Trust: Hard to build, easy to break

As more organizations move beyond experimentation to full-scale AI projects, they recognize there’s more to successful implementations than simply having the right datasets, AI models and scalability. Increasingly, dimensions of trust, including fairness, robustness and explainability, are essential to ensure confidence in AI outcomes.

Attend this keynote session to hear Ritika Gunnar, Vice President of IBM Data and AI, and David Cox, Director of MIT-IBM Watson AI Lab with IBM Research®, discuss how and why IBM is pioneering AI solutions people can trust.

Ritika Gunnar
Vice President, Data and AI, IBM

David Cox
Director, MIT-IBM Watson AI Lab, IBM Research AI, IBM

Journey to AI

How trusted AI helps you gain competitive advantage

As companies embark on their AI journey, privacy and algorithmic bias challenges can erode trust and slow progress.

Join Forrester analyst Srividya Sridharan, IBM executive Deborah Leff, and Woman Leader in AI honoree Kelly Combs from KPMG to find out how leaders in financial services and other industries are addressing this problem.

Srividya Sridharan
VP, Research Director Serving Customer Insights Professionals, Forrester

Deborah Leff
Global Leader and Industry CTO, Data Science and AI Elite Team, Distribution, IBM

Kelly Combs
Director Advisory, Emerging Technology Risk Services, KPMG LLP


Breaking open the “black box” of AI: A roundtable discussion

For organizations to scale AI across the entire businesses, they need to break open the ‘black box’ of AI. It is critical to ensure AI decisions are fully traceable – enabling enterprises to audit the lineage of their AI models and the associated training data.

Join this roundtable discussion to hear IDC analyst, Ritu Jyoti, General Manager of IBM Data and AI, Daniel Hernandez, and Vice President of IBM BigData and Cognitive Systems, Paul Zikopoulos, weigh in on why trust and transparency are essential to AI success.

Daniel Hernandez
General Manager, Data and AI, IBM

Paul Zikopoulos
Vice President of BigData and Cognitive Systems, IBM

Ritu Jyoti
Program Vice President, Artificial Intelligence Research, Global AI Research Lead, IDC

Betsy Schaefer
Director, Watson Marketing, IBM

Designing for trust in your AI experiences

AI gives us exciting new ways to solve problems, but its implementation invites questions: How do I know when AI is being used? How confident can I be in the recommendations it’s making? How do I know I can I trust this company with my data?

Join us for a session where we’ll discuss how IBM empowers users with the insights they need to feel confident about the recommendations Watson™ makes.

Jennifer Sukis
Director of Design, AI Transformation, IBM

Mary Kim
UX Designer, IBM

Robin Langerak
PhD, User Researcher, IBM

Lisa Chen
Design Strategist, Data and AI, IBM

Dillon Eversman
UX Designer, IBM


Cloud modernization

How Wunderman Thompson built a COVID-19 dashboard

In this unprecedented climate, many companies are struggling to adjust to a ‘new normal’. Global digital agency Wunderman Thompson, specializing in data-driven human insights to help clients devise marketing, media and advertising strategies, created a COVID-19 dashboard to help brands navigate these uncertain times with AI-powered health and economic data. Utilizing IBM Cloud Pak® for Data, IBM’s market-leading Data and AI platform, the dashboard and its Predictive Recovery Index look forward into recovery timing for communities to help them determine a safe pace for reopening.

Join IBM and Wunderman Thompson executives to learn more about this COVID-19 dashboard and its capabilities. Discover ways to plan your personalized consumer insights within your defined markets using IBM Cloud Pak for Data to solve your most complex business challenges for today’s changing world.

David Bertram-Shaw
Director of Data Science, Wunderman Thompson Data

Sheetal Rishi
Director, Cloud & AI, WPP Integrated Account, IBM

The most trusted cloud for enterprise AI

When most people think "trusted AI" they focus on the data — accessing, cleansing and cataloging the information used to fuel their AI models and drive accurate insights. What we've learned, however, based on our 30,000 AI engagements, is that trust needs to extend beyond data preparation. It needs to be woven into the multiple threads of your business. For instance, trust plays an important role in the partner you choose to help you deliver your data and AI capabilities.

Join IBM and IDC as we discuss the market realities of trusted data and AI, the explosion of as-a-Service deployment options, and how that ties to the latest development in our IBM Cloud Pak for Data family.

