AI Security and Governance Services for Regulated Organizations

AI is already present in most regulated organizations, whether formally approved or not. Employees experiment with generative tools, vendors embed AI into products, and leadership teams explore use cases under pressure to move quickly. Without structure, this activity introduces AI security and compliance risk that is difficult to see, explain, or defend.

For financial institutions and other regulated organizations, AI raises familiar questions in new ways: How is data being used? Who owns the risk? How are AI-driven decisions governed? And how will regulators evaluate oversight? AI security and governance services help organizations address these questions before they surface as audit findings or control gaps.

SBS offers AI services designed to support regulated organizations at different stages of AI maturity, from early exploration to enterprise-level oversight. Combined, these governance services help move AI use from informal experimentation to a structured, defensible program, providing a foundation for secure, compliant, effective, and ethical AI adoption.

Why AI Security and Governance Matter

Effective AI governance is not about slowing innovation. It is about ensuring AI use is intentional, documented, and aligned with existing risk management practices. The right AI services help organizations:

• Identify and manage AI security risks tied to data, models, and decision-making.
• Establish clear ownership and accountability for AI initiatives.
• Reduce exposure from informal or "shadow" AI use.
• Support regulatory readiness as examiner expectations for AI governance evolve.
• Build confidence with executives, boards, and regulators.

Organizations that invest early in AI security and governance are better positioned to expand AI use responsibly without relying on reactive controls or assumptions.

AI Risk Assessment

An AI risk assessment evaluates the use of artificial intelligence across the organization. This includes reviewing data inputs, access controls, use cases, documentation practices, and alignment with existing risk and compliance frameworks.

The assessment highlights areas where AI introduces new or unmanaged risk, such as insufficient oversight, unclear accountability, or gaps in policy coverage. Findings are prioritized to support practical remediation planning and stronger AI risk management.

Why it matters: Many organizations discover AI security gaps only after an examiner or auditor asks the right question. An AI risk assessment provides clarity and context before that happens.

When it's needed: An AI risk assessment is beneficial early in AI adoption, when new AI tools or use cases are introduced, or ahead of regulatory exams, audits, or board discussions that require clear visibility into AI-related risk.

Virtual Chief AI Officer

The virtual chief AI officer (vCAIO) provides executive-level leadership and oversight for AI initiatives without the need for a full-time role. This service helps organizations move from isolated experimentation to a structured AI governance and risk management program.

Guided by the NIST AI Risk Management Framework and the NIST Cybersecurity Framework, the vCAIO works with leadership to define AI strategy, establish governance structures, assess AI security risk, validate vendors, deploy pilot projects, and document outcomes.

Why it matters: AI is not just a technology decision — it is a business, compliance, and risk decision. The vCAIO ensures AI efforts remain intentional, coordinated, and defensible as they scale.

When it's needed: Organizations should engage a vCAIO when AI use spans multiple departments, when leadership needs formal governance and accountability, or when boards and regulators expect structured oversight of AI strategy and risk.

AI Copilot Training

AI Copilot training guides the secure and compliant use of Microsoft Copilot and similar approved AI tools within regulated environments. Training is tailored to business, IT, risk, and compliance teams and reinforces governance expectations, data boundaries, and appropriate use.

Sessions combine practical examples with clear guidance on how AI tools should be used within established policies and risk tolerances.

Why it matters: Without training, employees may unintentionally expose sensitive data or bypass existing controls. Training supports consistent AI security practices and reduces operational risk.

When it's needed: AI Copilot training is most effective when Copilot or similar tools are first deployed and should be revisited as functionality expands, policies are updated, or regulatory expectations become clearer.

Certified Banking AI Strategist

The Certified Banking AI Strategist (CBAIS) course, offered through the SBS Institute, builds internal expertise in AI security, governance, and risk management for financial institutions. The program blends strategic frameworks with hands-on assignments and real-world scenarios tailored to regulated environments.

Across seven modules, participants learn how to evaluate AI platforms, identify high-value use cases, manage AI vendor risk, establish governance practices, and apply tools such as Microsoft Copilot responsibly.

Why it matters: Strong AI governance depends on informed leaders who understand both opportunity and risk. CBAIS helps institutions develop internal capability to guide AI use with confidence and consistency.

When it's needed: Institutions should consider CBAIS certification to develop internal AI leaders, clarify ownership of AI initiatives, and align cross-functional teams.

Where to Start

Not every organization needs every AI service at once. Teams early in their AI journey often begin with an AI risk assessment to establish visibility and priorities. Organizations introducing Copilot or similar tools typically pair training with updated governance. When AI programs grow more complex, a vCAIO offers ongoing guidance, and CBAIS helps teams develop lasting internal expertise.

The right starting point depends on how widely AI is used today and how confidently leadership can explain that use to regulators.

Building a Repeatable, Defensible AI Program

AI security and governance are ongoing disciplines, not one-time initiatives. Successful organizations treat AI like any other material risk area: They assess it, assign ownership, document decisions, and review it regularly.

By combining AI security services, executive oversight, and internal education, regulated organizations can move from informal experimentation to a structured AI program that supports innovation without sacrificing control.