A common topic currently is how to confidently implement AI while maintaining solid data GRC (Governance, Risk, and Compliance). After two decades of navigating data GRC requirements, it’s clear that AI introduces new challenges to traditional and proven ways of handling them.
Adding AI to our data ecosystem also presents challenges to data privacy, access, monitoring, and integrity. Our existing governance framework has to evolve to include our AI ecosystem to ensure transparency and accountability.
With traditional data we can put reliable access controls on data sources. However, once we allow that data to be consumed by our AI ecosystem, access control becomes very hard to maintain or monitor. As a result, traditional controls have to adapt to the way AI processes and uses data. Depending on the AI vendors we’re using, or how we’re developing AI solutions in-house, we may have no visibility or control over how our data is being managed.
We can overcome these challenges by extending our existing data GRC and adapting it to add new AI-specific requirements. The benefits of overcoming these challenges is absolutely worth it. Once we have established data GRC across our new AI ecosystem, we can take advantage of powerful new capabilities such as:
Improved Risk Management: By analyzing large volumes of data in real-time, we can discover patterns and anomalies that humans might miss, enhancing the effectiveness of risk management strategies.
Predictive Analytics: AI-powered predictive analytics can forecast potential risks and compliance issues based on historical data and current trends.
Fraud Detection and Prevention: We can use AI to detect suspicious activities and potential fraud patterns faster and more comprehensively than with traditional methods.
Enhanced Audit Capabilities: Auditors can use AI to analyze vast amounts of data and identify discrepancies or irregularities quickly.
As we adopt AI into our data GRC, we expand our capability to automate data governance while maintaining data integrity and compliance.
What challenges are you facing with AI adoption and its impact on your data GRC?
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