Chandana Gopal
Research Director, Business Analytics, IDC

Stephanie Walter
Program Director, Data and AI Offering Management, IBM

A partnership advancing innovation in a trusted environment

The IBM and Anaconda partnership scales and advances open-source data science innovation in a trusted environment.

Join IBM and Anaconda leaders to learn how the integration of Anaconda’s Team Edition into IBM Cloud Pak for Data provides a managed, curated repository of open-source tools for use by data scientists, helping to reduce technical, operational and legal obstacles for enterprise adoption of open-source innovation.

Russ Milano
Global Sales Leader, Watson Studio, Data Science and AI, IBM

Brian Churchin
Senior Director, Sales, Anaconda

Cloud Data Lake Security. Enabled.

Cloud Data Lakes are the foundation of a modern data and AI platform, empowering companies to represent their structured and unstructured data in a uniform and consumable way. This data infrastructure takes advantage of a diverse set of analytics services as well as the elasticity, management operations, and built-in security of the cloud.

In this session, Riz Amanuddin and Torsten Steinbach will provide an overview of how IBM Cloud Data Lakes empower teams to securely ingest, store, organize, and analyze large volumes of diverse, full fidelity data. We will review IBM Cloud® security models and advanced security services that help to ensure comprehensive management across data lakes with authorized access and data governance.

Riz Amanuddin
Program Director, Offering Management, Cloud Object Storage & Data Services, IBM

Torsten Steinbach
STSM, Data Services & SQL Service, IBM Cloud, IBM

Data modernization

AI needs trusted data panel

Join us for an engaging panel discussion with Michelle Y. Reid, Worldwide Watson Channels Marketing Leader, along with IBM Data and AI Data Operations and Hybrid Data Management Business Partners, as they focus on how to build trust with your clients. In this session, our partners will share emerging AI trends and current use cases.

Michelle Y. Reid
Worldwide Watson Channels Marketing Leader, IBM

Robb Sinclair
Vice President, Analytics, Converge Technology Solutions Corp.

Brad Miller
Practice Director, Information and Analytics, Mainline Information Systems


Data-centric security for hybrid cloud data lakes

Data-centric security is vital for security configurations to align with business objectives; namely, to protect data and meet the associated regulatory compliance and business safeguards. Storage systems must be designed with enterprise protection, with a real-time data catalog to help identify data anomalies and security issues.

David Wohlford, WW AI and Data Senior Product Marketing Manager at IBM, will explain how IBM Storage for Data and AI helps build and scale secure data lakes for AI.

David Wohlford
Worldwide AI and Data Sr. Product Marketing Manager, IBM

Trust in AI: It starts with the data foundation

Successful AI adoption is predicated on building trust with all stakeholders. The starting point is a data management strategy that incorporates security, precision, accountability, and flexibility, with attributes such as data encryption, availability, container recovery, and multi-modal data management.

Join this session to hear Noel Yuhanna, VP and Principal Analyst at Forrester, and Nidhi Bhatnagar, Offering Manager, at IBM, discuss why trust in AI starts with a strong data foundation.

Nidhi Bhatnagar
Offering Manager, IBM Cloud & Cognitive Software, IBM

Noel Yuhanna
VP, Principal Analyst, Forrester

Embracing mainframe applications and data when trust is a must

Many organizations, specifically in heavily-regulated industries, are subject to strict regulations like data security and data manipulation. Complying with changing regulations is not an easy task. That’s why IBM recently announced Db2 Data Gate, a new solution that effectively brings Db2® for z/OS® data on IBM Z® to IBM Cloud Pak for Data, helping organizations keep the data synchronized between the system of record and target.

Join this session to hear Finanz Informatik share the use cases and pain points they encountered building custom solutions to address this explosive growth in applications that require read-only access to mainframe data, from which the idea for Db2 Data Gate was born.

Namik Hrle
IBM Fellow, CTO, Data and AI, IBM


Know, trust, and use your data with IBM DataOps

The pace of business transformation relies on delivering business-ready data, and 65% of enterprises demand their CIOs bring governance to data and AI to drive trusted business outcomes.

Join the panel conversation with Thad Vorozilchak, VP of Information Architecture at IBM, as they discuss how a DataOps practice delivers trusted, business-ready data driving business agility, speed, and trust.

