Posts by Melody Smith
Data and AI Governance: Why They Must Work Together
Artificial intelligence (AI) may be the shiny new engine driving innovation, but data remains the fuel. And like any high-powered machine, the quality of the fuel matters. Organizations rushing to adopt AI are quickly discovering that AI governance and data governance are not separate conversations. They are deeply interconnected disciplines that must work together to…
Read MoreGenerative AI: Exciting, Impressive and Occasionally a Little Chaotic
Generative AI (GenAI) has quickly become one of the most talked-about technologies in business, and honestly, it is easy to see why. It can write content, summarize information, help develop software, automate repetitive tasks and uncover insights in seconds that might have taken humans hours or days. Whether you love it, fear it or are…
Read MoreMapping the Lifeblood of Business
Data moves through modern businesses like electricity through a city grid. It powers customer service, finance, analytics and now increasingly, artificial intelligence (AI). But many organizations still do not fully understand where their data originates, where it travels, who touches it or how it changes along the way. In the age of AI, that lack…
Read MoreWhen Technology Gets a Little… Personal
There was a time when innovation meant faster computers, smaller phones and maybe a refrigerator that might judge you for buying off-brand yogurt. But now? Technology has entered its bold era. This interesting and somewhat humorous information came to us from Futurist Speaker in their article, “Twelve Inventions That Prove the Future Has a Sense…
Read MoreDecentralizing Data for a Smarter, More Secure Network
The Internet of Things (IoT) has rapidly expanded, connecting everything from smart thermostats to industrial sensors. But as the number of devices grows, so does the complexity of managing the data they generate. Traditionally, IoT systems rely on centralized platforms to collect, process and store this data. While effective, this model introduces challenges around scalability,…
Read MoreOntology: The Invisible Architecture Powering Findability in the Age of AI
In information science, ontology is one of those terms that sounds intimidating but quietly does some of the most important work behind the scenes. At its core, an ontology is a structured framework that defines the relationships between concepts within a domain. It goes beyond simple lists of terms or categories by mapping how ideas…
Read MoreRecords Retention in the Age of AI: Why Taxonomy Still Reigns Supreme
In a world increasingly shaped by artificial intelligence (AI), records retention has moved from back-office obligation to strategic necessity. AI systems thrive on data, but not just any data—relevant, accurate, well-structured data. Without intentional retention policies, organizations risk feeding their AI outdated, redundant or even harmful information, leading to flawed outputs and questionable decisions. This…
Read MoreAI and the Future of Leadership Succession
As artificial intelligence (AI) continues to impact many facets of the business world, it is also reshaping corporate leadership succession. Traditionally, succession planning relied on executive judgment, performance reviews and long-term observation. AI introduces a more data-driven approach, analyzing employee performance, behavioral patterns and leadership potential at scale. This allows organizations to identify high-potential candidates…
Read MoreAI and Data Engineering
The rise of artificial intelligence (AI) has fundamentally reshaped data engineering, turning what was once a largely pipeline-focused discipline into a dynamic, intelligence-driven ecosystem. On the upside, it has accelerated everything. Data ingestion is faster with automated schema detection. Data quality tools now flag anomalies in real time. Pipeline orchestration has become smarter, predicting failures…
Read MoreWhen AI Becomes the Researcher: Breakthrough or Boundary?
Artificial intelligence (AI) has long been a powerful assistant to human discovery, helping researchers analyze data, identify patterns and accelerate innovation. But a new frontier is emerging. AI systems can design and conduct their own research. For some, this signals a leap forward in scientific progress. For others, it raises deeply unsettling questions. The University…
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