Secure AI Adoption with Confidence

Mission:

Receive an in-depth look at how your organization is navigating the AI landscape.

Approach:

We go beyond a basic assessment to uncover what is working, what is missing, and what needs to evolve.

Outcomes:

• A practical, forward-looking roadmap.
• Clarity to your AI investments.
• Confidence to your decision-making.

Mission:

Partner with your team to shape and strengthen your AI operating model.

Approach:

Development and refinement of:

• Strategy on AI tool development and use, and how it aligns with larger strategic goals.
• Governance model focused on programmatic elements such as planning, accountability, and authority.
• Capability to review AI activities, looking at both programmatic and technical solutions.

Outcomes:

• Strategy, plan, and protocols are defined and ready for immediate execution, built from stakeholder input and workshops.
• Hands-on guidance to help organizations drive stakeholder alignment and turn strategy into real-world adoption.
• A clear AI strategy and governance model enables organizations to move from reactive decisions to proactive, confident action.

Mission:

Establish formal AI governance through defined principles and objectives, roles and responsibilities oversight, and risk management and compliance alignment.

Approach:

• Stakeholder interviews.
• Impact and risk workshop.

Outcomes:

• The scope of the organization's AI program, and roles and responsibilities for relevant stakeholders.
• A RACI matrix that denotes areas where relevant stakeholders should be made responsible, accountable, consulted, or informed related to AI governance activities.
• AI-focused risk and impact assessment with recommendations for prioritization and remediation, including compensating controls.

Mission:

Stay ahead of evolving standards by understanding where your policies stand today and what needs to change.

Approach:

• Evaluate your current policies against emerging industry expectations.
• Identify new approaches and leading practices to strengthen your framework.
• Translate cybersecurity and AI governance into clear, business-aligned language.

Outcomes:

• Clear, actionable roadmap.
• Executive-level insights.
• Prioritized next steps.

Mission:

Strengthen the foundation that enables effective and responsible AI.

Approach:

Evaluation of existing data governance approach to identify gaps and opportunities across key areas, including accountability, transparency, ownership, and data lifecycle management.

Outcomes:

• Roadmap to improve data governance.
• Ensure alignment with business goals.

Mission:

Go beyond a surface-level assessment and understand how your AI program functions end to end.

Approach:

Through workshops and stakeholder interviews.

Outcomes:

• Clear visibility into your current state.
• A confident path toward a more mature, scalable AI program.

Mission:

Review what impact AI tools and technologies have on your organization.

Approach:

• Interviews and control reviews to explore the impact AI is having on the overall security program.
• Highlight gaps against best practices.

Outcomes:

• Gain greater insight into potential risks and deficiencies in AI programs and their impact on overall cybersecurity maturity.

Mission:

Evaluation to ensure strong security of CoPilot deployment.

Approach:

• Review AI platform configurations and access controls.
• Assess user permissions and sensitive data exposure.
• Evaluate AI governance, policies, and oversight processes.
• Analyze connectors, integrations, and data access pathways.
• Deliver prioritized recommendations and a maturity roadmap.

Outcomes:

• Gain clearer visibility into AI-related risks.
• Practical path to strengthen governance, security, and AI readiness.

Mission:

Examine AI native to third-party platforms, review configurations, and analyze potential key risks.

Approach:

• Through access granting or screen sharing.
• Review user entity controls to establish the level of alignment of the third-party application security controls with best practices.
• Review the application's purpose, its alignment with corporate security goals, and, if applicable, data management concerns.

Outcomes:

• Gain a greater understanding of potential risks when sharing data with third-party applications.
• Receive recommendations to improve alignment with best practices.

Mission:

Assess the current process for building AI-related assets, such as chatbots and agents, against best practices.

Approach:

Evaluation of your current development lifecycle against leading practices.

Outcomes:

• Greater confidence in your AI development lifecycle.
• Clear steps to align with best practices and reduce risk.

Mission:

Assess alignment with AI-relevant frameworks such as ISO 42001, NIST AI RMF, and more.

Approach:

• How effectively AI risks are identified, managed, and monitored across the lifecycle.
• Alignment of your policies, governance, and controls to recognized AI frameworks.
• Maturity of your organization's approach to trustworthy, secure, and compliant AI.

Outcomes:

• Understand how well your governance, risk, and control structures support responsible AI.
• Structured, actionable path to strengthen compliance, governance, and risk management.

Mission:

Develop deterministic guidelines for AI systems to reduce the likelihood of unplanned or unsanctioned actions and reduce the risk of potential cybersecurity incidents caused by a lack of technical AI governance.

Approach:

• Review documented policy and governance.
• Engage stakeholders to understand desired outcomes and required controls for AI systems.
• Develop policy language, such as Cedar or other Policy-as-Code controls.
• Review with key stakeholders.
• Allow the organization to implement and validate effectiveness.
• Complete a review period where feedback is collected and adjustments are suggested.

Outcomes:

• Gain confidence in the technical controls of your AI tools.
• Improve the overall security of the organization.
• Enable the organization to safely use the full capability of AI.

Mission:

Explore potential ways attackers can exploit vulnerabilities in an organization, including leveraging multiple attack paths.

Approach:

• Control and architecture reviews.
• Scenario-based workshops.

Outcomes:

• Organizations will be able to evaluate potential vulnerabilities.
• Organizations will be able to gauge their susceptibility to attacks without risking infrastructure or business processes.

Mission:

Take a high-level, strategic look at how your AI architecture is designed and where it may be exposed.

Approach:

Evaluation to uncover gaps in critical controls and structural alignment.

Outcomes:

• Greater confidence in your AI architecture.
• Clear priorities for strengthening and aligning to best practices and business objectives.