Five Trends in AI and Data Science for 2025

Carolyn Geason-Beissel/MIT SMR | Getty Images This is the time of year for predictions and trend analyses, and as data science and artificial intelligence become increasingly important to the global economy, it’s vital that leaders watch emerging AI trends. N…
Prof. Lezlie Schultz · 4 days ago · 2 minutes read


AI Trends to Watch in 2025

1. The Promise and Perils of Agentic AI

Agentic AI, capable of performing tasks independently, is poised to be a major trend in 2025. While some hype surrounds it, experts caution that it's unlikely to have a significant impact on the workforce in the near future. However, it's expected to advance in specific tasks, such as assisting with internal processes or content creation.

2. Measuring the Value of Generative AI

While generative AI has garnered excitement, its economic value remains unproven. Many businesses claim productivity gains from these tools, but few are actually measuring their impact. Companies need to implement controlled experiments and measure content quality to fully understand the benefits of generative AI.

3. The Reality of Data-Driven Culture

Despite initial optimism, our recent survey shows a slight decline in organizations claiming to have created a data- and AI-driven culture. Generative AI alone cannot overcome cultural and change management challenges that hinder its implementation. Cultural transformation requires sustained effort and a wider adoption of data-driven practices.

4. Resurgence of Unstructured Data

Generative AI has sparked renewed interest in unstructured data, which comprises a large portion of organizational data. To harness its potential, organizations need to organize, tag, and load these documents into AI systems. While this process remains human-intensive, its benefits include enhanced knowledge sharing within organizations.

5. The Ongoing Struggle for Data and AI Leadership

Despite increasing investment in data and AI, data leadership remains a fledgling function. While the roles of chief data officer (CDO) and chief AI officer (CAIO) are becoming more prevalent, their responsibilities andreporting structures vary widely. The demand for strong data and AI leadership will continue to grow, but the optimal organizational structure remains unclear.

Expert Insights

Thomas H. Davenport believes CDOs should have a clear business focus and report directly to senior leaders. Randy Bean, however, advocates for a "supertech leader" role to oversee all technology functions, including data and AI.