Elias Baltassis
Partner & Director
Paris
Elias Baltassis specializes in artificial intelligence and data and analytics at Boston Consulting Group. He is a core member of the Technology Advantage practice and of BCG’s GAMMA team that focuses on analytics and data science.
Elias leads analytics and AI projects across many industries and functions, and regularly works in areas such as data strategy, data governance, and data regulation. He works with clients in several European countries and the US.
Elias has published numerous articles on these topics and is a regular speaker at leading AI industry events and conferences. He is also a lecturer at INSEAD on the topic “AI in Business.”
Elias has more than 20 years of experience in quantitative and data-driven topics. Prior to joining BCG, he was a founding member and managing director of Opera Solutions, a leading global pure-player in data and analytics. Prior to that, he was a Partner with Bain & Co.
Principles abound for socially responsible artificial intelligence. Here’s how to put them into action.
The better your data quality, the better you can solve problems, seize opportunities, and generate value. Here’s how to get that good data fast.
As companies accelerate efforts to become data-driven organizations, some are hitting bumps in the road, forcing them to slow down.
To win in the data race, companies need focused data structures, policies, and tools and a target operating model.
How well companies manage their use of consumers’ personal data can spell the difference between failing and flourishing.
The EU’s General Data Protection Regulation establishes new standards for handling customer data, increasing both the challenge and the rewards of proactively earning consumers’ trust.
Consumer distrust will cost you. But companies that establish best practices regarding data use can avoid brand damage and lost revenue—and capture the upside potential that comes with winning consumers’ trust.
Many companies have high hopes for big data but are developing initiatives and capabilities ad hoc. A new approach can sharpen a big data vision—and help make it a reality.
Data-driven transformation is becoming a matter of life and death in most industries, but initiatives often fail. Here’s how to make sure that yours succeeds.
Many companies don’t understand how consumers perceive new uses of data. In this slideshow, we explore the high cost of not taking these feelings into account.
