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10 AI strategy questions every CIO must answer

CIO Business Intelligence

To counter such statistics, CIOs say they and their C-suite colleagues are devising more thoughtful strategies. Here are 10 questions CIOs, researchers, and advisers say are worth asking and answering about your organizations AI strategies. How does our AI strategy support our business objectives, and how do we measure its value?

Strategy 141
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It’s 2025. Are your data strategies strong enough to de-risk AI adoption?

CIO Business Intelligence

Primary among these is the need to ensure the data that will power their AI strategies is fit for purpose. In fact, a data framework is critical first step for AI success. There is, however, another barrier standing in the way of their ambitions: data readiness. AI thrives on clean, contextualised, and accessible data.

Risk 111
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Why Your Data Governance Strategy is Failing

TDAN

What is Data Governance and How Do You Measure Success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? But what […].

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Secrets to Data Strategy Success from Data Champions Online Europe

Corinium

Three key themes emerged as 17 of Europe’s top data leaders shared the secrets of their success with more than 250 attendees at this insight-packed five-day event.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.

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Data Governance as an Emergency Service

erwin

Data governance (DG) as a an “emergency service” may be one critical lesson learned coming out of the COVID-19 crisis. Where crisis leads to vulnerability, data governance as an emergency service enables organization management to direct or redirect efforts to ensure activities continue and risks are mitigated.

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The future of data: A 5-pillar approach to modern data management

CIO Business Intelligence

The proposed model illustrates the data management practice through five functional pillars: Data platform; data engineering; analytics and reporting; data science and AI; and data governance. The choice of vendors should align with the broader cloud or on-premises strategy.