Earley Information Science Team

[Keynote] "There's No AI without IA" Artificial intelligence is getting lots of attention but one key aspect is often overlooked, understated or underestimated: the training of the AI through behind-the-scenes preparation of the data. Getting an AI application to actually do something useful does not happen by magic. The algorithms may be there but until the system gets a chance to learn, it will not produce the results you are hoping for. The more research you do, the more you realize that AI only works when it has the right data to spot trends, identify patterns, and provide needed functionality. No data? No AI. And it can't use just any unstructured data. The data needs to be good quality data. Yes it can be messy, but it can’t be poor quality. And depending on the application, that data will require structure and curation. In this session, we will discuss how to train your AI, the kinds of data that are needed to make it work, and why intelligent content is vital for artificial intelligence.

Intelligent Virtual Assistants, chat bots and other automated technologies will not be replacing people but will be augmenting capabilities. There’s a lot of promise to emerging technologies that are predicted to impact every aspect of business. However, breathless tech reporting, analyst prognostications and venture capital fueled vendor hype make the market noisy, confusing and risky. Emerging AI technologies are causing disruption in traditional business models while digital transformations (a hyped concept in and of itself) are upending supply chains and causing organizations to rethink how they create value. Part of this process is the increasing use of automation – from back end systems to customer facing interactions and everything in between. In this session, you will learn: A brief history of technology innovation that we now take for granted What is a digital worker and how they will augment today’s workforce How organizations must prepare for the advent of the “digital worker” The critical elements to successfully incorporating these emerging tools into your workforce. What steps do leaders needs to take to prepare and adapt?

With thousands of vendors in the marketplace, organizations are overwhelmed with choices around building their marketing technology stack. By evaluating tool choices according to a customer experience maturity model and aligning the results of that evaluation with the customer journey, organizations can make more intelligent choices around process gaps and acquire appropriate technologies to fill those gaps by relying on thoughtful analysis and fitness to purpose rather than being hijacked by slick vendor demonstrations. Using hands-on exercises, Seth Earley and Steve Walker will guide participants through the steps to understanding customer lifecycles and aligning stages with classes of technology in order to improve engagement. Attendees will leave with an approach for developing their own marketing technology blueprint.

The next step up in customer experience will come from better-trained bots that can pull data from all corners of a company, say experts at Earley Information Science roundtable. But be patient – it is still a work in progress. Support bots are in the wings, getting ready to take a star turn. Be patient, though – it may take a little while. Driven by the latest advances in artificial intelligence (AI) and machine learning, chatbots that support customers in their searches for products and services are upping their game. With stronger language skills, more sophisticated customer analytics and deeper reservoirs of company information to draw from, bots are getting better at guiding buyers on their journeys. But as good as they have become, bots are often not quite ready to take the center-stage spotlight for long stretches. They can get flummoxed by unfamiliar or complicated questions from customers. And at some companies, those reservoirs of information prove to be shallow or hard to find. More work remains to be done, and companies – and consumers – need to have realistic expectations about the current state of play, according to a panel of marketing and knowledge management experts at an Executive Roundtable hosted on Oct. 25 by Earley Information Science (EIS), a leading consulting firm focused on organizing information for business impact. The experts quickly added, however, that more and more companies are recognizing the bots’ potential and are on a hiring binge. They’re making the right move, said one of the panelists, Alla Reznik, Director of Customer Contact at Verizon’s Products and Services Group. “We probably overestimate what AI can do for us today,” she explained, “but we equally and vastly underestimate what it will do for us five years from now.” To that end, it’s important to understand that AI’s applications are a work in progress, the experts noted. That bots, like humans, not only require training, but retraining as conditions change. And that companies have to up their game, too, said Seth Earley, Founder and Chief Executive Officer of EIS. The goal is to give customers the information they need to use a product, make a selection, solve a problem and achieve their overall goal in a seamless and positive end-to-end experience. But at most large companies, the training platforms, knowledge bases and support apps have evolved in different ways, often making the journey a pretty bumpy ride, not just for the consumer, but for the bot, too. Thus “the need to harmonize data from different sources” and give the bots the tools to do their job, Earley said. The roundtable discussion, “Training