Editor of the Enterprise Architecture Professional Journal

Darryl Carr

An integration architecture thought leader and CITA-Professional

Brice Ominski

Founder and Managing Director, S2E Transformation Inc.

Whynde Kuehn

CEO and Founder,
Iasa Global

Paul Preiss
Executive in Residence,
DePaul University Innovation Lab
Roman Dumiak
Solution Architect,
Microsoft Services – Azure Cloud & AI
Ben Wright-Jones


24 hours of insightful presentations in a virtual meeting space. We are building the agenda which is subject to change – check back here often to see recent changes.  Click on the speaker names for their bio page and connection details.

All times are shown as US Central time (CST is UTC-06:00).


Founder & CEO, KYield

Fireside Chat: Enterprise AI Management Principles

KYield, Inc. just completed a scenario for the DoD in late Dec. that weave freshly minted 15 principles into the story – cybersecurity scenario in this case. A generic corp. version has since been delivered to majority of Fortune 100 CEOs.

In this fireside chat, we will discuss why organizations should adopt these 15 management principles in enterprise AI to be remain competitive.

A/Prof. Paul Cooper

A/prof. Health Informatics Management

Fireside Chat: Leadership – Is it still the weakest link in safely introducing Ai into healthcare in Australia?

This fireside chat will explore the best way to get the leadership aspects going in Australia that is necessary for AI to be more rapidly and safely introduced into healthcare (particularly aged care which is a very pressing need).

Somaieh Nikpoor

Research Advisor -AI/ML

Bias and Fairness in AI

Somaieh’s talk will cover the following points:

– What is an algorithmic bias and how it is introduced in the machine learning pipeline
– There are multiple sources for bias. It is essential to understand them when designing AI systems.
– What it means for an algorithm to be fair and how to measure fairness


Solution Architect, Microsoft Services – Azure Cloud & AI

Why You Need an AI Center of Excellence to Accelerate Innovation

Artificial intelligence presents many compelling opportunities, be it in healthcare, manufacturing, or education. Yet, there are many challenges and concerns spanning both technological implementation and responsible application of AI. Interest in the value of an AI Center of Excellence (COE) has grown as many organizations turn to intelligence-driven strategies.

In this session, we propose an AI center of excellence (COE) framework to accelerate innovation through ideation and experimentation whilst also enabling organizations to address their responsible and ethical uses (such as risk of harm, denial of consequential services, and infringement on rights). Using real implementation examples from around the globe, I will share AI Center of Excellence challenges and lessons learned (covering people, process and technology) to help you understand and leverage the business capability to accelerate and govern AI innovation.


Director of Product

Invest in Collaboration, Automate Insights, Prevent Extinction

Wildlife preservation is hard work, burdened with limited funds, disparate data sets, and heavy restrictions from universities, organizations, governments, and funders. Preservation of biodiversity, however, can’t wait. At Wild Me, we act as a neutral third party with a single goal: provide support by building conservation communities around shared platforms that leverage AI to reduce processing workload. We bring together those with data and expertise to accelerate discoveries and insights that can shape local and global policies to protect our shared home.


Partner Technology Strategist, Microsoft

Do No Harm – A Checklist for Responsible AI

The session will explain the guiding principles of Responsible AI and showcase demos of the tools and technology Microsoft offers to put these principles into action. This will be a detailed technical discussion with demos and is intended to be a L200-L300 session.


Seattle Director, Pacific Northwest National Laboratory

AI Accountability

A discussion of what algorithmic accountability in artificial intelligence (AI) is and why the potential for harm is so great yet the solutions are so complex. A discussion framework will be presented that addresses bias in AI data, models, and outcomes. Examples of each will be presented, followed by a high-level overview of how researchers and policy makers are addressing “accountability.” Several legislative efforts at regulation, including the federal Algorithmic Accountability Act of 2019 and California’s AB 13 will be examined.


The theme for our 8th July event is Artificial Intelligence: Today and TomorrowWe will explore the possibilities and challenges of artificial intelligence (AI) from multiple facets: business, government, technology, people, governance and ethics, society, and wellbeing. 

This event takes a practical look at AI today, through case studies that showcase how organizations are using artificial intelligence to build business value now.  

The event will also highlight essential perspectives on AI Tomorrow, to help us design and prepare for the future. 

This unique event will feature a broad spectrum of perspectives and voices, from business and government leaders to technology vendors and global thought leaders. 

Coinciding with this event is the BIL-T AI Case Study Awards, where we will select the top case studies to present at the event, and the winners will be announced during the event. 

Nominations are invited for the BIL-T Conference Series AI Case Study Award. This award recognises significant accomplishments in the use of Artificial Intelligence technologies, and is to be presented at the BIL-T Conference Series Artificial Intelligence: Today & Tomorrow event, held on July 8 & 9, 2021. 

To submit a case study: 

If you have a great case study that illustrates how your organization has leveraged artificial intelligence for business value, we’d love to hear from you! Describe your case study herealong with contact information for yourself and any other potential speakers. 

Case study submissions are due by Monday, 31 May 2021to be considered for the awards.  You will be notified of your selection to speak no later than Tuesday, 15 June 2021.   

AI Case Study Awards details

To submit an abstract to speak: 

If you feel your session will add value to our audience, please be as specific as possible when you send in your submission. Submission entries can be done here.

Deadline submission: May 31, 2021.
  • Case studies that illustrate how organizations have leveraged AI  
  • Envisioning the future: perspectives from business, government, specific industries, etc.  
  • Insights on the future from AI and analytics vendors 
  • The good, the bad, the ugly on usage scenarios such as facial recognition technology or autonomous vehicles 
  • AI governance and ethical considerations 
  • Insights from AI research or projects  
  • Human impacts and opportunities on individuals, society, and the work environment  
  • Architecting for AI 

Join us to explore Artificial Intelligence, where imagination and realization meet! Register Here


About MEGA International

Founded in 1991, MEGA is a global software company and recognized market leader for over ten years. MEGA has had demonstrated success implementing enterprise architecture solutions and use cases at over 2000 companies and has 340,000 users worldwide. Building upon the functionality of enterprise architecture, MEGA has enriched its solutions over the last few years by adding risk management, data governance, and data privacy solutions. Having all these solutions under one platform enables companies to connect these perspectives under one single source of truth. With this broader, connected view, companies get a better understanding of how their business works, uses technology, governs data, ultimately helping the company to realize transformation success. Get up and running quickly with open APIs, instant out-of-the-box reports, and customizable dashboards to share insights across your organization to make smarter decisions. –