Day 3 | Friday, October 25

MORNING | Plenary Keynote Sessions


8:00 am
Continental Breakfast (Harborview Foyer)

8:15 Keynote: AI World Society Roundtable on AI and Healthcare

Burns_EdModerator: Ed Burns, Site Editor, TechTarget

Silbersweig_DavidPanelist: Professor David Silbersweig,  Board Member of BGF, Harvard Medical School




Truong Vinh Long, MD, CEO, Gia An 115 Hospital 



Professor Mai Trong Khoa, PhD, Chairman of the Nuclear Medicine and Oncology Council, Director of the Gene-Stem cell Center, Bach Mai hospital, Senior lecturer, Hanoi Medical University, Secrectary of the National Council of Professorship in Medicine in Vietnam 



Truong Van Phuoc, PhD, Former Acting Chairman, State Inspectory Committee of Finance of Vietnam, Senior Advisor to Chairman, Vietbank 



8:45 Conference Introduction

Lundstrom_ScottScott Lundstrom, Group Vice President and General Manager, IDC Government and Health Insights, IDC and AI World, Conference Co-Chair 

8:50 Keynote Introduction

Yucel_EnverEnver Yucel, Chairman, Bahçeşehir University

9:00 Keynote: Enhancing Human Capability with Intelligent Machine Teammates

Shah_JulieJulie Shah, Associate Professor of Aeronautics and Astronautics, MIT 

Every team has top performers -- people who excel at working in a team to find the right solutions in complex, difficult situations.  These top performers include nurses who run hospital floors, emergency response teams, air traffic controllers, and factory line supervisors. While they may outperform the most sophisticated optimization and scheduling algorithms, they cannot often tell us how they do it.  Similarly, even when a machine can do the job better than most of us, it can’t explain how. In this talk I share recent work investigating effective ways to blend the unique decision-making strengths of humans and machines. I discuss the development of computational models that enable machines to efficiently infer the mental state of human teammates and thereby collaborate with people in richer, more flexible ways.  Our studies demonstrate statistically significant improvements in people’s performance on military, healthcare and manufacturing tasks, when aided by intelligent machine teammates.

9:30 Keynote: Democracy, Ethics and the Rule of Law in the age of Artificial Intelligence

Nemitz_Paul2Paul F. Nemitz, Principal Advisor in the Directorate-General for Justice and Consumers, European Commission 

10:00 Keynote: AI in Pharma: Where We are Today and How We Will Succeed in the Future

Jovanovic_NatalijaNatalija Jovanovic, PhD, Chief Digital Officer, Sanofi Pasteur 

Impact of adopted AI solutions varies broadly across industries, but some industries have made larger strides than others. This conversation will take a look at characteristics of situations where AI has not only been more adopted, but has also realized more valuable outcomes. We will compare those situations and the current state in the pharma industry, in hopes of crystallizing concrete actions towards realizing more impact from AI in pharma.

10:30 Start-up Awards Announcement

Desmond_JohnJohn Desmond, Principal at JD Content Services, Editor AI Trends 

10:35 am - 1:45 pm Expo Hall Open Hours (Commonwealth Hall)

10:35 Coffee Break in the Expo Hall (Commonwealth Hall)

10:50 Executive Roundtable: Enterprise AI Innovations

Technology strategy is directly tied to the mission and values of the enterprise. Successful companies are implementing AI solutions to address changing market environments, new competitive landscapes, andkindle the creative potential of their workforce. In this roundtable discussion, technology leaders from innovative companies share how their organizations are embracing AI technologies, removing barriers, and preparing employees for the future of work. The panel will explore the use of AI automation, and its roles in transforming organizations and fostering a culture of innovation in the enterprise. 