AI-Driven Support Bots to Deliver the Next Generation of Customer Experience,” was led by Earley. In addition to Verizon’s Reznik, the panelists were Ian Collins, CEO of Wysdom.AI, whose product is an AI-based customer service solution for large enterprises, and Lisa Michaud, Director of Natural Language Processing at Aspect Software, a customer engagement company. One key tool in making the customer interactions more seamless is putting the burden of communication more on the bot and less on the human, through a Natural Language Interface. “Instead of having to learn how to use a computer interface,” Lisa Michaud said, “you express your needs in the language you use in talking to another human.” The easier the communication with bots, the more customers are gravitating to them, particularly at call centers. “We’re seeing the channels that customers want to communicate on change so fast,” said Ian Collins. “Now it’s Facebook and Twitter, but chatbots are coming on strong,” albeit still a “small portion.” The cognitive technology behind the bots is “enabling fast, effective personalized answers” for consumers. “People are in and out, quickly getting the solutions that they came for.” New channels are “not only an opportunity but in many cases a necessity,” said Verizon’s Reznik. “Enterprises and public-sector companies sometimes don’t realize how much demand there is for alternate methods of communicating with them.” Yet because today’s bots still have their limitations, and can get stumped by questions or a lack of information, “you always need to be able to escalate to humans,” Earley said. At least, for now. The roundtable featured a real-time survey of the webinar attendees: Nearly two-thirds said they have a major AI/chatbot customer service project in the works (25%) or are investigating options and building the case (39%), but 25% are not making significant changes in their technology About 44% said they have a rigorous formal process for managing knowledge assets or a reasonably well-structured informal one, but another 44% conceded that they are “very immature” in this area and need more capabilities A little more than a quarter of executives, or 27%, are well informed about AI and have realistic expectations, but 34% have only “pockets of understanding” and 18% think that AI and machine learning tools work by themselves As for where companies are on the hype curve, 48% see AI/bots as an extension of existing technologies, 30% said they are excited by the possibilities but not grounded in realities, 17% have drunk the Kool Aid and don’t grasp what is required and 4% are not buying in Use these links to access the roundtable and a related article. The Earley Executive Roundtable is an educational webinar series focusing on topics of interest in the areas of digital transformation and information science. Each month, EIS leads a lively discussion with a panel of industry experts. The next roundtable is scheduled for Wednesday, Dec. 6, at 1 p.m. ET, on the topic of “The Customer Data Platform – A Path to a Unified Customer Experience.” To sign up, register here.

To innovate in Ecommerce, manufacturers and distributors have to keep pushing the data-organizing envelope to improve the user experience, say experts at Earley Information Science roundtable This is not your father’s taxonomy. In the ever more complicated and competitive world of Ecommerce, it’s been a long time since you could manage all of your product information on a spreadsheet. To survive, manufacturers and distributors have become much more sophisticated in building navigation and classification hierarchies. But to thrive, they have to go beyond thinking of the resulting data architecture, or taxonomy, as just a hierarchy and instead use it to drive advanced marketing capabilities, according to a panel of marketing, distribution and knowledge management experts at an Executive Roundtable hosted on Sept. 28 by Earley Information Science (EIS), a leading consulting firm focused on organizing information for business impact. Properly designed and regularly updated, cutting-edge taxonomies can improve site search, can be essential in merchandising (by assessing your product mix and by grouping products for specific targets and solutions) and can help with personalization, the panelists said. What every online company is trying to accomplish is to help website users answer their questions and solve their problems. So the goal “is to get them to the products that they need most quickly, efficiently and effectively,” said Seth Earley, Founder and Chief Executive Officer of EIS. You have to think through your products, he added, “in a way that aligns how they are organized” with how the users will deploy them in finding their solutions. And that means, Earley said, taxonomy becomes “a set of organizing principles,” destined to have an impact on “the entire user experience and the overall customer journey” in ways that are very different from its traditional role of navigational guide. The new bottom line: “It’s foundational to product management . . . it becomes the driver of consistency of all the digital machinery that runs the organization. It becomes your common business language.” The roundtable discussion, “Beyond Taxonomy: How Manufacturers and Distributors Are Innovating in Ecommerce,” was led by Earley and included Marc Shimpeno, Taxonomist and Data Specialist at Etsy, the peer-to-peer shopping site; Megan Koleff, User Experience Lead at the Genuine Parts Company, a distributor of auto and industrial replacement parts, among other items; and Noel McDonagh, Director of Information Development