Posts Tagged ‘Data governance’
Washington Is Watching AI
Washington’s focus on artificial intelligence (AI) includes competing priorities: accelerating innovation, protecting communities, strengthening national security and preparing workers. The White House’s March 2026 legislative framework asks Congress to address these issues through a national approach. Recommendations, however, are not enacted legislation. Washington still has to turn its intentions into requirements. The Economist brought this…
Read MoreExplainable AI: Building Trust Through Understanding
Trust becomes difficult when artificial intelligence (AI) delivers answers without showing why. Employees may question recommendations, customers may challenge decisions and leaders may struggle to defend outcomes. Explainable AI helps address that uncertainty by making the factors influencing a result easier to understand. MeriTalk brought this interesting and important topic to us in their article,…
Read MoreFollow the Data: Why Data Lineage Matters for Governance and AI
Artificial intelligence (AI) is only as reliable as the data behind it. When an AI system produces an inaccurate, biased or simply baffling result, one of the first questions should be: Where did the data come from? Data lineage helps answer that question. Data lineage is the documented journey of data throughout its lifecycle. It…
Read MoreAI Is Only as Good as the Data Behind It
Everyone wants to talk about what AI can do. Fewer people want to talk about where it gets its data, who maintains that data or whether anyone can find the latest version of it. Fair enough. Data management is not the flashy part. It is, however, the part that keeps the flashy part from confidently…
Read MoreSemantic Search Is Only as Smart as Its Governance
Semantic search promised more than traditional keyword search: an understanding of meaning, context and intent. Instead of matching exact words, it can connect a question with relevant information even when the language differs. But that intelligence depends on more than a fancy new model. It depends on well-governed data. MarTech brought this topic to our…
Read MoreIt’s Probably Your Data
When an artificial intelligence (AI) initiative underperforms, the model is often the first thing blamed. Maybe the algorithm isn’t sophisticated enough. Maybe the platform is wrong. Maybe the organization needs a newer, more powerful model. This interesting and important topic came to us from CIO in their article, “Your AI model isn’t the problem. Your…
Read MoreWho Is Governing Whom? Data Governance in the Age of AI
For years, data governance has been about control: organizations establish policies for how data is collected, stored, accessed, shared, protected and eventually retired. People create the rules, technology follows them, and governance provides the guardrails. Artificial intelligence (AI) complicates that relationship. As AI systems become embedded in search, analytics, content creation, decision support and everyday…
Read MoreWhy AI Makes a Data Strategy More Important Than Ever
Artificial intelligence (AI) may be changing what organizations can do with data, but it hasn’t changed one fundamental truth: AI is only as effective as the data behind it. That makes a strong data strategy more important than ever. This interesting topic came to us from Dataversity in their article, “Your Data Strategy Isn’t Ready…
Read MoreFrom Information to Action: Turning Data into Better Decisions
Organizations today have access to more data than ever before. Customer behavior, operational performance, financial trends, market activity and employee insights can all be measured and analyzed. But having data and making good decisions with it are two very different things. This interesting topic came to us from IDB in their article, “How Can Governments…
Read MoreAI Agents Need Data Governance and Data Governance Needs to Keep Up
Artificial intelligence (AI) agents are changing how organizations interact with data. Unlike traditional AI tools that primarily analyze information or generate responses, agents can take action: retrieving data, making decisions, initiating workflows and interacting with other systems with limited human intervention. This topic came to us from CIO in their article, “Why AI agents will…
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