Join us in Boston!

Harness the momentum of AI to create a better today, tomorrow, and beyond.


The Fortune 1000 are planning to increase their AI and Machine Learning investments in 2022 and beyond across all industries and sectors. Rapid AI advances are enabling supply chain efficiency, capital markets agility, energy resilience, marketing performance, reshaping the pharmaceutical value chain, and triggering advances in medical treatments.


AI predictive analytics and decision-making support will transform entire industries and generate new, more agile entrants changing the competitive landscape. However, success in harnessing AI and Machine Learning is a balancing act between making the right technological infrastructure investments, identifying impactful use cases, delivering strong business ROI, and evolving organizational culture.


Join Slalom, AWS, Databricks, and Tableau for a breakfast event with our AI and business experts, where you will gain insights on how to get your organization from Now to Next, no matter where you are on the AI maturity curve today. The sessions are designed to provide you with practical frameworks based on real-world examples to inspire you to get started on your AI journey or how to accelerate the benefits and scaling of your existing AI initiatives.


Date: Tuesday, May 10, 2022
Time: 8:00 a.m.-12:00 p.m. ET
Location: State Room
60 State Street
33rd Floor
Boston, MA 02109



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Additional event information

COVID requirements:

To attend the event, you must be fully vaccinated and obtain a CLEAR Health Pass within 12 hours of the event. CLEAR provides secure, digital proof of COVID-related health insights via a free mobile app. Learn more about CLEAR here. Local guidelines regarding masks will be enforced during the event. 


See the main event page to find other city registration pages. 

Meet the speakers

Tony Ko is the Head of Slalom's Global Artificial Intelligence. He is passionate about lowering the barrier of entry to emerging technologies, such as AI, to all organizations, team members and the general public. Tony works with executives and innovation teams to responsibly realize the promise of AI as well as with world leaders focused on making higher AI education more accessible to diverse leaders of the future. His team is dedicated to leveraging cutting-edge technologies and techniques (AI, Machine Learning, Cloud Platforms) to make a positive impact in the world.

Bob Galla has spent his career in data and analytics guiding customers towards providing actionable, contextual insights to their users. Since joining Salesforce in 2015, he has specialized in operationalizing AI driven insights for Salesforce customers to enable every user to make better decisions. As a Distinguished Technical Architect, he focuses on harnessing the value of ethical AI to improve business processes. 

Doug brings 20+ years of helping enterprises from all industries across the globe realize business value from their application of innovative technology. He’s held go-to-market executive roles in high-growth technology companies helping them to scale from $0 to more than $2B in annual revenues. Keys to his success include connecting technical strategy to business strategy, projecting and realizing value in a continuous fashion, and assessing maturity to accelerate adoption and business outcome realization. Over the past 10 years he has personally studied more than 500 organizations’ use of technology and their realization of value. Today, he leads the Value Acceleration team globally at Databricks which includes the Business Value Consulting, Strategic Customer, and Executive Engagement programs. The team’s mission is to help customers rapidly identify, quantify, and realize business value from leveraging the Databricks platform. 

Mike Buonocore leads a team of Solutions Architects that focuses on Artificial Intelligence and Machine Learning technologies at AWS.  Mike’s team supports their customers’ AI/ML adoption journeys, from those just starting to develop a data science or machine learning capability, to those with sophisticated production workloads. He has been working with machine learning technologies at Amazon for the last 4 years and brings more than 10 years of experience leading teams in technology companies.