at Dell EMC, which provides a range of data-related products and services, including storage and security. Shimpeno described his company’s approach to aligning taxonomy’s back-end hierarchy (in Etsy’s case, how sellers classify things) and the customer-facing front end. The back end, he said, “can be very different sometimes to how a buyer actually tries to find things.” Some people know exactly what they want, including many specifications, while others are just looking for a simple pair of scissors. On Etsy’s back end, “we have been trying to pare things down to what the thing actually is, and then having our sellers answer questions and describe attributes like color, size, material,” adding, “We do a lot of one-to-one stuff, to find more flexibility between the back-end seller and the front-end buyer.” In part, becoming more effective depends on understanding “that the way people look at things internally can be very different from the way people look at things externally,” Earley said. “There are many different varieties of customers,” said Dell EMC’s McDonagh, “and we have to segment those categories so we understand what they need. We have to align that understanding to the back end, where we are actually creating the information, and also align it to the front end.” Because the segments have different needs, a variety of information components, or systems, is required, putting the burden on “the creators of the information to utilize that same information across the board for those multiple systems. It’s a matrix that we are always looking at, evaluating how it is being used.” “There’s the technical customer who wants to get into the details,” McDonagh said, “and there’s the architecture customer who wants to understand the interconnectivity of different systems. Understanding those customer profiles relates very much to the front-end hierarchies, and then we have to support those front ends with the back end.” To keep pace with the needs of different customer groups and changes in products and services, how do you handle the updating of taxonomies? How do you manage the enablers in the process: merchandisers and subject matter experts? “From a day-to-day perspective, we hire a lot of people who straddle areas of expertise,” said Megan Koleff, from Genuine Parts. They need “a good foundation of knowledge in our industries as well as technological expertise so that they are able to implement.” It is a challenge, “as we start to overlay more customer demand. How does that core taxonomy shift and change? Do we need to set up other virtual taxonomies for different users (along with different tools) because we are overlaying the customer’s mental model?” “It’s a good challenge to have,” Koleff said, although everything is getting “significantly more complex.” The roundtable featured a real-time survey of the webinar attendees: Other than a primary product hierarchy, what navigational hierarchies does your website provide? Applications (32% of respondents), standards (24%) and industries (22%), with 30% saying “nothing else” and 27% choosing “something else” How does your website leverage product relationships? Merchandising product groupings (42%), solution bundles (39%), “users who bought this also bought . . .” (39%) and qualified product-to-product tagging (related parts and accessories, etc.) (21%). Twenty-four percent said “none of the above” How do you ensure that taxonomies are effective? “We have informal reviews by our internal subject matter experts” (32%), “we perform competitive analysis and survey our customers” (18%) and “we have a rigorous formal process for testing and validation driven by use cases and compared with baseline metrics” (18%). An additional 25% said that “we perform very little, if any, testing” Please use these links to access the roundtable recording and a related article. The Earley Executive Roundtable is an educational webinar series focusing on topics of interest in the areas of digital transformation and information science. Each month, EIS leads a lively discussion with a panel of industry experts. The next roundtable is scheduled for Wednesday, Oct. 25, 2017 at 1 p.m. ET, on the topic of “Training AI-Driven Support Bots to Deliver the Next Generation of Customer Experience.” Click this link to register for the webinar. About Earley Information Science: EIS is a specialized information agency. We support business outcomes by organizing your data—making it findable, usable and valuable. Our proven methodologies are designed specifically to address product data, content assets, customer data and corporate knowledge bases. We deliver governance-driven solutions that scale and adapt to your business as it grows. For more information, visit www.earley.com.  #####

Product information management for conglomerates can be devilishly difficult, but there are ways to do it right, say experts at Earley Information Science roundtable It’s hard enough to design and implement a “garden variety” product information management (PIM) program. Even at a single-line company with a straightforward structure and limited market reach, it’s just not that easy to figure out product names, determine which attributes to tout and organize everything into an effective system—and somehow also win consensus from various stakeholders along the way. But the challenges, and potential pitfalls, are exponentially greater at conglomerates and other complex decentralized enterprises, where PIM may have to function as a shared platform across numerous operating units, or even separate companies, in any number of markets or perhaps all around the world. Consensus