms
  3. Policy and control expectationsEnterprise AI and Microsoft environments
  4. Governance and executive oversightOperating model

Approved, proposed and observed AI use

AI use cases and risk tiers

Create a basis for proportionate review rather than treating every AI use case alike.

  • Business purpose, users and accountable owners
  • Data, model and automation characteristics
  • Risk classification and approval criteria

Enterprise data, identities and AI platforms

Data and access risk

Assess what information AI systems can receive, retrieve or expose.

  • Data classification and permitted-use boundaries
  • User, service and privileged access controls
  • Third-party handling, retention and integration considerations

Enterprise AI and Microsoft environments

Policy and control expectations

Translate governance principles into practical requirements.

  • Acceptable use, prohibited use and exception handling
  • Logging, monitoring and human-review expectations
  • Security incident and model-output escalation paths

Operating model

Governance and executive oversight

Define who makes, records and revisits AI decisions.

  • Decision rights across business, IT, security, data and legal
  • Risk-register, inventory and review cadence
  • Metrics and reporting needed for executive visibility

Evidence behind the assessment

Discovery reviews an agreed sample of proposed and existing AI use cases, data flows, access paths, vendor handling terms and current policies with business, security and data owners. We record where an AI workflow is not sufficiently documented to approve.

Insyto provides technology, security and governance advice, not legal opinions. Policy approval, regulatory interpretation and risk acceptance remain with the organization and its qualified advisors.

Business questions the engagement answers

  • Which AI use cases are permitted, restricted or require enhanced review?
  • What data and actions can each system access?
  • Who approves exceptions and accepts residual risk?
  • How will leadership know whether governance is operating as intended?

What your team receives

The final materials separate observed findings, assumptions and decisions so leadership and delivery teams can act on the same record.

  • An inventory and risk-tiering approach for in-scope AI use cases.
  • AI policy and acceptable-use principles for stakeholder review.
  • Governance roles, decision rights and escalation paths.
  • Data, access, monitoring and evidence requirements.
  • A prioritized governance roadmap and executive risk briefing.

What the findings mean

The output distinguishes use cases that can proceed under current controls, those needing additional safeguards and those needing an explicit leadership decision. It assigns governance owners and review triggers; it does not approve tools or make legal determinations for the customer.

How the engagement works

01

Inventory use and stakeholders

Identify platforms, use cases, data, owners and the business and regulatory concerns that governance must address.

02

Evaluate risk and decisions

Classify use cases, review controls and facilitate agreement on policy, ownership and evidence requirements.

03

Design the operating model

Document decision rights, control expectations, reporting and a roadmap for implementation and recurring review.

Configuration changes, deployments, migrations and recurring administration are not included automatically. Those activities begin only under an approved implementation or managed-service scope.

From findings to implementation and operations

Consulting identifies decisions and priorities. The next engagement depends on the findings; it is not predetermined by the assessment.

Managed Services

Managed Security Services

Operate agreed security controls and response workflows after the governance decisions are implemented.

Connection to Data & AI guidance

Governance establishes decision rights and control requirements for role-aware AI grounded in approved enterprise information.

Explore Data & AI guidance

Evidence and guidance

Microsoft 365 and Purview are one platform context for the data and access controls reviewed here; the governance model also covers other approved AI tools. Explore Microsoft technology

Turn AI concerns into accountable decisions

Tell us which AI tools and use cases are already under discussion. We can define the stakeholders, risks and governance outputs needed before adoption expands.

Discuss AI governance
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