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Adoption of new technologies can alter an organisation’s attack surface, requiring security controls, testing, and risk management to change.

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Adoption is the extent to which people and organizations begin using a security technology, control, policy, or practice and incorporate it into routine work. In cybersecurity, adoption is more than purchasing or deploying a capability: it includes correct configuration, user participation, and continued use. Examples include enabling multifactor authentication, applying security patches, using secure coding practices, and collecting logs from systems that require monitoring.

Adoption matters because uneven or incomplete use leaves exploitable gaps. A partially deployed authentication control may protect some accounts while others remain exposed; delayed patch adoption can leave known vulnerabilities available to attackers; and missing or poorly configured logging can limit detection and investigation. Practitioners therefore assess coverage, exceptions, configuration quality, and whether controls operate as intended. Training, usable workflows, staged rollout, and measured policy compliance can improve adoption without encouraging insecure workarounds or unnecessary collection of personal data.

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Governance Professionals Struggle to Measure ROI and Control AI SystemsAI is becoming embedded across the enterprise, yet many organizations still can't quantify its value or answer key questions about oversight and control. ISACA's latest AI Pulse Poll reveals persistent uncertainty about AI ROI, governance and operational readiness, said GRCIE CEO Jenai Marinkovic.

Directs Agencies to Expand Commercial Access, Recruit Non-Gov ExpertsThe Trump administration's directed the military and intelligence agencies Friday to accelerate advanced artificial intelligence adoption while reducing barriers to deployment. It blames "undue bureaucracy" for a slower-than-desired pace of uptake.

Series A Funding Supports Visibility Across Cloud, Code and Endpoint EnvironmentsGeordie AI, the 2026 RSAC Innovation Sandbox winner, raised $30 million in Series A funding to expand a platform that provides visibility, governance and behavioral monitoring for AI agents operating across cloud, code and endpoint environments as enterprises accelerate autonomous AI adoption.