in this context has to be reached despite yawning differences in processes, priorities, products and services. The task is formidable, so much so that you have to ask whether there are too many variations to support “one system of record,” says Dino Eliopulos, Managing Director of Earley Information Science (EIS). “What are the limits to the value of supporting a centralized system? Can so many different business units all standardize on a single PIM model?” The do’s and don’ts of implementation, and the reasons why PIM is still very much worth the effort, were discussed by a panel of manufacturing, distribution and knowledge management experts at an Executive Roundtable hosted on Aug. 31 by EIS, a leading consulting firm focused on organizing information for business impact. Among other things, big decentralized enterprises have to decide “what products belong in the PIM and what data is appropriate to master for those products,” Eliopulos said, and whether to use a “big bang” approach to implementation or one that is incremental. And they have to settle on the right governance structure. The roundtable discussion, “Product Information Management for Conglomerates: The Best Approach for Complex Decentralized Enterprises,” was led by Eliopulos and included Marguerite Eddy, Principal Data Architect at National Instruments, a producer of automated test equipment and virtual instrumentation software, and Jennie Yates, Manager, eCommerce Catalog and Content, at WESCO Distribution, an electronics distribution and services company. “PIM’s always a good idea,” said Yates. “It’s a very difficult journey to start, when you are looking at it from an enterprise-wide management point of view,” but the potential payoff is enormous. “It’s really part of that whole master data management [MDM], big data theory of reaping the benefits of having all of your product data in one place,” serving multiple parts of the enterprise. “The true secret sauce in starting the journey,” Yates added, “is not to look at it as technical implementation,” which is certainly involved, but rather as a chance to understand the business processes of all affected entities and operations and identify the things that need to change. Through these conversations “you begin to develop your requirements to get a shared PIM throughout the organization that would be in everybody’s interest.” Eddy agreed. “We went through strategic sessions with stakeholders across the company to define what we meant by product and to determine the scope of what we were working with. And only then did we start looking at technology.” “That upfront input,” Yates added, “defines the business process that’s going to support the PIM,” including change management and the commitment to provide more resources. The panelists also discussed the types of data that belong in the PIM, including product attributes; the considerations in deciding between the big bang and incremental transition approaches; the need for dual maintenance in making the shift from legacy systems; and the governance issues that can affect time to market. The roundtable featured a real-time survey of the webinar attendees: When asked how they are using PIM in their organization, 20% said enterprise-wide as the system of record for all product content and 30% said across many business units or departments. But the remaining 50% said they don’t have a PIM system of any kind When asked if they are using PIM for master data, 9% said they master all of their product data across all channels, 9% use such data for digital channels and 36% said PIM is one of a number of sources of product data. Another 45% said they did not use PIM for master data management Finally, when asked if they could see their business using PIM as an MDM platform across all lines of business and subsidiaries, 17% said they are already doing just that “to great effect” and another 17% said they have plans and funding to follow suit within the next 12 months. Meanwhile, 33% said they are evaluating the various approaches and another 33% have no plans and are not interested Please use these links to access the roundtable and a related article. The Earley Executive Roundtable is an educational webinar series focusing on topics of interest in the areas of digital transformation and information science. Each month, EIS leads a lively discussion with a panel of industry experts. The next roundtable is scheduled for Sept. 28, on the topic of “Beyond Taxonomy: How Manufacturers and Distributors Are Innovating in eCommerce.” To sign up, contact Sharon Foley at Sharon.Foley@earley.com. About Earley Information Science: EIS is a specialized information agency. We support business outcomes by organizing your data—making it findable, usable and valuable. Our proven methodologies are designed specifically to address product data, content assets, customer data and corporate knowledge bases. We deliver governance-driven solutions that scale and adapt to your business as it grows. For more information, visit www.earley.com. #####

