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Accelerating AI at scale without sacrificing security

CIO

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. 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.

Security 498
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What’s holding back CIO’s AI strategies? Their own AI learning curve for one

CIO

Salesforce CIO Juan Perez encourages CIOs to learn from their peers. “AI But it’s important to understand that AI is an extremely broad field and to expect non-experts to be able to assist in machine learning, computer vision, and ethical considerations simultaneously is just ridiculous.”

Learning 497
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Singapore unveils AI system guidelines, emphasizing secure-by-design

CIO

Singapore has rolled out new cybersecurity measures to safeguard AI systems against traditional threats like supply chain attacks and emerging risks such as adversarial machine learning, including data poisoning and evasion attacks.

Security 446
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Revolutionizing data management: Trends driving security, scalability, and governance in 2025

CIO

As enterprises scale their digital transformation journeys, they face the dual challenge of managing vast, complex datasets while maintaining agility and security. With machine learning, these processes can be refined over time and anomalies can be predicted before they arise. This reduces manual errors and accelerates insights.

Security 424
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Navigating the complexities of security and compliance on the mainframe

CIO

As organizations look to modernize IT systems, including the mainframe, there’s a critical need to do so without sacrificing security or falling out of compliance. With the stakes so high, IT leaders need to ensure their modernization strategies are inclusive of mainframe security. PCI DSS v4.0).

Security 391
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Leveraging AMPs for machine learning

CIO

As a result, many companies are now more exposed to security vulnerabilities, legal risks, and potential downstream costs. Data scientists and AI engineers have so many variables to consider across the machine learning (ML) lifecycle to prevent models from degrading over time.

Learning 221
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Learn from past cloud-first mistakes for better AI

CIO

As organizations build their AI factories today in this new era, IT leaders have an opportunity to learn from their cloud-first sins of the past and strategically build in a way that prioritizes security, governance, and cost efficiencies over the long term, avoiding errors that might need to be corrected down the line.

Learning 521