Responsibly Sourced Data: AI’s Crucial Ingredient

Well-managed data gives organizations a strong competitive advantage. Organizations that have superior data collection, storage and analytics capabilities are benefiting from increased revenues and profitability, with use cases ranging from enhanced productivity to new forms of customer experiences and business value propositions.

Now, there is even more potential to get ahead by using artificial intelligence (AI) to drive smarter, faster decision-making. But to avoid problems such as hallucinations, bias and ethical missteps, AI solutions need to be fed with data that is of high quality and responsibly sourced. With the rise of open-source and specialized AI models, data integrity and transparency are more critical than ever.

New research from Iron Mountain, in partnership with FT Longitude, uncovers the extent to which organizations have developed information management systems and datasets that are fit for the AI age. Based on a survey of senior leaders at 500 large organizations worldwide (those with more than 1,000 employees), it identifies the performance gaps in organizations’ data ecosystems and practices. And it identifies a group of leaders that are providing a blueprint for building AI-ready information management capabilities.