Because technical buyers have no patience for sales pitches, successful web sites draw them in with practical experiences based on a deep knowledge of who they are and what they want, say experts at Earley Information Science roundtable “Skip the sales pitches and just give me what I need,” engineers, procurement managers and other technical buyers plead. They’re not like B2C shoppers. They are all business—typically facing complicated projects and inflexible deadlines—and often arrive with extremely long lists of required parts and equipment and very short fuses. But giving them what they need is not easy, and the stakes can be very high, said Dino Eliopulos, Managing Director of Earley Information Science (EIS). “Recommend the wrong component to an engineer and you could end up with a collapsed building, exploding rocket or poisoned hamburger. And yet these customers say, ‘Do not market to me.’ ” Given the suspicions that tech buyers harbor for anything that looks like merchandising and advertising, including product recommendations, getting the right products in their hands is a challenge that many marketers don’t know how to solve, and some don’t fully recognize. The answer is to deliver a customized, albeit bare-bones, online experience that is efficient, practical and trustworthy, according to a panel of marketing and knowledge management experts at an Executive Roundtable discussion hosted on July 26 by EIS, a leading consulting firm focused on organizing information for business impact. What is required, the experts said, is a sophisticated soft-sell formula that depends heavily on understanding the different segments in the tech demographic and how customer journeys vary; the approaches that will engage these buyers before, during and after making purchases; and the role that analytics, artificial intelligence (AI) and machine learning can play in fueling the effort. The roundtable discussion, “The Secret to Successfully Marketing to the Technical B2B Buyer,” was led by Eliopulos and included Yvonne Brown, Partner and Chief Marketing Officer (CMO) of Chief Outsiders, a marketing strategy firm focused on startup to mid-sized companies; Hayne Shumate, Senior Vice President of Internet Business, Mouser Electronics, which sells components to engineers designing circuit boards for new projects; and Michelle Fields, Senior Director of Marketing and eCommerce at Brock White, a distributor of construction materials. “While we are pleased to serve anyone who comes to our website, our target customers are design engineers or procurement professionals who have been given a list of products from an engineer,” said Mouser’s Shumate. “Engineers are not interested in sharing their ideas with us. So, we have to understand what they need and focus on getting them to their products as quickly as possible, while staying out of their way when they do their shopping.” But tech buyers come in all shapes and sizes. Brock White works with buyers involved with huge projects, Michelle Fields said, but also sells to one-person businesses and to consumers who want to work with a contractor to add stone to their home. “Kind of the whole gamut,” she noted, and the wide range in roles and products affects the buyer’s involvement in the purchasing decision. “There may be differences in the time scales and in the linearity and non-linearity of the shopping process,” Eliopulos added. How do you engage these various buyers? In other words, how do you use the site’s content and functionality? Again, the type of buyer is key. A procurement specialist wants to see a list of things to order, Fields said, while an engineer is after pieces of technical information and an architect is looking for inspiration. “It depends on the persona that comes to the web site.” One common denominator, though, is the desire for transparency and accuracy. A paramount concern for many buyers, according to Yvonne Brown, is the ability “to get information they need to a very detailed level and have confidence that the information is 100% accurate.” They want to see an image, zoom into it and examine it from different perspectives. And then there is “ease of consumption,” she said. “Not using a video when it could be simpler to use text, or using a video for demonstration purposes when it adds a lot of value.” After all, “the technical buyer in general is very pressed for time these days,” and anything that saves time is highly appreciated. Another area of confidence building is having accurate inventory online, she said, given the critical timelines often at play. “They not only need the right product, they also need it on time.” As for product reviews, those have little value, she noted, “because there isn’t confidence that the person who is reviewing the product is using it in the right way or understands it properly.” Instead, tech customers tend to prefer opinions from peers they know. The panelists also discussed the critical supporting role that big data and machine learning can play in the tech buyer’s shopping experience. Brock White is “working through data to help build segmentation,” said Michelle Fields, a process that allows companies to “find out who your core spots or core customers are” and to better understand the differences in customer journeys. That kind of understanding, Yvonne Brown added, gives you the opportunity to “provide buyers with the right information” as they try to apply product research to the project or design they are working on. That said, Hayne Shumate noted privacy concerns that restrict the collection of certain data in a number of markets around the world. The roundtable featured a real-time survey of the webinar attendees: Nearly half, or 47%, said their business as a whole depends on B2B technical buyers, and an additional 35% said such buyers are important to a portion of the business In identifying the most important factors in engaging the tech buyer, the respondents chose product selection and price (35%), rich meaningful content and product information (30%) and product findability (25%) As for using advanced analytics and AI to engage customers, 26% said they are already doing that to great effect and 16% said they had plans to do so within the next year. But more than