Day 2 | Thursday, October 24

MORNING | Plenary Keynote Sessions


8:00 am
Continental Breakfast (Harborview Foyer)

8:20 Breakfast Keynote: The Promise and Pain of Computer Vision in Retail, Healthcare, and Agriculture

Ben Schneider, Vice President, Product, Alegion

Rapid advancements in computer vision are empowering enterprises to increase automation, create new business value, and gain a competitive advantage. Specifically retail, agriculture, and healthcare are adopting some of the most innovative forms of machine learning. However, it is a difficult task to get computer vision models into a production ready state at the required scale.  In this session Ben will cover some of the most cutting-edge examples being applied as well as expose the biggest challenges that occur while creating these types of models and define strategies that can be used to overcome these challenges.

9:00 Conference Introduction

Weinman_EliotEliot Weinman, Founder & Conference Chair, AI World; Executive Editor, AI Trends

9:05 IDC Introductory Remarks

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

9:15 Keynote: The Human Strategy

Pentland_Alex_SandyAlex Sandy Pentland, PhD, Professor, Engineering, Business, Media Lab, MIT    

Government and civic systems can potentially have great benefit from AI, but how are we going to make sure that AI serves everyone?   The trust data consortium at MIT builds systems for counties ranging from the EU to China to Senegal that provide greater transparency, accountability, and effectiveness in both government and private domains.   The key is handling data correctly, and providing the right sort of governance. 

9:45 Keynote: Uber’s Intelligent Insights Assistant

Bell_FranziskaFranziska Bell, PhD, Director, Data Science, Data Science Platforms, Uber 

Wouldn't it be amazing to have highly accurate forecasts, anomaly detection and intelligent exploratory data analysis at a touch-of-a-button? The Platform Data Science team at Uber builds scalable platforms and tools that are making this a reality, resulting in faster innovation cycles and more accurate insights. 

10:15 Keynote: AI in Finance: Present and Future, Hype and Reality 

Elkan_CharlesCharles Elkan, PhD, Managing Director, Goldman Sachs

Artificial intelligence (AI), which includes machine learning and natural language processing, has great achievements and great potential in many industries, including finance. However, AI technologies are far from being magical and far from equaling humans in many capabilities. This presentation will explain concretely what AI methods are and are not capable of currently, and will provide a framework for predicting the success or failure of potential applications of AI. 

10:40 Coffee Break (Harborview Foyer)

11:00 Keynote: AI at Work in Legal, News and Tax & Accounting

Al-Kofahi_KhalidKhalid Al-Kofahi, PhD, Vice President, Research and Development. Head - Center for AI and Cognitive Computing, Thomson Reuters

This talk focuses on the practical side of AI. Starting with an overview of some of the opportunities that for AI and ML in the legal, news, and tax & accounting industries, followed by an in-depth discussion of example case studies and ending with best practices and lesson learned from building dozens of AI-powered applications to quality and scale. 

11:25 Executive Roundtable: Disinformation, Infosec, Cognitive Security and Influence Manipulation

Krigsman_MichaelModerator: Michael Krigsman, Industry Analyst, CXOTalk

Breuer_PabloPanelists: Pablo Breuer, Director of US Special Operations Command Donovan Group and Senior Military Advisor and Innovation Officer, SOFWERX

Terp_SJSara-Jayne Terp, Data Scientist, Bodacea Light Industries LLC 

Gourley_BobBob Gourley, Co-Founder and CTO, OODA LLC

Scriffignano_AnthonyAnthony Scriffignano, PhD, SVP, Chief Data Scientist, Dun & Bradstreet 


Fighting disinformation (and misinformation) attacks has become a crucial part of information security.  At this AI World executive plenary roundtable, three experts explain these dangerous attacks, which are based on influence and manipulation, and how to disrupt them. 

11:50 Session Break

11:50 am - 6:30 pm Expo Hall Open Hours (Commonwealth Hall)

12:00 pm Luncheon Keynote (complimentary lunch voucher will be provided to those who attend this keynote): Case Studies of Conversational AI: Real Deployments at Scale 

Customer experience (CX) will overtake price and product as the key brand differentiator by next year (Walker Study).  Because of this, CX is at the heart of the AI adoption for most enterprises,  and they are embracing it as a key component of their digital transformation initiatives.  In particular, Conversational AI is enabling brands to deliver dramatically improved CX and customer engagement, while also providing significant and demonstrable operational savings. 

Join Interactions as we discuss how leading enterprises have accelerated their transition from today's frustrating and uninspired customer service transactions to productive, conversational experiences.  We’ll discuss several real use cases and you'll hear first hand how our Intelligent Virtual Assistant helped Constant Contact to reduce their rate of misroutes and lower average handle time per call, while creating a pleasant, streamlined process for their consumers. 

