Accelerating AI at scale without sacrificing security

How does a business stand out in a competitive market with AI? For some, it might be implementing a custom chatbot, or personalized recommendations built on advanced analytics and pushed out through a mobile app to customers. For others, it may simply be a matter of integrating AI into internal operations to improve decision-making and bolster security with stronger fraud detection.

The transformative power of AI is already evident in the way it drives significant operational efficiencies, particularly when combined with technologies like robotic process automation (RPA). By eliminating time-consuming tasks such as data entry, document processing, and report generation, AI allows teams to focus on higher-value, strategic initiatives that fuel innovation.

Unfortunately, implementing AI at scale is not without significant risks; whether it’s breaking down entrenched data siloes or ensuring data usage complies with evolving regulatory requirements. As AI adoption accelerates, it demands increasingly vast amounts of data, leading to more users accessing, transferring, and managing it across diverse environments. Each interaction amplifies the potential for errors, breaches, or misuse, underscoring the critical need for a strong governance framework to mitigate these risks. Above all, robust governance is essential.

Failing to invest in data governance and security practices risks not only regulatory lapses and internal governance violations, but also bad outputs from AI that can stunt growth, lead to biased outcomes and inaccurate insights, and waste an organization’s resources.

Keeping Data Governance at the Core of Effective AI

Data falling into the wrong hands should be a concern of any business—regardless of size or status in the market. Examples include the  2008 breach of Société Générale, one of France’s largest banks, when an employee bypassed internal controls to make unauthorized trades, leading to billions of dollars lost. Similarly, in 2017 Equifax suffered a data breach that exposed the personal data of nearly 150 million people. This type of data mismanagement not only results in financial loss but can damage a brand’s reputation.

Data breaches are not the only concern. An evolving regulatory landscape presents significant challenges for enterprises, requiring them to stay ahead of complex, shifting requirements while managing compliance across jurisdictions. Organizations must navigate frameworks like the EU’s General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and sector-specific mandates such as the Health Insurance Portability and Accountability Act (HIPAA).

With the rise of AI and data-driven decision-making, new regulations like the EU Artificial Intelligence Act and potential federal AI legislation in the U.S. are creating additional layers of accountability. To meet current and future requirements, enterprises must implement robust compliance frameworks that include real-time monitoring and proactive reporting mechanisms

And business leaders know the risk of ineffective data governance strategies. According to a Cloudera survey, 72% of business leaders agree that data governance is an enabler of business value, underscoring the critical link between secure data and impactful AI.

The analytics that drive AI and machine learning can quickly become compliance liabilities if security, governance, metadata management, and automation aren’t applied cohesively across every stage of the data lifecycle and across all environments. Ensuring these elements are at the forefront of your data strategy is essential to harnessing AI’s power responsibly and sustainably.

As AI usage spreads, data frequently moves between different infrastructures, making it harder to keep track of and protect. Solutions like Cloudera’s platform address a variety of constraints—organizational, regulatory, or otherwise—through a federated service that consistently secures, governs, and tracks data across hybrid cloud environments. The platform also offers a deeply integrated set of security and governance technologies, ensuring comprehensive data management and reducing risk.

As AI adoption expands across entire enterprises, organizations must implement strong defensive measures and continuously monitor for potential threats as AI is integrated into various environments.

Learn more about how Cloudera can help your organization ensure data governance and security are equipped to keep pace with accelerating AI adoption.