half, or 58%, said they are still evaluating the approach to take Please use these links to access the roundtable and a related article. The Earley Executive Roundtable is an educational webinar series focusing on topics of interest in the areas of digital transformation and information science. Each month, EIS leads a lively discussion with a panel of industry experts. The next roundtable is scheduled for Aug. 31st. Click here to register for the live event, or to view a recording afterward. About Earley Information Science: EIS is a specialized information agency. We support business outcomes by organizing your data—making it findable, usable and valuable. Our proven methodologies are designed specifically to address product data, content assets, customer data and corporate knowledge bases. We deliver governance-driven solutions that scale and adapt to your business as it grows. For more information, visit www.earley.com. #####

Most of AI’s promise may be in the future, but companies must prepare now or risk falling behind for good, says CEO of Earley Information Science Artificial intelligence has become the “it” topic in the business news sections and throughout the tech world, commanding attention for everything from self-driving cars to predictive analytics and maintenance. But many companies are watching from the sidelines, convinced that there is little AI can do for them now and that it will be easy enough to plug in down the road, when the full power of the technology will kick in. These companies are fooling themselves and flirting with existential danger, warns Seth Earley, founder and CEO of Earley Information Science Corp. (EIS), a leading consulting firm focused on organizing information for business impact. “They don’t know what they don’t know, and they don’t appreciate the capabilities that they don’t have,” said Earley, issuing a call to action following his recent appearance at this year’s MIT Sloan CIO Symposium. “They are operating under the delusion that once they decide to adopt AI, it will magically do everything for them. But AI is not magic, and companies that are not putting in the time and the effort now to learn how to apply AI to today’s problems are going to lose ground, perhaps permanently, to companies that will.” At the CIO Symposium, Earley participated in a panel discussion moderated by Joi Ito, Director of the MIT Media Lab. One of the big takeaways from the panel, “Putting AI to Work,” is that the technology, at least for the immediate future, represents less of a threat to replace human workers and more of a positive change, in that it could improve, or “augment,” human activity. And even though companies may not think AI is relevant to their activities, Earley says, the processes they use to perform those activities are often ripe for AI efficiencies. “Companies that realize this and act on it,” Earley says, “will become more competitive and therefore will outperform their peers.” “AI is evolving very quickly, and organizations need to move quickly, too, to build fundamental new abilities for the new AI world,” Earley says. Ironically, they have to make the transition the old-fashioned way, “based on tried-and-true information management principles. AI tools don’t operate on junk—otherwise, it’s garbage in, garbage out. In other words, it’s the data, stupid. The AI machines have to be ‘fed’ the right data and the right content, properly structured and curated.” That structure, a company’s so-called knowledge architecture, is core to the AI process. It makes it easier to find and use information today—helping you, for instance, to deal quickly and correctly with an on-line customer’s questions—even as it positions you for the further preparations that will be needed to handle AI in the long term. “If you don’t have that right, you can’t build on top of it,” Earley says. Eventually, AI will prove very disruptive to the job market, but for now the change is more subtle: rather than replacing people, AI is shifting them into roles and tasks that will require new skills. “It’s really about making people more productive,” Earley says. “We have to look at this as a partnership, using AI to build new capabilities through really high-quality, interactive, personalized training that takes into consideration different learning styles and natural skills.” “We have to train the robots with the right knowledge architecture,” Earley says. “But we also have to train the people to use the robots.” ***** Please use these links to access the CIO Symposium discussion on putting AI to work and to review EIS resources about AI. Seth Earley’s expertise includes knowledge strategy, data and information architecture and search-based applications. For more than 20 years, he has worked with a diverse roster of Fortune 1000 companies. He helps them improve performance by making information more findable, usable and valuable, particularly with reference to analytics, eCommerce and customer experience. He has briefed many C-level executives on the principles of AI and cognitive computing, explaining the practical steps that need to be taken to cut through the noise and get value from emerging technologies. He can be reached at seth@earley.com. About Earley Information Science: Earley Information Science is a specialized information agency. We support business outcomes by organizing your data. Our proven methodologies are designed specifically to address product data, content assets, customer data and corporate knowledge bases. We deliver governance-driven solutions that scale and adapt to your business as it grows. For more information, visit www.earley.com.

