Erick Brethenoux

Erick Brethenoux

Sr Director Analyst
Erick Brethenoux is a Research Director specializing in machine learning, artificial intelligence and applied cognitive computing. Mr. Brethenoux guides organizations on the strategic, organizational and technology aspects of using advanced analytics as a driving force of their growth. In particular, his research focuses on the deployment of machine learning insights through integration with advanced analytics solutions, next-generation, decision-making systems, cognitive computing solutions (including advanced customer analytics) and man-machine collaboration.
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Tuesday, 12 November, 2019 04:15 PM|Tuesday, 12 November, 2019 05:00 PM
Talent Futures: How AI Will Impact Jobs and Your Workforce

By 2020, AI becomes a positive net job motivator, creating more jobs than it destroys. As AI evolves and matures, new jobs and new ways of working will emerge. In this session, we will explore the future of work and how leaders should support their organizations as they navigate the transition to an AI-enabled workforce.

Wednesday, 13 November, 2019 10:30 AM|Wednesday, 13 November, 2019 11:15 AM
Five Steps to Practically Implement AI Techniques and Deliver Real Business Impacts

Moving from "I want to use AI" to a tactical approach aimed at practically and sustainably solving business problems, does not require super-powers. AI skills and a proper set of data are second order considerations when they should be front and center. Organizational issues should come after a rigorous business cases selection process. We are introducing a formula to facilitate the pragmatic introduction of AI techniques within organizations.

Thursday, 14 November, 2019 02:15 PM|Thursday, 14 November, 2019 03:00 PM
Operationalizing Machine Learning and Data Science Projects: From Academics to Economics

The democratization of machine learning and the popularity of open sources languages are facilitating the proliferation of ML models. However, as analytical assets are being deployed across organizations, the scalability of their performance and integrity (along with their economic value) is in question. Organizations need to establish data science operational strategies to scale and systematically monetize their data science efforts.

Hear it first at Gartner IT Symposium/Xpo™