A news summary based solely on the provided article body: Artificial intelligence is rapidly becoming a core driver of enterprise productivity, but many enterprises are moving faster on AI adoption than on cybersecurity readiness. AI systems often integrate directly with enterprise data, digital infrastructure, and external platforms, significantly expanding the organisational attack surface. Without strong security foundations, the productivity benefits of AI cannot scale safely or sustainably. The rapid growth of AI adoption is largely driven by the need for speed and efficiency, with generative AI tools lowering the barrier to entry for AI experimentation across departments. However, this decentralised adoption can create blind spots, as business units may deploy AI tools without comprehensive security review, potentially exposing sensitive data or critical infrastructure. AI systems rely on complex technology ecosystems including training data pipelines, machine learning models, APIs, cloud infrastructure, and automated decision systems, each introducing potential security risks. Cybersecurity researchers have identified emerging threats such as adversarial attacks that manipulate models, data poisoning attacks that alter training datasets, and prompt injection attacks that manipulate AI systems into bypassing safeguards.