The State of Data Infrastructure 2024 by Hitachi Vantara revealed worries of data loss as AI adoption strains their infrastructure.
Data storage infrastructure Hitachi Vantara new survey, State of Data Infrastructure 2024 Report, found that 36% of participants recognise the importance of data quality for AI success, but the focus remains on data security, leaving gaps in AI performance.
Nearly half (48%) of respondents cite data security as their top concern for AI implementation, reflecting the critical need to guard against internal and external threats. Plus, 84% of respondents admitted that losing data to an attack or mistake would be catastrophic.
However, the study results showed that ignoring data quality comes at a cost for BFSI institutions. For example:
- BFSI AI models are accurate only 21% of the time
- 36% say a data breach caused by AI making a mistake is a top three concern
- 32% are concerned an AI-enabled attack could cause a data breach
- 38% are concerned about inability to recover data from ransomware
“Financial institutions worldwide are accelerating AI adoption, but many are realising their data infrastructure isn’t ready to support it,” said Joe Ong, Vice President and General Manager for ASEAN at Hitachi Vantara.
“This global research reflects what we’re also hearing in Southeast Asia — that the real barrier to AI success isn’t the technology itself, but the ability to manage data securely, accurately, and at scale. Financial organisations must focus on strengthening their data foundations to ensure AI delivers real, sustainable impact.”
“We’re on a mission to help customers from all industries harness the power of AI regardless of the market they’re in,” said Jason Hardy, chief technology officer for artificial intelligence at Hitachi Vantara.
“The business model in financial services is inherently tied to trust. Reputational harm is a significant risk, and so in our industry, the interaction between security and accuracy is a critical and complex challenge” said Mark Katz, CTO of Financial Services, Hitachi Vantara.
“For instance, if a chatbot inadvertently discloses sensitive information that was included in the training data, that will have serious repercussions. Additionally, the cost of a wrong answer or a hallucination poses a significant risk; if someone were to act on bad data, it raises all sorts of questions about liability.”
Despite accuracy challenges, AI adoption within BFSI is accelerating. However, many are deploying AI without adequate preparation, with 71% of respondents admitting to testing and iterating on live implementations, while only 4% are using controlled sandbox environments.
Read the full report here.
