Demystifying AI for the Enterprise
A Playbook for Business Value and Digital Transformation
- Available for pre-order. Item will ship after November 24, 2021
Artificial Intelligence in its various forms – machine learning, chat bots, robots, agents, etc. – is increasingly being seen as a core component of enterprise business workflow and information management systems. The current promise and hype around AI are being driven by software vendors, academic research projects, and startups. However, we posit that the greatest promise and potential for AI lies in the enterprise with its applications touching all organizational facets.
Increasing business process and workflow maturity coupled with recent trends in cloud computing, datafication, IoT, cyber security, and advanced analytics, there is appreciation that the challenges of tomorrow cannot be solely addressed with today’s people, process, and products. A recent Gartner article supports our contention that AI is essential because it "promises to solve problems organizations could not before because it delivers benefits that no humans could legitimately perform."
There is still considerable mystery, hype and fear about AI. A considerable amount of current discourse focus on a dystopian future – with adversity impacted individuals/employees/society. Such opinions, with understandable fear of the unknown, don’t consider the history of human innovation, current state of business/technology, or the primarily augmentative nature of tomorrow’s AI.
Our book demystifies AI for the enterprise. Our journey takes the reader from the basics (definitions, state of the art, etc.) to a multi-industry journey, and concludes with validated expert advice on everything an organization and its people must do to succeed. Along the way, we also debunk myths, provide practical pointers, and include best practices with appropriate vignettes.
In summary, AI brings to enterprises capabilities that promise new ways by which professionals can address both mundane and interesting challenges more efficient, effectively, and collaboratively (with humans). The opportunity for tomorrow’s enterprise is to augment existing teams and resources with the power of AI in order to gain competitive advantage, discover new business models, establish or optimize new revenues and achieve better customer/user satisfaction.
Table of Contents
Chapter 1: AI Strategy for the Executive
Chapter 2: Learning Algorithms, Machine/Deep Learning, and Applied AI – A Conceptual Framework
Chapter 3: AI for Supply Chain Management
Chapter 4: HR and Talent Management
Chapter 5: Customer Experience Management
Chapter 6: Financial Services
Chapter 7: Artificial Intelligence in Retail
Chapter 8: Visualization
Chapter 9: Solution Architectures
Chapter 10: AI and Corporate Social Responsibility
Chapter 11: Future of Enterprise AI
- Banking Case Study #1: Get More Value from Your Banking Data – How to Turn Your Analytics Team into a Profit Centre
- Banking Case Study #2: AI in Financial Services – WeBank Practices
- Retail Case Study: 7-Eleven and Cashierless Stores
- Supply Chain Case Study: How Orchestrated Intelligence is Utilising Artificial Intelligence to model a Transformation in Supply Chain Performance
- FMCG Case Study: Paper Quality at Georgia-Pacific
- Healthcare Case Study: GE Healthcare: 1st FDA Clearance for an AI-enabled X-ray Devices –
Prashant Natarajan is Product Director of Healthcare Solutions at Oracle in the Health Sciences Global Business Unit. He has portfolio responsibility for precision medicine, population health, translational research, and convergence products. He is passionate about helping healthcare organizations maximize their technology investments to improve patient care, provider satisfaction, personal wellness, and health policy. Prior to joining Oracle in 2008, Prashant contributed to progressive career roles as product manager, emerging technologies specialist, and consultant at Healthways, McKesson, Siemens, and eCredit. Com.
Prashant received his master’s degree in technical communications and linguistics from Auburn University (2005) and his undergraduate degree in chemical engineering from Mangalore University (1999). He is also a Stanford Certified Project Manager. Prashant is author or contributing author of three books on healthcare informatics.
Prashant is Industry Advisor for Data Science and AI at UCSF/Center for Imaging of Neurodegenerative Disease in the San Francisco VA Center. He volunteers on the Board of Advisors for the Council for Affordable Health Coverage, Washington, DC, and is currently serving as Co-Chair of HIMSS NorCal’s Innovation Committee.
Dez Blanchfield is a strategic in business and digital transformation, with 25 years experience in the information technology and telecommunications industry, developing strategy and implementing business initiatives. His specialties include; cloud computing, big data and analytics, cognitive computing, machine learning, Internet of Things, digital transformation infrastructure and architecture and security and regulatory compliance.
Kirk Borne is the Principal Data Scientist and Executive Advisor at Booz Allen Hamiliton. He is a data scientist and an astrophysicist who has used his talents at Booz Allen since 2015. He was professor of astrophysics and computational science at George Mason University (GMU) for 12 years. He served as undergraduate advisor for the GMU data science program and graduate advisor in the computational science and informatics Ph.D. program.
Kirk spent nearly 20 years supporting NASA projects, including NASA's Hubble Space Telescope as data archive project scientist, NASA's Astronomy Data Center, and NASA's Space Science Data Operations Office. He has extensive experience in large scientific databases and information systems, including expertise in scientific data mining. He was a contributor to the design and development of the new Large Synoptic Survey Telescope, for which he contributed in the areas of science data management, informatics and statistical science research, galaxies research, and education and public outreach.
Bob Rogers, PhD is Chief Data Scientist for Analytics and Artificial Intelligence Solutions at Intel, where he applies his experience solving problems with big data and analytics to help Intel build world-class customer solutions. Prior to joining Intel, Bob was co-founder and Chief Scientist at Apixio, a big-data analytics company for healthcare. He has co-authored the book Artificial Neural Network: Forecasting Time Series, which led to a twelve-year career managing a quantitative futures trading fund based on computer models he developed. He received his BS in Physics at UC Berkeley and his PhD in Physics at Harvard.
John Frenzel, MD, is the Chief Medical Informatics Officer at MD Anderson Cancer Center and a Professor in the Department of Anesthesiology and Perioperative Medicine. He received his medical degree from Baylor College of Medicine and completed his fellowship training in Cardiovascular and Thoracic Anesthesia at the Mayo Clinic in Rochester, MN.
In 2001, he received a Master’s Degree in Informatics from the University of Texas Health Science Center Houston, School of information Science. Dr. Frenzel has been active in applied informatics throughout his career at MD Anderson.
In addition to several clinical leadership roles, in 2010 he was asked to led the development and installation of MD Anderson’s third-generation Clinical Data Warehouse, which sought to bring together all institutional clinical and genomic data. In 2012, he was asked to help lead the Institution’s effort to install the Epic EHR and integrate clinical data back into the institutional warehouse.
John has published on various topics pertaining to clinical informatics. He is currently focused on the use of Time-Driven Activity-Based Costing (TDABC) to drive hospital revenue process optimization and labor costing efforts in preparation for bundled payments in oncology care. He is Board certified in both Anesthesiology and Informatics.