Overcoming Data Quality Hurdles in AI Adoption

8.6% of organizations feel fully data-ready for AI. The other 91.4% are evaluating LLMs anyway.

52% say data quality is their biggest barrier. And yet most AI roadmaps start with model selection. There's a team out there right now on month four of an LLM evaluation while the data pipeline that feeds it breaks every time someone updates a shared spreadsheet.

The average enterprise runs 12+ siloed systems. The data that made the pilot look good was hand-curated. Production needs governance, lineage, ownership rules, and quality standards that nobody has built.

MIT Sloan put it well: most AI failures are data failures in disguise.

If you're three months into comparing LLMs and you haven't assessed whether your data can support any of them in production, you might be solving the fun problem instead of the important one.

#dataquality #AIadoption #LLMevaluation #datagovernance #AIfailures