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Securing AI: Six steps to enable trusted innovation while addressing risk
An actionable roadmap to enable secure enterprise AI adoption, backed by governance, controls, validation, and continuous monitoring.
Map your path to trusted AI
Explore six essential steps leaders can take to secure AI and support enterprise innovation.
The new AI reality: Big opportunities, bigger risks
AI is moving faster than most security programs can adapt. New tools are rolling out across the business, teams are chasing efficiency and productivity gains, and experimentation is happening everywhere.
It’s an exciting moment—except for one hard reality: Many security teams lack the specialized resources, mature processes, and enabling technology to govern and secure AI risks at scale. With incomplete visibility, uneven controls, and inconsistent governance constraining their ability to act, the gap between what AI can do and what organizations can confidently control is widening by the day.
Key finding
82%
of CEOs surveyed by KPMG cited cybersecurity as their company’s top threat.
CISOs and security leaders need a path forward that matches the speed of the technology.
Our new report:
- Defines a clear, practical way to get ahead of AI adoption, establish guardrails that actually work, and keep innovation safe as it scales;
- Outlines six essential steps that help organizations shift from ad-hoc pilots to a secure, disciplined, and continuously monitored AI program;
- Shows how managed services can help organizations put a trusted AI program in motion quickly and efficiently.
The core capabilities of AI security
Securing AI doesn’t have to mean rebuilding your entire cybersecurity program. It’s about strengthening your existing framework and layering in the visibility, controls, and validation needed for a technology that behaves—and evolves—very differently from anything before it.
These six moves form the foundation:
1
Define the strategy
Align on AI priorities, decision rights, and accountability so security can guide adoption from the start.
Align on AI priorities, decision rights, and accountability so security can guide adoption from the start.
2
Build visibility
Identify where AI is being used, how it works, and who owns it to ensure every model and workflow is on the radar.
Identify where AI is being used, how it works, and who owns it to ensure every model and workflow is on the radar.
3
Strengthen governance
Update policies, roles, and review processes to reflect AI-specific risks, data flows, and model behaviors.
Update policies, roles, and review processes to reflect AI-specific risks, data flows, and model behaviors.
4
Integrate controls
Extend proven cybersecurity and compliance frameworks to cover model logic, training data, and third-party components.
Extend proven cybersecurity and compliance frameworks to cover model logic, training data, and third-party components.
5
Validate performance
Test AI systems early and often to confirm they behave as intended and to catch vulnerabilities before launch.
Test AI systems early and often to confirm they behave as intended and to catch vulnerabilities before launch.
6
Monitor continuously
Track model decisions in real time, detect drift or misuse, and adjust controls as risks and the technology change.
Track model decisions in real time, detect drift or misuse, and adjust controls as risks and the technology change.
These moves give organizations a clear path from scattered experimentation to secure, disciplined AI adoption. Each requires specific actions to make it real—something many overstretched security teams address through full-suite cyber managed services that can rapidly deliver the required talent, tooling, and scale.
How secure AI transforms performance
When the leading-practice structures and safeguards are in place, AI becomes something security teams can champion, rather than chase. Organizations using this secure AI framework can expect outcomes like:
Reduced enterprise risk
Fewer blind spots, clearer ownership, and stronger protection as AI adoption grows.
Faster, safer innovation
Guardrails that let teams move quickly without exposing the business.
More consistent decision-making
Reliable validation and monitoring that keep models accurate, explainable, and aligned with expectations.
Greater operational confidence
Clear processes that help security teams stay ahead of issues instead of responding after the fact.
Stronger cross-functional alignment
Shared frameworks that align security, data, legal, and business teams.
A scalable foundation for growth
A security program designed to evolve as AI expands across the enterprise.
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How KPMG Cyber Managed Services can help
Service
Cyber Managed Services
Strengthen defenses and upgrade operations with a human-led, AI-enabled approach that continuously learns, adapts, and protects.
Building a secure AI program takes more than a roadmap. It requires the talent, tooling, and continuous oversight to make each part work in practice. Our Cyber Managed Services team helps organizations put these capabilities into motion by delivering the governance, testing, and monitoring needed to keep AI secure as it scales.
Our KPMG professionals provide flexible, always-on support across strategy, discovery, validation, and runtime assurance. From AI maturity assessments and model testing to continuous monitoring and policy integration, we help organizations reduce risk, strengthen oversight, and keep pace with a rapidly changing threat landscape. With KPMG Cyber Managed Services, enterprises can operationalize trusted AI faster, with greater consistency, and without expanding internal headcount.
Meet the team
Connect with our KPMG Cyber Managed Services and AI security professionals to explore how KPMG can help your organization build, validate, and sustain a trusted AI program. Our specialists combine deep technical experience with proven delivery models to help clients stay secure, compliant, and ready for what’s next.
Katie Boswell
Managing Director, Cyber Security & Tech Risk Management, KPMG US
Chris Crevits
Principal, Advisory, Cyber Managed Services, KPMG US
Kristy Hornland
Director Advisory, Cyber Security Services, KPMG US
Weston Cole
Specialist Director, Delivery Management, Managed Services Market Growth and Client Success, KPMG US
Griffin Reid
Specialist Director, Delivery Management, Managed Services Cyber, KPMG US
Sai Gadia
Partner, Cyber Security Services, KPMG LLP
Katie Boswell
Managing Director, Cyber Security & Tech Risk Management, KPMG US
Chris Crevits
Principal, Advisory, Cyber Managed Services, KPMG US
Kristy Hornland
Director Advisory, Cyber Security Services, KPMG US
Weston Cole
Specialist Director, Delivery Management, Managed Services Market Growth and Client Success, KPMG US
Griffin Reid
Specialist Director, Delivery Management, Managed Services Cyber, KPMG US
Sai Gadia
Partner, Cyber Security Services, KPMG LLP