AI collecting at scale without human expertise produces datasets full of errors that no model can fix downstream. Download the whitepaper to find out if your harvesting model is built to win
Every business that runs on data faces the same challenge. The data that powers competitive advantage cannot be bought off a shelf. It must be harvested - with precision, at scale, and at speed. In 2026, most organisations are using AI to do that harvesting. Most of them are getting it wrong.
The IBM Institute for Business Value found that only 16% of AI initiatives have successfully scaled across the enterprise.1 S&P Global Market Intelligence reports that 42% of companies abandoned most of their AI initiatives in 2025 - up from just 17% the year before.2 The data quality crisis is not a technology problem. It is a harvesting problem. And no amount of additional automation solves it.