Thad Vorozilchak
Vice President, Information Architecture, Data and AI, IBM

Five steps to leverage trusted data for data modernization

Cloud computing is critical to the flexibility, speed, and cost savings organizations need. But if data management and data integration lags behind, much of the cloud’s potential will be lost. Organizations need to modernize data movement, integration and governance to shorten the time it takes to realize the operational and cost benefits from the cloud.

Join this session to learn how your organization can modernize data integration and governance for multiple cloud platforms and continuing on-premises systems. David Stodder from TDWI, along with Beate Porst from IBM, will discuss key topics such as ‘design once - run anywhere’ principles, governance, data catalogs, and more concepts that are vital to a holistic approach to data integration.

David Stodder
Senior Director of Research for BI, TDWI

Beate Porst
Program Director Offering Management IBM Data and AI

Bharath Chari
WW Product Portfolio Marketing Manager, IBM Data Integration and Information Server

Data science and AI

Trust Watson to expedite insurance claims payments

In a competitive market, it is imperative to constantly review your processes and try to optimize your business. Join this session to discover why Banco Bradesco, the biggest insurance company in Brazil, trust IBM Watson® Machine Learning to expedite their insurance claims payments through analytical models and insights.

Glaucio Calixto Joanico
IT Superintendent, Life Insurance and Pensions, Banco Bradesco

Leonardo P. Frollini
Executive Software Client Architect, Banco Bradesco

AutoAI: The trusted brain behind faster and smarter machine learning

As organizations hurry to enhance and modernize business with AI, one thing is clear: simply acquiring more knowledge is no longer sufficient. Your business needs the ability to identify trends and make predictions, trust AI models, and speed experimentation time from weeks and months to minutes and hours. AutoAI is helping companies speed model development by up to 80%, enabling data scientists to make higher-value contributions.

How well does AutoAI live up to its promise? Join Christopher Penn, Co-founder and Chief Data Scientist at for an expert’s view on how you can automate the AI lifecycle for better outcomes.

Christopher Penn
Co-Founder & Chief Data Scientist,

Automating the AI lifecycle for trust and value

AI can help organizations accelerate discovery, adjust how they interact with the market, reallocate resources, and gain efficiencies. However, AI can also bring complications for brand trust. 

Join this expert panel session with Zain Nasrullah, Model Learning Validator, Royal Bank of Canada, Mike Hind, Distinguished Research Staff Member at IBM Research, and Emma Tucker, Offering Manager at IBM, to learn about how automating the AI lifecycle can enable a foundation of trust and value for your organization.

Zain Nasrullah
Model Learning Validator, Royal Bank of Canada

Mike Hind
Distinguished Research Staff Member, IBM Research AI, IBM

Emma Tucker
Offering Manager, Watson Knowledge Catalog, IBM

Karen Madera
Portfolio Product Marketing Manager, DataOps and Watson Knowledge Catalog, IBM

AI for customer service

Inside the most effective ways regulated domains employ NLP

If you’ve heard of AI, you’ve heard of natural language processing (NLP). A trusted NLP model is a critical component of any thoughtful AI application — why? Enterprises, especially in highly regulated or data intense industries, have always needed a trusted source of data truth, but it’s even more important than ever when applying AI. How did your AI reach its decision? Do you trust it?

Join IBM experts and leaders in risk and compliance and law to understand how they are using NLP to accelerate processes, analyze data more efficiently, or even provide smarter recommendations. For example, how one organization uses NLP to index, process and translate nearly 2 million laws from 100 countries. They’ll share insights on the importance of trust and transparency when it comes to decisions and how IBM’s NLP and NLU capabilities empower them to break down their data and harvest new insights.

How voice capabilities create a trusted, accurate, and efficient customer experience

Providing high quality customer service in call centers is a challenge. The need to grow call volumes, increase end-user expectations, and ensure customer service is consistent across all channels.

In this session, we'll talk about how IBM Watson Assistant for Voice Interaction works as an AI assistant in your call center, and review the latest technologies that enable Watson Assistant to provide accurate and up-to-date information.

Brian Loveys
Offering Management, IBM Watson, IBM

How partners are embedding Watson within their workflows to build client trust in AI

To meet the needs of your customers, you must increasingly build trust. With Watson partners are embedding and integrating their business solutions with Watson to augment human intelligence. These capabilities provide employees with accurate information quickly so that they can better serve customers and engender more trust.

