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Marcus Bernardi
Head of AI & Data
Daki
Speaker Topics
- AI, Data and Analytics
- AI Strategy and Business Alignment
Speaker Bio
Portuguese:
Marcus Bernardi é Head de AI e Data na Daki, com trajetória em dados, analytics, inteligência artificial e transformação de negócios em empresas de varejo, tecnologia e delivery. Há um ano, vem liderando projetos de IA aplicados a dados, operação e tomada de decisão, conectando novas tecnologias a problemas reais de negócio. Ao longo da carreira, liderou a construção de plataformas de dados, camadas analíticas, modelos de decisão self-service e times multidisciplinares em companhias como Daki e Carrefour Brasil. Seu trabalho combina visão executiva, engenharia de dados, analytics aplicado e gestão de equipes, sempre com foco em aproximar tecnologia das áreas de negócio e transformar dados em decisões práticas.
ENG:
Marcus Bernardi is Head of AI and Data at Daki, with a background in data, analytics, artificial intelligence, and business transformation in retail, technology, and delivery companies. For the past year, he has been leading AI projects applied to data, operations, and decision-making, connecting new technologies to real business problems.
Throughout his career, he has led the development of data platforms, analytical layers, self-service decision models, and multidisciplinary teams at companies such as Daki and Carrefour Brazil. His work combines executive vision, data engineering, applied analytics, and team management, always with a focus on bringing technology closer to business areas and turning data into practical decisions.
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Marcus Bernardi é Head de AI e Data na Daki, com trajetória em dados, analytics, inteligência artificial e transformação de negócios em empresas de varejo, tecnologia e delivery. Há um ano, vem liderando projetos de IA aplicados a dados, operação e tomada de decisão, conectando novas tecnologias a problemas reais de negócio. Ao longo da carreira, liderou a construção de plataformas de dados, camadas analíticas, modelos de decisão self-service e times multidisciplinares em companhias como Daki e Carrefour Brasil. Seu trabalho combina visão executiva, engenharia de dados, analytics aplicado e gestão de equipes, sempre com foco em aproximar tecnologia das áreas de negócio e transformar dados em decisões práticas.
ENG:
Marcus Bernardi is Head of AI and Data at Daki, with a background in data, analytics, artificial intelligence, and business transformation in retail, technology, and delivery companies. For the past year, he has been leading AI projects applied to data, operations, and decision-making, connecting new technologies to real business problems.
Throughout his career, he has led the development of data platforms, analytical layers, self-service decision models, and multidisciplinary teams at companies such as Daki and Carrefour Brazil. His work combines executive vision, data engineering, applied analytics, and team management, always with a focus on bringing technology closer to business areas and turning data into practical decisions.
Session
Wednesday, 23 September, 2026 02:45 PM - 03:15 PM BRT
Executive Story Daki: From AI Champions to “Data for All”
Marcus Bernardi,
Head of AI & Data, Daki
In December 2025, Daki had a solid AI plan: to train AI Champions in every department, using automation tools and a single model as the internal self-service AI infrastructure. The plan already had nine projects delivered and four more underway. In 60 days, the company decided to abandon this approach. The consolidation of open protocols for integrating generative models and technical parity among leading AI providers changed the equation. Instead of training people to operate a tool, the decision was to build a curated semantic layer and connect models directly to company data — no tickets, no dashboards, no queues. In eight weeks, adoption went from 0% to 82% among active users in this flow. The company shut down its BI tool and now runs eight agents in production, with use cases such as fiscal classification of incoming invoices and automated customer service, all on the same semantic substrate, model- and cloud-agnostic. In this session, discover the honest journey of this shift: what survived from the original plan, what had to be eliminated, how the change was justified internally, and lessons learned about culture, governance, and technology choices. Also, get practical recommendations for CIOs at three different levels of AI maturity.
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