Exploit the stack you already know. If talent is scarce, the stack is a force multiplier. Gartner projects that by 2028, 80% of genAI business applications will be developed on existing data management platforms, not on greenfield AI stacks. That aligns with common sense. You’ll go faster and involve more of your current staff if you bring AI to your data and systems, rather than ripping and replacing for novelty’s sake.
Use skills you already have to wire in AI. Look at where your teams are strong today (SQL, data modeling, production discipline). For example, SQL is still one of the most widely used languages among professional developers; Stack Overflow’s 2025 survey shows 61% of pros use SQL, and it’s 62% among professionals who use AI tools. That means you can anchor early AI wins in the patterns your teams already know: queries, joins, access controls, lineage, and service-level agreements—now augmented with embeddings, vector search, and retrieval.
Does this sound unglamorous compared to spinning up a bespoke model stack? Good. AI’s business value is unglamorous by nature. It’s retrieval over the right data, sensible workflows, and a feedback loop that improves outcomes. It’s the boring bits.