Freeze_JimJim Freeze, Chief Marketing Officer, Interactions

Bauks_BenBen Bauks, Sr. Business Systems Analyst, Constant Contact



12:25 Networking Coffee and Dessert in Expo (Lunch available for purchase) (Commonwealth Hall)

1:30 – 5:05 Afternoon Breakout Tracks 

5:05 – 6:30 Networking Reception in the Expo (Commonwealth Hall)

6:30 – 7:30 Meetup Groups (Cityview)

7:30 Close of Day 2 

AFTERNOON | Concurrent Tracks

Waterfront 1

Track 1: Operationalizing Big Data to AI

Track Chair: Dan Vesset, Group Vice President, Analytics and Information Management, IDC

The mechanics of collecting the data, which algorithm is the best-fit, and even deriving insights are all important. But the greatest business value from big data, analytics, and AI comes from acting upon it. Decision-making requires modeling both the data and the people making the decision. Achieving desired outcomes and the ability to act upon the data matters most when operationalizing enterprise big data with AI.

  • Why data is not the new oil or currency; why insights alone do not make the business better.
  • How to create organizational value from data?
  • The benefits of operationalizing value through action

Click here for details

Cityview 1

Track 2: Emerging AI Technologies

Track Chair: David Schubmehl, Research Director, Cognitive/Artificial Intelligence Systems, IDC

There is no shortage of opinions on the potential for AI technologies in business. However, the current round of solutions is often viewed as expensive, proprietary, and complex to deploy and manage. When will AI solutions scale industry-wide? Is it possible to measure ROI for automation? How does AI rank against other corporate initiatives? The state of AI technology and its future is spoken here. From the development of neuromorphic chipsets to democratizing deep learning toolsets and from the next wave of machine vision, emotion, gestures, NLG, new algorithms, HPC and quantum computing will all be shared by the industry’s best and brightest.

  • Are there AI standards in development to unify current fragmentation of tools and methods?
  • How does current and impending regulation impact development and use of algorithms in the enterprise?

Click here for details

Waterfront 2

Track 3: AI & Real-Time IOT in Manufacturing

Track Chair: Les Yeamans, Founder and Executive Editor, RTInsignts

Reviewing data from thousands or millions of IoT sensors is beyond the capability of humans. Manufacturing is the largest and most advanced industry where AI is required in the deployment and operation of IoT applications. The addition of intelligence and processing on small devices at the edge raises additional challenges. This track features use cases from the manufacturing industry that sit between the intersection of AI and IOT.

Click here for details

Harborview 2

Track 4: AI in Healthcare

Track Chair: Lynne Dunbrack, Group Vice President, 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 3

Track 5: AI in Pharma

Track Chair: Alan Louie, Research Director, Life Sciences, 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 6: AI & ML Learning in Finance, Banking & Insurance

Track Chair: Rivka Gewirtz Little, Research Director, Global Payment Strategies, IDC

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 3

Track 7: Applied AI in Energy

Track Chair: Kevin Prouty, Group Vice President, Energy and Manufacturing Insights, IDC

Climate change and depletion of the Earth’s natural resources are frequent media headlines directly tied to demand for clean, affordable, and reliable energy. In parallel, gains in computing, memory, and storage have made artificial intelligence technologies more accessible. The intersection of AI and energy may hold the key to unlocking some of the greatest challenges our world faces. “Exponential technology is rapidly pushing electricity to reach the point of eventually becoming nearly free,” remarks Pascal Finette of Singularity University. Research into renewables and the use of simulations to creates digital twins are two examples of the accelerated value that machine learning brings to the energy sector. This track explores the tremendous promise possible today and in the near future.

  • How are large data sets being analyzed for identifying patterns, detecting anomalies, and making precise predictions?
  • Identify smart applications that can autonomously make accurate recommendations based on learning.
  • Where predictive analytics improves equipment O&M and predicts equipment downtime.

Click here for details


Track 8: AI for Retail & eCommerce

Track Chair:Jon Duke, Research Vice President, Retail Insights, IDC

In 2019, AI and machine learning technologies in retail have eclipsed the human analytical capability. Simple, rules-based pricing and competitive response have given way to agile, SaaS-delivered solutions optimized for immediate market conditions. By combining historical sales data with edge sensors and demand-shaping signals, retailers and ecommerce marketers utilize the massive scalability of machine learning to anticipate market events. Customer-facing applications powered by AI, such as recommendation functions and self-service checkout capabilities, enhance the customer experience.

  • Humans will continue partnering with AI to improve customer experience and business processes in the retail industry.
  • From supply chain planning and demand forecasting, to customer intelligence, AI will revolutionize ecommerce and the entire retail sector.
Click here for details


Harborview 1 

Track 9: Building Conversational Applications

Track Chair: William Meisel, PhD, TMA Associates

Automating the understanding of human text and speech revolutionizes connections with your customers and employees. Natural Language Processing (NLP) technology—interpreting speech or text— combined with Artificial intelligence algorithms is one of the most dynamic and rapidly developing areas of technology today. One key trend, for example, is “digital assistants” that converse with customers or employees to ease use of digital systems and services. A conversational platform using NLP allows a close intuitive connection with users, minimizing frustration and allowing efficient automation of many tasks. NLP technology also allows effective analysis of unstructured text or speech data.

  • The state of the underlying NLP and speech recognition technology available for commercial use
  • Case studies of deployments
  • Best practices for successful use of NLP technology
  • Creating a flexible conversation, rather than an overly structured and non-intuitive challenge.

Click here for details