The evolving role of data scientists: why business leaders should care

Artificial intelligence and machine learning are transforming decision making in grocery retail and many other industries. As CPGs and retailers invest more in AI to optimize supply chains, forecast demand, scale marketing campaigns and develop innovative products, data scientists are poised to take on more strategic responsibilities. Here's why business leaders should take note. 

The democratization of insights

From mobile devices to web traffic, point-of-sale systems to industrial IoT sensors, data is being generated at greater speeds and volumes. With the advent of large language models (LLMs), interactive virtual assistants powered by LLMs are enabling business teams without a technical background to translate much of the data that is being generated into insights. In a shift to democratized insights, business teams are increasingly empowered to uncover emerging patterns, trends and other insights from data without a data science background.

Will data scientists be replaced by AI?

The democratization of insights powered by AI has enormous implications for data scientists’ roles. Although AI will transform certain aspects of the profession, it is more likely to enhance rather than supplant the critical human role of a data scientist. By 2026, 20% of top data science teams will have rebranded as cognitive science or science consultancies, increasing diversity in staff skills by 800%, predicts Gartner.     Essentially, data scientists will become the bridge between technical AI systems and actual business implementation – so investing talent and resources in upstream data assets and processes continues to be critical. While business teams are able to surface more insights with the help of AI tools, the depth of analysis and complexity of use cases still require an expert.     Data scientists are needed to oversee and guide the AI, help translate the outputs into actionable decisions and ensure the systems deliver continuous value. This makes them invaluable strategic advisors as companies navigate the AI era.     Here are two examples of higher-value work that data scientists could provide: 

• Guidance on AI investment decisions  With nearly limitless possibilities around using AI, having strategic advisors who understand both the business context and AI capabilities is essential for making smart investment decisions. Data scientists can provide recommendations on where AI can create the most business value while balancing what’s feasible now and in the near future.   

• Responsible AI perspectives  Having an ethical checkpoint is crucial as algorithms drive decisions in areas like pricing, promotions and marketplace recommendations. AI advisors can provide guidance on ensuring the algorithms are fair and transparent. A responsible AI perspective will be invaluable for maintaining consumer and associate trust.   

The future data scientist needs both hard technical skills and soft skills like communication to thrive in a data and AI-driven world. With the rise of AI tools democratizing data insights, adaptive data scientists will move up the value chain, delivering value through cross-collaborations instead of just uncovering insights. Business leaders who invest in this skills evolution will gain an early advantage.     Learn more about AI’s impact on associates and customers in our ebook, “5 ways data science and AI are shaping the future of grocery shopping.”