David Sweenor, founder of TinyTechGuides is an international speaker, and acclaimed author with several patents. He is a specialist in AI, ML, and data science.
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This is part two in a two-part series exploring AI governance for business success. Read part one here.
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Introduction
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As artificial intelligence (AI) becomes ubiquitous, it’s reshaping decision-making in ways that go far beyond the scope of traditional business automation. Using a combination of predictive and generative AI, systems can now make tactical, operational, and strategic decisions at scale. They dynamically adjust product prices, recommend your next binge-worthy TV show, and generate sales and marketing content for mass diverse audiences. Yet scaling such AI use cases requires governance frameworks that do more than just manage data—effective AI governance frameworks encompass systems that continuously learn, adapt, and operate with minimal human intervention.
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The debate over the role of AI governance in business success is not just about compliance or ethical concerns—it's a question of whether companies can realize the financial potential that AI promises to unlock. As AI moves from concepts and proofs-of-concept (POCs) to a core component of business operations, the real question for business leaders is not if AI governance matters, but how it directly influences their bottom line.
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Sometime around 2005, self-service business intelligence (BI) applications like Tableau and Qlik rose in prominence, displacing IT-centric solutions like Congos and Oracle Business Intelligence Enterprise Edition (OBIEE). In switching to these BI tools, we were promised actionable insights and real-time visibility for our business operations.
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This blog examines Gartner’s report “Quick Answer: What Makes Data AI-Ready?” and argues that ensuring data readiness upfront is the single most important factor for AI success. By aligning data with use cases, qualifying it to meet AI requirements, and implementing governance that accounts for AI’s unique challenges, organizations can not only avoid costly failures but also accelerate their competitive advantage. Business leaders must act now or risk being left behind.
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Note: This blog was created from a presentation delivered at Snowflake Summit 2024 and it’s representative of Alkermes’ experience implementing the Alation Data Intelligence solution.
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Key Insights
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It’s been a crazy two weeks! We’re just getting back from another whirlwind week at the Moscone Center in San Francisco. The Databricks Data & AI Summit 2024 was another smashing success, with core focuses on AI for innovation in data – and ample reminders that you can’t be successful in AI without a solid data foundation. The Alation team was there in full force, sharing our latest updates, from compelling customer stories to product innovations designed to make our joint customers more successful. Let’s dive in!