Employees leaking company secrets. Traceability gaps blocking production. 74% of organisations regret their AI vendors. The rush to adopt artificial intelligence is creating massive blindspots. Daren Tan of ALPHV Technologies joins Tech Talk to unpack the expensive realities of enterprise AI deployment and how to stop "Shadow AI" in its tracks.

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The Shadow AI Threat: Employees using free-tier consumer AI tools pose a massive cybersecurity risk, requiring strict endpoint management and enterprise legal contracts to prevent proprietary data leaks.
Escaping Pilot Purgatory: Enterprise AI projects often fail to scale because leaders chase consumer-level "magic" without engineering for compliance, traceability, and localised hardware costs.
Traceability & Explainability: Organisations must build step-by-step reporting tools to justify AI decisions (such as rejecting a bank loan) to ensure accountability when system errors occur.
The "Human in the Loop" Safeguard: To manage unpredictable edge cases, companies must deploy fail-safes and manual override triggers that pause autonomous workflows when model performance degrades.
Agentic AI & Open Claw: The next frontier of enterprise automation involves autonomous AI agents executing complex device-level tasks, driving a surge in localised processing hardware like Mac Studios to avoid staggering cloud token costs.

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