Secure Generative AI for Government & DIB Professionals
Duration: 1 Day | 6-8 Hours
Delivery: Instructor-Led Virtual or Onsite
Generative AI can improve productivity, research, analysis, and decision support, but its use can also create significant risks when employees work with government, proprietary, controlled, or sensitive information. Secure Generative AI for Government & DIB Professionals provides practical guidance for using generative AI while protecting organizational and government information.
Participants will examine common AI use cases, data exposure risks, third-party AI services, responsible prompting, organizational policies, and security practices. Real-world scenarios help participants determine what information should and should not be entered into AI systems and how to use generative AI more securely in government and Defense Industrial Base environments.
Students Will Learn To:
Ideal for: Government personnel, federal contractors, DIB employees, program and project managers, cybersecurity professionals, IT staff, business professionals, and organizations introducing generative AI into environments that handle government or sensitive information.
Delivery: Instructor-Led Virtual or Onsite
Generative AI can improve productivity, research, analysis, and decision support, but its use can also create significant risks when employees work with government, proprietary, controlled, or sensitive information. Secure Generative AI for Government & DIB Professionals provides practical guidance for using generative AI while protecting organizational and government information.
Participants will examine common AI use cases, data exposure risks, third-party AI services, responsible prompting, organizational policies, and security practices. Real-world scenarios help participants determine what information should and should not be entered into AI systems and how to use generative AI more securely in government and Defense Industrial Base environments.
Students Will Learn To:
- Understand generative AI and large language models at a practical level
- Identify appropriate and inappropriate uses of generative AI in government and DIB environments
- Recognize risks associated with entering sensitive information into AI tools
- Understand considerations surrounding CUI, FCI, proprietary information, personal information, and other sensitive data
- Evaluate the security and privacy implications of public and enterprise AI services
- Recognize common AI threats, including prompt injection and sensitive information disclosure
- Apply secure prompting and data-handling practices
- Understand the importance of approved AI tools and organizational acceptable-use policies
- Identify risks associated with AI-generated content, including inaccurate or fabricated information
- Verify and appropriately handle AI-generated outputs
- Apply practical security practices when incorporating AI into everyday workflows
- Recognize when an AI use case should be escalated for security, privacy, legal, or management review
Ideal for: Government personnel, federal contractors, DIB employees, program and project managers, cybersecurity professionals, IT staff, business professionals, and organizations introducing generative AI into environments that handle government or sensitive information.
AI Governance & NIST AI Risk Assessment Framework
Duration: 1 Day | 6-8 Hours
Delivery: Instructor-Led Virtual or Onsite
Organizations adopting artificial intelligence need a structured way to identify opportunities while managing security, privacy, reliability, accountability, and other AI-related risks. AI Governance & NIST AI Risk Management Framework introduces participants to practical AI governance and the NIST AI Risk Management Framework (AI RMF).
Participants will explore the AI RMF's Govern, Map, Measure, and Manage functions and learn how they can be applied to organizational AI initiatives. The course connects the framework to practical activities such as AI inventories, risk assessments, policies, roles and responsibilities, third-party risk, documentation, oversight, and ongoing monitoring.
Students Will Learn To:
Ideal for: Executives, AI program leaders, CISOs, CIOs, cybersecurity professionals, risk managers, compliance teams, privacy professionals, government personnel, DIB organizations, and individuals responsible for AI governance or risk management.
Delivery: Instructor-Led Virtual or Onsite
Organizations adopting artificial intelligence need a structured way to identify opportunities while managing security, privacy, reliability, accountability, and other AI-related risks. AI Governance & NIST AI Risk Management Framework introduces participants to practical AI governance and the NIST AI Risk Management Framework (AI RMF).
Participants will explore the AI RMF's Govern, Map, Measure, and Manage functions and learn how they can be applied to organizational AI initiatives. The course connects the framework to practical activities such as AI inventories, risk assessments, policies, roles and responsibilities, third-party risk, documentation, oversight, and ongoing monitoring.
