•    Technical Due Diligence Imperative: Why critical infrastructure operators need specialized IT engineers to evaluate AI solution architectures, data handling practices, and algorithm transparency before deployment in sensitive operational contexts
•    Validating AI Claims vs. Reality: Establishing internal expertise to distinguish between genuine machine learning capabilities and conventional software solutions rebranded as "AI" to command premium pricing in the energy sector
•    Total Cost of Oversight: Balancing the promised automation benefits against the hidden expenses of maintaining specialized talent needed to monitor, validate, and troubleshoot third-party AI systems throughout their lifecycle
•    Vendor Partnership Evolution: Creating collaborative frameworks where suppliers provide appropriate levels of algorithmic transparency while energy companies develop the technical acumen to meaningfully evaluate AI performance against operational requirements