Patience_NickModerator: Nick Patience, Founder & Research Vice President, Software, 451 Research

Monfort_Norbertv2Panelist: Norbert Monfort, Vice President, IT Transformation and Innovation, Assurant Global Technology 

Rudina SeseriRudina Seseri, Founder and Managing Partner, Glasswing Ventures





fitzgerald_dawnDawn Fitzgerald, Director of Digital Transformation Data Center Operations, Schneider Electric 

11:30 Keynote: How AI is Helping to Improve Canadian Lives Through AML

Gossain_VishalVishal Gossain, Vice President, Global Risk Management, ScotiaBank 

The government of Canada is executing on a vision to become the best destination for artificial intelligence (AI) workers. Through the design of its immigration system, development of a diverse workforce, and innovative AI ecosystem, Canada is preparing to lead in AI and machine intelligence. This session explores the state of the practice of AI in Canada’s financial services markets, and discusses how machine learning is being applied to detect and counter financial crimes, such as anti-money laundering (AML) and fraud. Given that the financial services industry is also heavily regulated, we will also discuss how machine learning can assist in compliance by flagging anomalies and automating the reporting process. 

12:10 pm Luncheon Keynote (complimentary lunch voucher will be provided to those who attend this keynote): How AI/ML is Changing the Face of Enterprise IT

Aimes_RobertRobert Ames, Senior Director, National Technology Strategy, VMware Research, VMware

ML/AI is transforming the IT world. As workloads, AI/ML requires new infrastrucure capabilities previously only seen in HPC. And as techniques, it powers the vision of a self-driving data center in which ML-powered IT components combine to deliver next generation IT capabilities. We will discuss both facets of this transformation.

12:30 – 1:45 Networking Coffee and Dessert in the Expo – Last Chance for Viewing  (Commonwealth Hall)

1:45 – 4:45 Afternoon Breakout Tracks

4:45 Close of AI World 2019 


AFTERNOON | Concurrent Tracks

Waterfront 2

Track 10: Preparing Big Data for Automation & Monetization

Track Chair: Judith Hurwitz, President & CEO, Hurwitz & Associates 

With data in-hand, machine learning aids in everything from cleaning datasets to managing multiple data sources to synthesizing data. With the help of machine learning, data can now be monetized. This track identifies key business strategies for data monetization and steps to be taken to maximize the impact of AI technology interaction with Big Data.

  • What process or framework do you use to create new data monetization business models?
  • How much data is enough? Do you have too much data or not enough? How do you to get the data that you need?
  • Identify how challenges in data storage, processing, and analysis can be overcome using AI technologies

Click here for details

Harborview 1

Track 11: Automating Strategic Enterprises Functions

Track Chair: Mickey North Rizza, Program Vice President, Enterprise Applications and Digital Commerce, IDC  

Enterprise organizations have a range of core business operations able to utilize AI technologies, however, this one-size-fits-all functionality can be a non-starter for some industries. Whether due to regulation, government oversight compliance, or unique requirements, these vertical markets may appear to be laggard adopters. Hear how these companies can innovate using intelligent solutions for sales, marketing, finance, engineering, HR, customer service, change management, corporate governance, and more.

  • How, regardless of industry, AI is reducing human error and creating higher repeatability
  • The ways that workers are being trained to handle more complex, subjective, and creative tasks alongside AI deployment
  • The need for data sciences to enhance all enterprise roles and functions

Click here for details


Track 12: AI in Telecom & Mobile

Track Chair: Berge Ayvazian, Senior Analyst and Consultant, Wireless 20/20 

According to a recent article in Forbes, “…a fully autonomous self-driving vehicle will be the epitome of AI and 5G technology.” The synergy between Artificial Intelligence (AI) and 5G is likely to lead to dramatic breakthroughs. Enterprises are especially interested in how the business case for their investments in Big Data, Cloud and IoT applications will be enhanced by AI and 5G networks.

  • What business growth strategies are mobile network operators considering for deployment of AI in 5G?
  • How are investments in AI startups differentiating 5G devices?
  • What AI applications will drive ROI in 5G wireless networks?

Click here for details

Harborview 3

Track 13: AI in Healthcare

Track Chair: Cynthia Burghard, Research Director, Value-based Healthcare IT Transformation Strategies, IDC 

Artificial intelligence in the healthcare industry is predicted to save $150 billion annually for the US. As such, AI is being rapidly deployed in many areas of the healthcare landscape. This event will primarily focus on the Providers, attracting CIOs, CTOs, VPs of IT and Informatics along with senior Physicians and Clinicians from leading US hospitals who will share their experiences of using AI in clinical care and hospital operations.