2017 MIT Sloan CIO Symposium to Provide Roadmap for the Global CIO Adventure: Seth Earley, CEO of Earley Information Systems, to discuss at the Nation’s Premier CIO Conference on May 24, 2017 Earley Information Science (EIS) today announced that Seth Earley, CEO of EIS will be a speaker at the at the 14th Annual 2017 MIT Sloan CIO Symposium, the nation’s premier CIO conference on May 24, 2017. Earley will be speaking about artificial intelligence (AI) applications that are currently in practice or are imminent. The panel session, entitled “Putting AI to Work,” will also feature speakers from Cogito Corporation, Clearpath, OTTO Motors, and MIT. Earley is one of an elite group of presenters from a wide range of industries participating in the conference. While the fully autonomous vehicle is the poster child for AI, it is still five or more years out on the horizon. In contrast, many implementations of AI are available today or will be within the next year or so. AI technologies and AI-driven products are enabling new services never possible before, providing deep business intelligence, automating work, and cutting costs. The development and deployment of these systems also raise ethical and regulatory concerns as well as the risk of the displacement of jobs. This panel will focus on how firms are implementing or how they expect to implement AI, including effectiveness, stage of adoption, and benefits, as well as the potential impacts on unemployment and society The premier conference will bring together more than 800 global CIOs, senior IT executives, technology innovators and MIT academic thought leaders together on the MIT campus in Cambridge, Massachusetts, for a full day of networking, collaboration and discussions around building a digital organization, IT talent management, business leadership and the increasingly important impact technology is having on corporations and society. More than a dozen keynote presentations and interactive panel discussions tied to this year’s theme “The CIO Adventure: Now, Next and…Beyond” will feature more than 60 business leaders, technology trendsetters, and thought leaders from academia. In addition to “Putting AI to Work,” topics to be addressed during the conference, include: Pathways to Future Ready: The Digital Playbook Preparing for the Future of Work Trusted Data: The Role of Blockchain, Secure Identity, and Encryption Who’s Really Responsible for Technology? Expanding the Reach of Digital Innovation Running IT Like a Factory Navigating the Clouds What Comes After Digital Transformation? You Were Hacked—Now What? Talent Wars in the Digital Age Winning with the Internet of Things The CIO Adventure: Insights from the Leadership Award Finalists Measuring ROI for Cybersecurity: Is It Real or a Mirage? The MIT Sloan CIO Symposium is co-organized by the MIT Sloan Boston Alumni Association, the MIT Initiative on the Digital Economy (IDE), and the MIT Sloan Center for Information Systems Research (CISR). It will take place from 8:00 a.m. to 7:00 p.m. on Wednesday, May 24, 2017, at the Massachusetts Institute of Technology, Kresge Auditorium, 48 Massachusetts Avenue, Cambridge, MA. To register for the Symposium, please click here. About the MIT Sloan CIO Symposium The MIT Sloan CIO Symposium is the premier global conference for CIOs and digital business executives to become more effective leaders. In one day, CIOs and senior IT executives explore enterprise technology innovations, business practices and receive actionable information that enables them to meet the challenges of today and the future. The Symposium offers a unique learning environment by bringing together the academic thought leadership of MIT with the in-the-trenches experience of leading, global CIOs and industry experts. The MIT Sloan CIO Symposium is organized and developed by the MIT Sloan Boston Alumni Association, the MIT Initiative on the Digital Economy (IDE), and the MIT Sloan Center for Information Systems Research (CISR). For more information and to register for this year’s Symposium, visit www.mitcio.com. ###

Attendees get an opportunity to be part of the discussion! Sit with many of the day’s speakers to ask questions about their presentations, share your thoughts, and dive deeper into your challenges. Seth Earley will lead a discussion on the changing role of the chief data officer. Each Roundtable discussion lasts 30 minutes – attendees may choose 2.