“To create transformative AI solutions, we need a holistic, synergistic, and simultaneously integrated flow of information,” explains Earley, who has helped companies across industries to manage data to enable digital transformations. The problem is that, all too often, this foundational principle is ignored, given short shrift, or deprived of resources.
The answer, Earley says, lies in ontology – a consistent representation of data and data relationships that can inform and power AI technologies. In other words, ontology is “the master knowledge scaffolding of the organization.” Without it, any AI-driven transformation will be slow, costly, and less effective.
In language accessible to a non-tech audience, Earley draws on examples from numerous client companies to describe what correct execution of data management looks like. He addresses how to manage this transformation, step-by-step, covering such issues as:
Customer Experience – Customer experience is hard to get right and easy to get wrong. “It’s a question of the proper integration of technology,” writes Earley. He explores the roadblocks that hinder a systematic approach to customer experience, and offers a solution: a “high-fidelity journey map” that accounts for how technology represents and enables elements of the customer experience.
Marketing – Good marketing is about presenting the right content at the right time to engage the customer. Today, this means reading the online equivalent of physical body language: “the digital breadcrumbs, cues, and clues that tell us about what our customers need, how we can meet those needs, and how to best present the content most likely to engage the customer at that moment in their journey.” According to Earley, digital marketers must become knowledge enablers, champions of data quality, architects of digital systems, and keepers of the ontology that powers it all.
Ecommerce – Ecommerce is where ontology-powered AI can have its biggest impact, says the author. Its success or failure depends on the quality of data. THE AI-POWERED ENTERPRISE addresses how to enhance this quality by improving both customer classification and product taxonomies (categorizations) based on features and relationships.
Sales Process – “AI technologies can improve every part of the sales process by freeing sales staff from routine tasks and making them more efficient,” Earley writes. He discusses effective use of AI-powered chatbots in customer interaction; machine learning to train AI systems to identify sales prospects; and sematic search to recommend the most productive approaches to sales leads.
Employee Productivity – AI and efficient knowledge retrieval systems can enhance productivity across a range of tasks. The author describes how to overhaul knowledge management systems and text analytics so they can be used in making hiring decisions, training employees effectively, and providing them with access to the correct, contextualized information in their day-to-day work.
In addition to these issues, Earley explains how having the right ontology and data structures can enable AI to improve supply chain dynamics and logistics – and can even have powerful impact on strategy and governance issues. Moreover, he outlines the basic principles that should guide leaders who are undertaking digital transformations of their organizations.
“The winners and losers of the next fifteen years will be determined by who best harnesses AI for solving business problems for employees and customers,” Earley contends. Combining a sophisticated explanation of how AI works with a practical approach to applying it to a range of business problems, THE AI-POWERED ENTERPRISE is a must-read for CEOs, CMOs and technology executives – along with anyone who wants to understand the role of AI and how to get a jump on the opportunities it presents.
SETH EARLEY is CEO of Earley Information Science (EIS), a leading consulting firm focused on organizing information for business impact, with expertise in knowledge strategy, data and information architecture, search-based applications, and information findability solutions. He is currently on the editorial board of the Journal of Applied Marketing Analytics and is a former Data Analytics department editor for IEEE’s IT Professional magazine. He lives in Carlisle, Massachusetts.