  • Invaluable insight from the Payers, Patients and Investors
  • Integrating human and machine brains: The ethical issues
  • Using AI to generate trends and influence healthcare policy
  • Analyzing the economic models of AI: Who should pay and why?
  • Assessing the impact of recent M&As between payers, providers and PBMs and streamlining AI across all 3 sectors
  • How can chatbots help to evaluate symptoms, manage medications and monitor conditions?
  • Practical application in clinical/patient care: Image analysis, decision making, diagnostics, doctor consultation, personalized treatments, robotic surgery, virtual nursing assistants and electronic health records (EHRs)
  • Increasing efficiency in operations, workflows and administrative tasks (inc EHRs)

Click here for details

Harborview 2

Track 14: AI in Pharma

Track Chair: Mike Townsend, Research Manager, Life Sciences Commercial Strategies, IDC

Application and investment of AI in the pharmaceutical industry is rapidly gaining momentum. We bring together CEOs, CIOs, CTOs and Global AI, IT and Informatics Experts from leading pharmaceutical and technology companies to give strategic talks from a business perspective together with use cases from across the drug development pipeline.

  • What are successful pharma companies doing today to prepare for a data-fueled, machine learning future?
  • Why is the pharma industry finding AI so difficult? Bridging the gap between life science and computer science
  • Breaking down silos: Creating cross-functional AI teams and making data available to all
  • Examining industry partnerships, collaborations and M&As
  • What are the best strategies for hiring AI talent with life science experience?
  • Disrupting drug discovery: Precision medicine, biomarkers, target identification and screening
  • Predicting clinical trial outcomes with the use of AI
  • Using AI to optimize regulatory processes, manufacturing strategies, supply chain, real-world evidence, HR, finance and the commercialization of products

Click here for details

Cityview 2

Track 15: AI & ML in Finance, Banking & Insurance

Track Chair: TBD

Artificial intelligence (AI) and Machine Learning (ML) are disrupting the financial services industry, and rightly so. The Finance, Banking and Insurance industries are sitting atop a mountain of customer data and are well positioned to benefit their business and their customers if they can utilize it effectively. AI can serve to improve decision-making, affect overall business strategy, generate new revenue, predict customer behavior, automate customer service, improve risk models, reduce costs, enhance business operations, improve customer experience, offer tailored products and advice, prevent fraud, and optimize internal processes. This track brings together business leaders and data science practitioners from the leading banks, insurance firms, asset management organizations, broker and investment firms, and fintech startups.

  • How organizations are adopting AI, ML, data analytics, image, voice recognition and NLP technologies across their enterprise to improve their businesses and better serve their customers
  • Integrate AI into business strategy development in banking, finance and insurance to make data-driven management decisions for the enterprise
  • How are innovators and Centers of Excellence bridging the gap between the tech and the business and developing a business case for AI
  • Applying AI to compliance, anti-money laundering (AML), fraud detection and digital identity
  • Using AI, ML and Deep Learning to improve personalization and predict customer behavior in banking, finance and insurance

Click here for details

Waterfront 1

Track 16: AI & Robotics: State of the Practice

Track Chair: Remy Glaisner, Research Director, WW Robotics, IDC

This conference track is specifically designed to impart to technical professionals the information they need to successfully develop the next generation of commercial robotics systems. Talks emphasize the design and development of commercially viable robotics and intelligent systems products including robots, drones, and autonomous machines.

Proposed Sessions:

  • Technologies, Tools and Platforms: covering the latest advances in the core technologies that are common to most classes of robots and intelligent systems, including Sensors and Sensing, Thinking and Cognition, and Actuation and Mobility.
  • Design and Development: covering the design and development of commercial robotic systems.
  • Manufacturability, Production, and Distribution: includes trends, designing for manufacturing, supply chain support, and robotics as a service.

Click here for details 

Cityview 1

Track 17: Cutting Edge AI Research

Track Chair: Ritu Jyoti, Program Vice President, Artificial Intelligence Strategies, IDC

This track will showcase cutting edge research and algorithms from both commercial and academic labs, that will be available for deployment in the next 1-3 years. The audience will learn what is currently being worked on and address several relevant issues, including:

  • How much data is needed to train a model?
  • Robustness of the models – trustworthy models
  • Ensuring privacy in the data

Click here for details