Info-Tech Research Group’s newly released research blueprint provides IT and security leaders with a strategic plan for identifying and mitigating AI risks. The framework from the global IT research and advisory firm helps organizations launch effective AI red-teaming practices to safeguard their systems, ensure compliance, and strengthen resilience across rapidly evolving threat landscapes.
TORONTO, April 23, 2025 /PRNewswire/ – As artificial intelligence (AI) becomes deeply embedded in enterprise workflows, a new category of cybersecurity risk is rapidly emerging. While AI tools are increasingly used to drive innovation and automation, threat actors are also using the technology to exploit new vulnerabilities and scale attack vectors. To help organizations confront these emerging risks, Info-Tech Research Group has recently released its blueprint, Get Started With AI Red-Teaming, which outlines a strategic, four-step framework to help organizations test and secure their AI systems against sophisticated attacks. The firm’s research addresses the growing gap between AI adoption and readiness to confront AI-specific threats such as prompt injection, data poisoning, and adversarial manipulation.
Info-Tech Research Group’s newly released research blueprint provides IT and security leaders with a strategic plan for identifying and mitigating AI risks. The firm’s framework helps organizations launch effective AI red-teaming practices to safeguard their systems, ensure compliance, and strengthen resilience across rapidly evolving threat landscapes. (CNW Group/Info-Tech Research Group)
AI red-teaming is a security exercise adapted from traditional cybersecurity practices, focused explicitly on challenging AI systems, including machine learning (ML) models and generative AI applications, to uncover hidden vulnerabilities, biases, and system limitations. While threat actors continue to weaponize AI for complex attacks, many organizations remain unprepared, lacking a dedicated plan to test their AI tools or defend against misuse.
“AI technologies have enabled organizations to scale productivity, accelerate innovation, and enhance their security posture,” says Ahmad Jowhar, Research Analyst at Info-Tech Research Group. “But with that growth comes an evolving threat landscape, as malicious actors leverage AI to increase the sophistication and reach of their attacks. AI red-teaming provides a necessary countermeasure, helping organizations proactively identify vulnerabilities and apply meaningful guardrails.”
Info-Tech’s resource also highlights the emerging global regulatory momentum around AI safety. Countries such as the USA, Canada, UK, EU member states, and Australia are moving to adopt standards that recommend or mandate AI red-teaming to ensure the safe use of these technologies. By aligning with these evolving frameworks, organizations can improve compliance while enhancing the resilience of their AI infrastructure.
Info-Tech’s Strategic Four-Step Framework for AI Red-Teaming
The following practical framework from Info-Tech Research Group’s recently published blueprint can help organizations initiate and operationalize an effective AI red-teaming practice:
- Define the Scope: Identify which AI technologies and use cases will be tested. These may include Gen AI models, AI-enabled chatbots, or traditional ML systems.
- Develop the Framework: Build a multidisciplinary team, including security, compliance, and data science experts, and align processes with existing best-practice methodologies and frameworks such as Microsoft AI Red Team, MITRE ATLAS, NIST AI RMF, and the OWASP Gen AI Guide.
- Select Tools & Technology: Evaluate tools and technologies that support adversarial testing and AI model validation, such as those highly rated by end users on Info-Tech’s SoftwareReviews platform, and ensure they meet organizational needs, align with in-house capabilities, and follow AI security best practices.
- Establish Metrics: Set KPIs to monitor effectiveness, including the number of exploitable vulnerabilities, successful adversarial attacks, and adherence to regulatory frameworks.
“To be effective, AI red-teaming requires more than technical testing; it demands a strategic plan that defines clear goals and identifies the right people, processes, and technologies to manage risk and reinforce trust in AI systems,” adds Jowhar.
In addition to reducing exploitable vulnerabilities, the firm advises that effective AI red-teaming improves visibility into AI system behavior, supports ethical and compliant design, and helps restore trust in high-stakes environments such as healthcare, finance, and government.
For exclusive and timely commentary from Ahmad Jowhar or to access the complete Get Started With AI Red-Teaming research, please contact [email protected].
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About Info-Tech Research Group
Info-Tech Research Group is one of the world’s leading research and advisory firms, proudly serving over 30,000 IT and HR professionals. The company produces unbiased, highly relevant research and provides advisory services to help leaders make strategic, timely, and well-informed decisions. For nearly 30 years, Info-Tech has partnered closely with teams to provide them with everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.
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SOURCE Info-Tech Research Group
