Businesses losing an average of $493k from data integrity flaws
Managing data responsibly and effectively for the AI age can give organisations a strong competitive advantage, but many are failing to harness this successfully, despite AI-readiness being a key strategic priority.
New research from global information management leader Iron Mountain (NYSE: IRM) and FT Longitude examines how 500 large organisations are leveraging their information and datasets to be ‘AI-ready’ and identifies a group of leaders with a blueprint for building AI-ready information management capabilities.
The good data dividend
A total of 84% of Australian respondents reported revenue and profitability growth over the past 12 months as a direct result of their organisation’s information management practices, including data collection, storage and analytics capabilities.
This ‘good data dividend’ equated to a total global revenue gain of A$115 trillion, or average revenue growth of A$3.4 billion per organisation.
Data integrity is critical to being AI-ready
Iron Mountain’s research also found that, on average, an organisation had lost approximately A$493,000 over the past 12 months because of data integrity flaws, equating to a A$22 billion loss globally.
Half (50%) of Australian organisations say improving data insight extraction will be key to achieving their strategic ambitions over the next 12 months – making it the most cited focus area in the country. This is 37% higher than the global average, and surpasses countries such as the United Kingdom (U.K.) (44%) and the United States (U.S.) (39%).
Over a third of respondents (36%) identified AI-ready data as the information management focus area that will have the greatest impact on achieving their organisation’s strategic ambitions over the next 12 months.
Almost half of surveyed organisations in Australia identify loss of competitive advantage as the main consequence of data integrity flaws (48%). This is significantly higher than the global average of 29% and the highest among markets surveyed.
However, workforce AI literacy remains an important concern, with 42% citing this as one of the top challenges set to impact their AI readiness over the next one to three years. Significantly higher than the global average of 28%.
Nearly all (92%) Australian organisations say their AI readiness strategies have benefited their companies to date – 14 percentage points above the global average. However, while 34% of Australian organisations consider their AI readiness activities to be a crucial part of their competitive advantage, 58% say that, while their AI initiatives provide occasional benefits, they lack consistency.
Narasimha Goli, Chief Technology Officer, Iron Mountain, said:
“With the rise of open-source and specialised AI models, data integrity, transparency and trust are more critical than ever. At Iron Mountain, we are investing in solutions such as our Iron Mountain InSight® Digital Experience Platform (DXP) to help our customers get their information ready for use in generative AI and other AI-powered applications. This enables organisations to illuminate dark, unstructured data by automating the processes for extracting and organising meta data at speed and scale, and with a high degree of accuracy.
“By leveraging technology like this to ensure their data is being sourced responsibly, organisations can harness the full potential of their information to drive intelligent decision-making and unlock new growth opportunities.”
Lessons from the leaders: an AI-ready data blueprint
Iron Mountain’s research showed that over the last 12 months, the organisations surveyed achieved an average of A$3.4 billion in revenue growth as a direct result of enhancements from new information management systems and strategies.
A small group of global leaders who are experiencing the most revenue and profitability increases have more data integrity and accuracy provisions in their workflows to ensure the data used in AI outputs are sourced responsibly:
100% have processes for eliminating redundant, obsolete or trivial (ROT) data and for automating data extraction.96% are using AI dashboards to explain outcomes and data lineage to non-technical stakeholders.
These leading organisations are 16% more likely to have adopted AI nutrition labels to verify data quality, and 55% of them are looking to AI technologies themselves to improve their unstructured data sources so they are more AI-ready.
Mithu Bhargava, Executive Vice President and General Manager, Digital Solutions, Iron Mountain, said:
“Smart information management is key to capitalising on the growing AI opportunity, and Iron Mountain’s research shows that a commitment to responsibly sourcing the data for AI models is a hallmark of leading organisations. With AI fast becoming a necessity, this data quality-first mindset is now essential for every organisation.”
