Navigating Data Strategy in the AI Era: Insights from Pioneers

In an era increasingly driven by AI, data leaders across industries are seeking guidance on how to navigate the changing data landscape. A recent webinar, “Data Strategies for the AI Era,” provided valuable insights into how organizations can leverage data to drive AI innovation and organizational efficiency. During the conversation with Razi Raziuddin, Youssef Idelcaid from Genentech shared his experiences and strategies for success in the AI-driven landscape.

The Critical Role of Data in AI Implementation

Youssef Idelcaid, Head of Data Science for Commercial, Medical Affairs, and Government Affairs at Genentech, emphasized the importance of data quality, trust in AI systems, and robust data governance as the foundation for successful AI implementation. He highlighted that high-quality data is vital for training AI models, ensuring their accuracy, reliability, and explainability.

“High-quality data leads to a better outcome,” Youssef shared, underlining how the performance of AI models is directly impacted by the quality of the data upon which they are trained.

Trustworthiness in AI systems, contingent on data quality, is essential for stakeholder confidence, which is fundamental for AI solutions’ wide adoption and effectiveness.

“Users or stakeholders must have that confidence in the data… Trust in AI systems is also contingent on the data quality and its underlying infrastructure,” he explained, noting the importance of both inputs and outputs in building reliable AI systems.

Furthermore, Youssef stressed the significance of data governance:

“We all talk about governance. I think sometimes we succeed, sometimes we fail, but I think to really make the AI use cases successful, you need to pay attention to that. The robustness of your governance strategy is essential to managing your data assets.”

Merging Traditional Data Management with AI

Razi Raziuddin, co-founder and CEO of Featurebyte, addressed how traditional data management methods and tools are inadequate for advanced AI pipelines. He suggested that generative AI and tools like Featurebyte could significantly accelerate and enhance AI data preparation and deployment. He emphasized the importance of  creating efficient and cohesive data practices by combining tabular data management with unstructured data handling capabilities.

“SQL…it’s the cockroach of data management. It never dies,” said Raziuddin, advocating for the enduring value of SQL while also highlighting the importance of integrating new AI technologies to keep data management practices current and dynamic.

Data Science Skills in the AI Era

The conversation also touched on the skills required for data scientists to thrive amid the rapid evolution of AI. Beyond technical competencies, the speakers highlighted the need for adaptability, continuous learning, and the ability to tell compelling stories with data. Connecting technical outcomes with business objectives and stakeholder needs is increasingly important for data professionals.

Youssef remarked on the necessity for data scientists to evolve their approach, highlighting two important skills data scientists should sharpen: “Telling stories…we should be able to articulate what we do, why we do it, and how we do it. I would also say the ability to accept failure…I think that’s very important because we as practitioners often don’t accept when a business rejects our outcome, right? You come with your model;  it’s fancy, it’s beautiful, it’s accurate, but it doesn’t make any business sense.”

The Future of AI in Healthcare and Beyond

Looking ahead, Razi and Youssef explored potential sectors set for significant AI disruption, with healthcare and pharmaceuticals at the forefront. From drug discovery and clinical trials to commercial strategies, AI and machine learning technologies are expected to transform traditional practices. This transformation includes streamlining processes, improving patient outcomes, and driving efficiencies across operations.

Listen to the full conversation between Razi and Youssef by downloading the on-demand webinar “Data Strategies for the AI Era.”