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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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Blackstone-Led Funding Round Expands R&D and Partnerships to Address AI ThreatsWith AI adoption outpacing security readiness, Cyera secured $400 million at a $9 billion valuation to protect data in an agentic AI landscape. The company plans to expand engineering efforts and partner with tech giants to create a control plane for enterprise AI use.

Bank Info Security 6 months, 1 week ago

Zero Trust for the Age of Autonomous AI Agents - Part 1

Why Human-Centric Zero Trust Models Fail in a World of Autonomous AI AgentsZero trust was built for humans, not autonomous AI agents. As organizations adopt agentic AI at scale, human-centric security assumptions break down - creating a paradox between utility and least privilege that traditional zero trust models cannot resolve.