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The Missing Ingredient in the Race to AI
The race to artificial intelligence (AI) is often framed as a competition for faster models, bigger computing environments and more sophisticated algorithms. Organizations invest in machine learning platforms, large language models (LLMs) and automation tools, hoping to gain some advantage. Yet, one critical factor is often overlooked: data accountability. AI systems are only as trustworthy…
Read MoreSemantic Search and the Preservation of Scholarly Intent
For decades, academic publishing has focused on creating authoritative, peer-reviewed content designed to advance knowledge. Yet, as discovery increasingly depends on artificial intelligence (AI) and semantic search systems, a new challenge has emerged: ensuring that scholarly intent survives machine interpretation. Semantic search differs from traditional keyword search by attempting to understand meaning rather than simply…
Read MoreThe More Technology Changes, the More Findability Matters
Over the past decade, emerging technologies have transformed nearly every aspect of how we create, manage and access information. Artificial intelligence (AI), machine learning, cloud computing, automation and natural language processing have shifted from futuristic concepts to everyday business tools. Entire industries have been rebuilt around predictive analytics, generative AI and massive-scale data processing. Information…
Read MoreData Governance and Change Management: The Twin Engines of a Data-Driven Organization
Every organization wants to be data driven until it realizes that becoming data driven is not actually a technology project. It is a people project supported by technology. Dashboards, analytics platforms and artificial intelligence (AI) tools may grab the attention, but none of them create meaningful change without two critical components working together: data governance…
Read MoreData 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 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 MoreAccess Innovations, Inc. to Exhibit at SSP’s 48th Annual Meeting
Access Innovations, Inc. is proud to support the Society for Scholarly Publishing’s (SSP) 48th Annual Meeting, taking place May 27–29, 2026, at the Gaylord Pacific Resort & Convention Center in Chula Vista, California. As one of the premier gatherings for the scholarly communications community, the SSP Annual Meeting brings together publishers, librarians, researchers, technologists and…
Read MoreGarbage In, Genius Out? Not Without Data Governance
Generative artificial intelligence (GenAI) is having a moment. It writes, summarizes, predicts, designs and occasionally makes you question your own job security before your coffee kicks in. But beneath all the flash and promise is something far less glamorous and far more important: data governance. Because no matter how sophisticated your AI tools are, they…
Read MoreAccessInn.ai Launches: API-Driven Ontological Services for Multi-Disciplinary Large Language Model Development
Access Innovations, Inc. is proud to announce the launch of AccessInn.ai, a next–generation platform providing API–accessible ontological services designed to empower developers, data scientists, and AI architects in building, managing, and scaling language model programs across public, private, and enterprise environments. Using agnostic, fungible APIs, the ontologies tag content at the level of content submitted, from full documents…
Read MoreBig Data and AI: A Partnership with Power and Pressure
Big data and artificial intelligence (AI) are often discussed together because each strengthens the other in ways that drive real value. Big data provides the volume, variety and velocity of information that AI systems need to learn, adapt and improve. AI, in turn, turns that raw data into something useful by identifying patterns, making predictions…
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