The Data Quality Crisis No One Talks About

We are surrounded by the biggest Data and AI leaders at Gartner. Yet one question keeps coming up. Why are so many AI initiatives still failing? I asked Rich Hoyland, President, Global Field Operations, Anomalo to answer that directly on The Ravit Show at Gartner Orlando.

His take was simple.

AI does not fail because of ambition.

It fails because of bad data.

We spoke about:

-- Why agentic AI raises the stakes for data quality

-- Why speed without trust is a risk for executives

-- What data quality failure actually looks like inside large enterprises

-- Why traditional rule-based approaches are not enough anymore

-- And where Anomalo sees the future of data management going

One part of the conversation stood out. When AI moves from insight to action, data quality stops being a reporting issue. It becomes a business risk issue.

Old approaches were built for dashboards. Now we are feeding data into agents that make decisions. That changes everything. Rich also shared how their long term vision goes beyond just catching bad data to providing enterprises with an agentic “self-driving data” system. It is about building continuous trust in data across the enterprise from ingestion to decision so AI agents can operate and scale safely.

If you care about AI that actually works in production, this is one to watch.

#data #ai #anomalo #dataquality #theravitshow