From scattered experiments to one focused build.

The firm had recently rolled out LLM subscriptions across the entire business, but it had not yet defined an AI strategy. A handful of disconnected experiments were underway, none of which had turned into real operational value. Across 200+ properties, daily work was full of manual, repetitive tasks, yet no one could say with confidence which of them AI could meaningfully improve.

The question of where to focus was spread across functions, which made it hard to separate high-return opportunities from noise. The real risk was pouring time into AI that looked impressive but moved nothing.

Skylite ran a fixed-scope AI Diagnostic to map the business, pressure-test every opportunity, and hand leadership a ranked plan they could act on.

The result was a clear sequence for putting AI to work, and agreement on the single highest-impact place to start.

The diagnostic gave leadership a shared, defensible view of where to begin their AI journey. They aligned on one flagship to build first: an AI “first reviewer” for compliance files, a workflow where a person currently checks nearly 100 certification files by hand each week and roughly three in four come back with required edits. Automating that first pass removes hours of rework and reduces the risk tied up in hundreds of incomplete files.

More than a list of ideas, the engagement produced a phased plan the firm could commit to. Rather than spreading effort across 55 experiments, leadership gained the focus to invest in the few that would compound, starting with a tool already moving to production.