{"id":65830,"date":"2026-04-01T15:47:57","date_gmt":"2026-04-01T13:47:57","guid":{"rendered":"https:\/\/blog.docsity.com\/en\/?p=65830"},"modified":"2026-04-01T15:53:17","modified_gmt":"2026-04-01T13:53:17","slug":"escps-msc-in-business-analytics-ai-a-cross-interview-on-the-future-of-ai-for-business","status":"publish","type":"post","link":"https:\/\/blog.docsity.com\/en\/news-universities\/escps-msc-in-business-analytics-ai-a-cross-interview-on-the-future-of-ai-for-business\/","title":{"rendered":"ESCP\u2019s MSc in Business Analytics & AI: a Cross Interview on the Future of AI for Business"},"content":{"rendered":"\n

In a world where artificial intelligence is rapidly reshaping how companies make decisions, compete and grow, business education has to evolve just as quickly. That is exactly the direction ESCP Business School has taken with the recent evolution of one of its flagship programmes: the former MSc in Big Data and Business Analytics is now the MSc in Business Analytics & AI<\/em><\/strong>. But what does this change really mean? Looking at the perspectives of Lynn Farah – <\/strong>Associate Professor \/ Co-Director MSc in Business Analytics & AI at ESCP<\/em> –<\/strong>, Louis-David Benyayer – <\/strong>Associate Professor \/ AI Initiative Coordinator at ESCP<\/em> -,<\/strong> and Hao Zhong – <\/strong>Associate Professor \/ Co-Director Big Data and Business Analytics at ESCP<\/em> -, what emerges is not simply a renamed programme, but a sharper academic vision: one that places artificial intelligence at the centre of business transformation while maintaining a strong focus on analytics, decision-making and real-world impact.<\/p>\n\n\n\n

Why rename the programme now?<\/h4>\n\n\n\n

For Lynn Farah<\/strong>, the shift from Big Data to Business Analytics & AI is both timely and necessary. In her view, Big Data no longer reflects where the real value lies today. The focus has moved away from the sheer size of data and towards its utility: data is now the raw material powering AI models and machine learning systems, from predictive analytics to natural language processing. Farah also argues that integrating AI into management education is not a passing trend, but an essential evolution. In this sense, the new name reaffirms ESCP\u2019s ambition to remain at the forefront of AI for Business<\/strong> and to train leaders who can use AI not only as a technical tool, but as a driver of value creation.<\/p>\n\n\n\n

What makes the OpenAI partnership distinctive?<\/h4>\n\n\n\n

One of the programme\u2019s most notable developments is its partnership with OpenAI<\/strong>. According to Louis-David Benyayer, the value of this partnership goes well beyond access to tools like ChatGPT. The real difference lies in how generative AI is embedded into the learning experience itself. He explains that both students and faculty already use ChatGPT in course design and delivery. In some cases, professors have developed custom GPTs to provide round-the-clock support on course content; in others, they have created digital twins of managers so students can practise scenarios such as negotiation. <\/p>\n\n\n\n

Why does the collaboration with Hugging Face matter?<\/h4>\n\n\n\n

Benyayer <\/strong>also highlights the importance of the programme\u2019s collaboration with Hugging Face<\/strong>, one of the most influential platforms in the open-source AI ecosystem. For students, this means access to a vast collection of open datasets and models, helping them build both technical literacy and practical skills. At the same time, Hugging Face introduces them to a broader culture of knowledge creation and sharing. It is not only a platform for learning, but also a space where students can engage with the collaborative logic that increasingly shapes AI innovation.<\/p>\n\n\n\n

How has the curriculum evolved?<\/h4>\n\n\n\n

For Hao Zhong<\/strong>, the curriculum’s stronger emphasis on AI is reflected in new and updated modules that both adapt to how AI is transforming professional practice and bridge technical knowledge with managerial decision-making. One such updated module is Introduction to Data Analytics Coding (Python). Beyond teaching Python fundamentals, the course incorporates vibe coding – where developers describe their intent in natural language and let AI generate the code – so that students learn to collaborate effectively with AI coding assistants from day one. Another example is Data Science & AI for Business (with Dataiku). What makes this course especially relevant, he explains, is that it shows students how technical choices translate into business decisions. Concepts such as model thresholds are explored through real use cases like credit risk, where issues such as compliance and efficiency must be balanced. Together, these modules reflect the programme’s core ambition: training graduates who can both harness AI as a practical tool and bridge the gap between data science and strategic decision-making.<\/p>\n\n\n\n

Is the programme more practical than theoretical?<\/h4>\n\n\n\n

According to Lynn Farah<\/strong>, the programme remains grounded in theory and technical skills, but places a stronger emphasis on application. Unlike a traditional engineering curriculum, its focus is firmly on business analytics and applied value creation<\/strong>. That means more hands-on learning, real-world use cases and practical problem-solving. Students are encouraged to learn by doing and to understand how data and AI can generate strategic value in business settings. Farah also points to the programme\u2019s strong industry links, with several courses built in close collaboration with leading companies in the market and involving guest speakers. One highlight is the yearly Hackathon which provides our students with opportunities to tackle real-world problems across different industries through the power of data analytics.\u00a0<\/p>\n\n\n\n

What kinds of careers is the MSc preparing students for?<\/h4>\n\n\n\n

Zhong makes it clear that the refreshed MSc is no longer aimed only at future Data Scientists. Instead, it prepares students for a broader set of roles where AI acts as a strategic capability across business functions. Graduates may still pursue technical paths such as Machine Learning Engineer<\/strong> or Data Scientist<\/strong>, but the programme is also aligned with roles such as AI Strategy Consultant, Digital Transformation Consultant, AI Product Manager, AI Solutions Architect<\/strong> and AI Governance & Ethics Officer<\/strong>. Just as importantly, it is relevant for students entering more traditional business careers in consulting, finance or marketing, provided they can bring a strong AI perspective to those roles.<\/p>\n\n\n\n

Who is the ideal student for this new version of the programme?<\/h4>\n\n\n\n

In the joint vision shared by Lynn Farah<\/strong> and Hao Zhong<\/strong>, the ideal candidate is not defined by a purely technical background. What matters most is the potential to become a hybrid profile<\/strong>: someone able to understand advanced analytical methods and apply them in business contexts. They describe the best-fit students as curious, adaptable and internationally minded, with strong communication skills and a genuine interest in the intersection of business and technology. Above all, they are looking for candidates who want to translate insights into business value. A technical background is not mandatory, as the programme is designed to help students build the skills they need along the way.<\/p>\n\n\n\n

Are you ready to explore the future of business analytics and AI?<\/em><\/strong> <\/strong>Discover ESCP\u2019s MSc in Business Analytics & AI<\/a> and learn how this programme can help you build the skills, mindset and experience needed to thrive in an AI-driven business world.<\/p>\n","protected":false},"excerpt":{"rendered":"

In a world where artificial intelligence is rapidly reshaping how companies make decisions, compete and grow, business education has to evolve just as quickly. 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