This paper evaluates artificial intelligence use cases for cyber defense and enterprise offensive security in a general enterprise environment. It examines defensive applications such as SOC alert triage, threat intelligence analysis, secure code review, detection engineering, incident response support, identity analytics, attack surface prioritization, and autonomous remediation. It also evaluates authorized offensive security use cases, including reconnaissance, exploitability validation, web and API testing, cloud and identity attack-path testing, phishing simulation, adversary emulation, detection evasion testing, and reporting support. The paper emphasizes evidence-backed controls, implementation requirements, risk tradeoffs, procurement considerations, reference architecture, pilot design, governance ownership, and success metrics. It distinguishes authorized enterprise offensive security from malicious attacker enablement and treats external adversary use of AI as threat context for what security teams should emulate and defend against.