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Seth Earley CEO at Earley Information Science, Artificial Intelligence Speaker, Writer and Influencer

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  • Harvard Business Review: Is Your Data Infrastructure Ready for AI

    Creating an ontology is an essential investment to prepare your enterprise to realize the benefits of AI and machine learning. Gone are the days when businesses should simply allow a number of small AI projects to blossom independently: for these projects to be competitive they need to draw on data from across the company, data stored in many different forms in many different systems. Businesses will be best positioned to build ontologies if they identify and research pain points first–areas where the data connections are most needed–before beginning to set the organizing principles for the ontology itself.

  • The Coming Tsunami of Need — Knowledge Management for Artificial Intelligence

    Knowledge management has had a bad rap. For the past few decades, it has gone through cycles of popularity after being introduced in the early 90s, and in some of those cycles, it has been significantly devalued. That is the online incarnation of KM. Now knowledge management is experiencing something of a revival, as its value in enabling AI is being increasingly recognized.

  • Moving Personalization to the Next Level: Three data driven approaches for personalization, contextualization and recommendation.

    Personalization comes in multiple shapes and forms, many of which businesses can put to effective use. But they shouldn't make the mistake of launching all of them at once. An incremental approach works well here. And a good place to start is product hierarchies.

  • Leveraging Data to Improve the Customer Experience

    When you consider how customers interact with organizations these days, it quickly becomes apparent that much of that interaction is through digital channels. “CX” suggests a customer experience via laptops or mobile devices, and that digital experience is driven entirely by data. The question is, how do we make it the most relevant and seamless experience possible, given the needs and objectives of the user, and what data can we leverage to do so?

  • 5 core principles for successful AI/human partnerships

    AI works best when humans are in the loop. Knowledge communities can provide a robust flow of information that supports and continuously refreshes the content on which AI relies. When organizational processes are identified and documented, AI can take over routine tasks, leaving the creative and more challenging problem-solving tasks to be handled by humans. Behind the scenes, content and product models need to be developed and aligned with data capture processes to make AI components work, but humans must create the knowledge flow and take charge of the content.

  • There's No AI Without IA

    Artificial intelligence (AI) is increasingly hyped by vendors of all shapes and sizes—from well-funded startups to the well-known software brands. Financial organizations are building AI-driven investment advisors. Chat bots provide everything from customer service to sales assistance. Although AI is receiving a lot of visibility, the fact that these technologies all require some element of knowledge engineering, information architecture, and high-quality data sources is not well known...

  • “Just Make it Work” – Dealing with Executive Disengagement During Large Scale Digital Transformations

    Executives cannot make informed decisions without getting into the weeds about not just the nature and severity of the challenges but the business decisions that need to be made as part of any technology effort. The most important program parameters include expected outcomes, proof points to support the investment, a realistic plan, ongoing measures of success, and long-term program ownership and governance.

  • Verizon's Digital CX Transformation: 6 Fails (and Fixes) for One Customer

  • How Companies Are Benefiting from “Lite” Artificial Intelligence

    AI applications range from the very complex and expensive (like self-driving cars) to more modest “AI lite” initiatives. In this article Seth lays out a path to AI that companies can undertake right now.