Remove Business Objectives Remove Data Strategy Remove Measurement
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The AI-Driven Enterprise: Aligning Data Strategy with Business Goals

DataFloq

As companies prepare to meet this demand with a structured approach towards data modernization , their success relies on a foundational alignment between data strategies, AI adoption initiatives, and the overarching goals and objectives of the business. How to Create a Data Strategy Aligned With Business Goals?

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Bridging the AI Execution Gap: Why Strong Data Foundations Make or Break Enterprise AI

Jen Stirrup

." Understanding the AI Execution Gap The AI execution gap manifests when organizations invest significant resources in AI technologies and talent but fail to achieve scaled, production-ready AI solutions that deliver measurable business value. Looking to assess your organization's data foundation and AI readiness?

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5 tips for better business value from gen AI

CIO Business Intelligence

Specify metrics that align with key business objectives Every department has operating metrics that are key to increasing revenue, improving customer satisfaction, and delivering other strategic objectives. In HR, measure time-to-hire and candidate quality to ensure AI-driven recruitment aligns with business goals.

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CDOs: Your AI is smart, but your ESG is dumb. Here’s how to fix it

CIO Business Intelligence

Similarly, Deloittes 2024 CxO Survey highlights that while CDOs prioritize AI and business efficiency, sustainability remains a secondary focus. However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive.

IT
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Excel Hell: 7 Signs Your Business Needs Data Automation (and How to Escape)

Jen Stirrup

Manual processes amplify the risk, and this figure reflects the vast scope of operational inefficiency, lost productivity, and poor decision-making resulting from inaccurate, incomplete, or inconsistent data. Furthermore, your business introduces risk and creates bottlenecks with a system that is not easily maintained.

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Small language models (SLMs): a Smarter Way to Get Started with Generative AI

DataFloq

The truth is, most businesses don’t need boundless AI creativity; they need focused, reliable, and cost-efficient automation. They deliver quick wins – faster deployment, tighter data control, and measurable return on investment (ROI) – without the complexity or risk of oversized AI. Evaluate data readiness.

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How to Develop an AI Strategy

DataFloq

We examined the client’s data quality, infrastructure maturity, budget, and regulatory limitations to help the client gain a clear understanding of what was realistically achievable. That is to say, a solid AI strategy doesn’t follow the hype. Trying to develop an AI strategy to see tangible results?