IM Topic: Advances in AI and Industry Implications

Author: Michael Dziekan

Date: September 19, 2018


Information management leaders must determine how AI can be used to support their organizations:

  • To improve operational efficiency in order to do more with less
  • To scale information governance and data management practices to turn unstructured data into structured knowledge
  • To ensure privacy, security, standards, and usage rights are understood and in practice
  • To acquire deeper understanding of data-oriented copyright restrictions and contract terms amid the evolving digital era
  • To transition from a cost center to a profit center by participating in the AI innovation value chain as a  recognized source of quality data that can be used to train AI

Information management centers must be recognized as best-in-class knowledge centers:

  • To demonstrate relevance and influence in their organizations
  • To permit scaling to ensure that their resources and services are on-target to today’s users
  • By applying AI to help educate the organization on new technologies and skills
  • To illustrate a new class of information managers with modern digital services that provide more value than what end users can obtain online today in open platforms and interfaces

Practitioners must be closer to the end user 

  • AI technologies can be applied to scale the business to address a growing rate and diversity of client queries.
  • Content must be delivered in new, modern, immersive formats (e.g., text, video, and audio) with interactive user experiences across platforms and screens.
  • Quality content and contextually relevant knowledge continue to drive improved decision-making, increasing the importance of the use of advanced analytics and data visualization software by information management and corporate libraries to deliver value directly to the end user.

Our Methodology

This study combines:

  • Synthesis from Outsell’s daily contact and interviews with CEOs, CDOs, CPOs/CTOs and heads of analytics and decision-making data businesses.
  • Deep knowledge of Outsell’s ongoing and unique 20+ years of market analysis
  • Original analysis based on the deep industry experience of our analysts
  • Assessment of technology vendors’ public disclosures and earnings

It also draws upon our unique discipline of studying the major information market components (data/content, technology, and workflow) that, when triangulated, add 360-degree context to our insights into how businesses view, capitalize, and evolve their data and product strategies with AI, while building on prior reports analyzing this topic.

Table of Contents

Why This topic IS IMPORTANT FOR Information Management and Corporate Libraries  3

OUR Methodology  4

AI definition and getting beyond the “Buzz”   5

The AI Market landscape has expanded  13

Core Foundation (AI technology and Data Services)   15

Example: Enabling Immersive Customer Experiences  17

Example: Extracting Meaning an New Insights from Content   18

Example: Leveraging AI an the Cloud to Scale the Business   19

Advancing Functional Applications for the Enterprise   20

Embedding AI in Legacy Portfolios  21

Example: Improving Behavioral Targeting  22

Example: Optimizing Situational Advertising  23

AI is an Enabler for IoT and Vice Versa   24

Advancing Industry solutions for the Enterprise  25

Industry Use Case Examples   26

AI having a Profound Effect on the Financial Sector   27

Example: Amassing New Insights and Predictions in Financial Services  28

Example: Advancing Scientific, Patient Care an Drug Discovery   29

Example: Innovations in Legal Solutions   30

Key Takeaways  31

Imperatives for IM  32

Related Research   33

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