Students Will Learn To:
- Understand the purpose and structure of the NIST AI Risk Management Framework
- Understand the Govern, Map, Measure, and Manage functions
- Identify and categorize risks associated with AI systems and use cases
- Establish roles and responsibilities for AI governance
- Develop an inventory of organizational AI systems and use cases
- Evaluate AI risks in the context of business and mission objectives
- Identify security, privacy, reliability, transparency, and accountability considerations
- Develop practical AI policies, standards, and governance processes
- Assess risks associated with third-party AI technologies and vendors
- Identify appropriate risk measures and controls
- Document AI risks and communicate them to organizational stakeholders
- Establish processes for monitoring AI risks throughout the AI lifecycle
- Use the NIST AI RMF to support more trustworthy and responsible AI adoption
- Begin developing an organizational AI risk management roadmap
Ideal for: Executives, AI program leaders, CISOs, CIOs, cybersecurity professionals, risk managers, compliance teams, privacy professionals, government personnel, DIB organizations, and individuals responsible for AI governance or risk management.
AI, CMMC & CUI: Managing AI Risk in the DIB
Duration: 1 Day | 6-8 Hours
Delivery: Instructor-Led Virtual or Onsite
The rapid adoption of generative AI creates an important question for Defense Industrial Base organizations: How can employees take advantage of AI without putting Federal Contract Information, Controlled Unclassified Information, or other sensitive information at risk?
AI, CMMC & CUI: Managing AI Risk in the DIB examines how the use of generative AI intersects with existing cybersecurity, information protection, and CMMC responsibilities. Participants will explore scenarios involving employees, contractors, AI assistants, third-party AI platforms, and AI-enabled business applications to understand where new risks can emerge.
The course does not treat AI as a separate set of CMMC controls. Instead, it helps participants understand how AI adoption can affect an organization's existing responsibilities for protecting FCI and CUI and how established cybersecurity practices can be applied to emerging AI use cases.
Students Will Learn To:
Ideal for: Defense contractors, DIB cybersecurity teams, CMMC program managers, compliance professionals, CISOs, IT managers, security professionals, executives, program managers, and employees responsible for protecting FCI and CUI.
Delivery: Instructor-Led Virtual or Onsite
The rapid adoption of generative AI creates an important question for Defense Industrial Base organizations: How can employees take advantage of AI without putting Federal Contract Information, Controlled Unclassified Information, or other sensitive information at risk?
AI, CMMC & CUI: Managing AI Risk in the DIB examines how the use of generative AI intersects with existing cybersecurity, information protection, and CMMC responsibilities. Participants will explore scenarios involving employees, contractors, AI assistants, third-party AI platforms, and AI-enabled business applications to understand where new risks can emerge.
The course does not treat AI as a separate set of CMMC controls. Instead, it helps participants understand how AI adoption can affect an organization's existing responsibilities for protecting FCI and CUI and how established cybersecurity practices can be applied to emerging AI use cases.
Students Will Learn To:
- Understand how generative AI is being used across the Defense Industrial Base
- Identify AI use cases that may create risks to FCI, CUI, proprietary information, and other sensitive data
- Understand how AI use can intersect with existing CMMC security requirements and practices
- Recognize data leakage scenarios involving public and third-party AI services
- Identify risks associated with employees copying sensitive information into AI prompts
- Evaluate AI-enabled applications and services before introducing them into sensitive environments
- Understand access control and identity considerations for enterprise AI
- Assess third-party and supply-chain risks associated with AI providers
- Identify logging, monitoring, and incident-response considerations for AI use
- Develop appropriate AI acceptable-use rules for employees and contractors
- Establish procedures for evaluating and approving AI tools
- Recognize AI-related activities that may require additional security review
- Incorporate AI risks into existing cybersecurity risk assessments
- Prepare the workforce to use AI without undermining established information-protection practices
- Develop practical next steps for integrating AI risk management into an organization's cybersecurity and CMMC program
Ideal for: Defense contractors, DIB cybersecurity teams, CMMC program managers, compliance professionals, CISOs, IT managers, security professionals, executives, program managers, and employees responsible for protecting FCI and CUI.