Wesley Chung, Director of Watson Strategic Partnerships, will talk to two of our top With Watson partners on how AI is allowing them to reimagine their business workflows with trust in mind.

Wesley Chung
Director of Watson Strategic Partnerships, IBM

Warren Hart
Global Practice Leader, DXC Technology

Denise Stokowski
Group VP, Platform Products, Gainsight

AI for risk and compliance

AI governance: connecting trust and risk

Financial institutions are increasingly dependent on models to help estimate risk, predict and measure qualitative information, create informed decision-making, and drive business outcomes. However, many business stakeholders, especially in regulated industries, do not trust AI. As the business environment becomes more complex, and as regulatory scrutiny increases, with new sanctions such as SR 11-7 guidance on model risk management in financial services, it has never been more crucial for all organizations to ensure their AI models are robust, fair, explainable and fit for purpose.

Join industry leaders, Brandon Purcell, Forrester analyst, and Ian Francis and Alex Jones from IBM, as they discuss how AI is helping firms automate the model development cycle and monitor and perform model risk assessments to help detect and correct AI model bias to ensure regulatory compliance and overall financial risk governance to meet business objectives.

Brandon Purcell
Principal Analyst Serving Customer Insights Professionals, Forrester

Ian Francis
Principal Solution Consultant, GRC, IBM

Alex Jones
Offering Manager, Watson OpenScale™, IBM

AI for financial operations

Trusted insights, confident decisions: AI-driven analytics

At a moment when there is little room for missteps and wasted time, it is critical to have analytics you can trust. A small error in a spreadsheet can lead to big disruptions caused by miscalculated sales forecasts, erroneously reported revenue, or an inaccurate view of inventory. IBM’s planning and analytics solutions help clients leverage automation and AI, allowing for more visibility and alignment while removing bias.

Join us for a panel discussion with Aberdeen Research and QueBIT to learn how clients are driving trust with solutions like IBM Planning Analytics and experiencing time savings of over 30 hours per week, while increasing accuracy by 10 percent.

Mike Lock
Senior Vice President of Research, Aberdeen

AG Tan
Senior Vice President, Strategy & Operations, QueBIT

Jason Tavoularis
Senior Offering Manager, Planning Analytics and Cognos®, IBM

Carol Samuel
Program Director, Planning Analytics and Cognos Marketing, IBM


Planning for change

Pivot to meet a new market reality with integrated planning, analytics and reporting

Every business needs a plan. But every business also needs a plan B, and even C. To ensure agility in an era of disruption, integrating the planning process across your business is the best way to streamline planning, budgeting, and forecasting. This collaborative approach creates a single source of truth and delivers confidence and agility to your planning process.

Join us for a panel discussion with IBM Business Partners Carpe Datum and eCapital to hear how their clients can leverage AI and automation in IBM Planning Analytics to drive results they can trust.

Erin Gabrielson
Program Director of the Data and AI Ecosystem & With Watson Marketing, IBM

John Martin
Managing Partner, Carpe Datum

Matt Fredrick
Partner, eCapital Advisors

Industry spotlight

Highmark Health's prediction and response in urgent and uncertain times

Highmark Health data scientists worked with IBM to build models to predict sepsis hospital admissions. Join the discussion with Highmark's Curren Katz, PhD, Director of Data Science R&D and IBM Data Science Elite's Brittany Bogle, PhD MPH to learn how Highmark is now applying their approach to the urgency of COVID-19.

Curren Katz
PhD, Director of Data Science R&D, Highmark Health

Brittany Bogle
PhD MPH, Senior Data Scientist & Healthcare Lead, IBM Data Science Elite Team, IBM

Ed Macko
Vice President of Industries and CTO of Healthcare, IBM

Trusting AI to prioritize care: iKure's telemedicine goes the distance

Join Sujay Santra, Founder and CEO, iKure, and IBM data scientists, who worked together to build and remove bias in models to identify high-risk cardiac patients by combining wearable data and historic patient data. Since their initial project, COVID-19 has become a top priority for this healthcare provider for rural and remote parts of India. Using the same process, iKure is working to predict and classify high-risk COVID-19 patients in their community, as well as explore ways to measure the impact of yoga and mindfulness for their cardiac care patients.

Sujay Santra
Founder and CEO, iKure

Julie Lockner
Executive Director, IBM Data and AI Offering Management, IBM