5 Key Trends 2024 - Shaping the Future of AI and Data Science @ MIT

?

Artificial Intelligence (AI) and data science took center stage in 2023, largely due to the surge in generative AI. As we step into 2024, industry leaders are anticipating key trends that will shape the landscape. Three recent surveys involving over 500 senior executives shed light on the priorities and challenges faced by organizations in the realm of AI and data science.

?

1. Generative AI Struggles to Deliver Value:

Generative AI has captured significant attention, with 80% of AWS survey respondents believing it will transform their organizations. However, despite high excitement, the surveys indicate that the economic value is yet to be fully realized. Only a small percentage of companies have moved beyond experimentation, and production deployments will require substantial investment, organizational change, and a focus on data strategy.

Note: Lets talk if you are looking into Generative AI to add value in your business.

?

2. Data Science Shifts to Industrialization:

Data science is evolving from an artisanal activity to an industrialized process. Organizations are investing in platforms, processes, and methodologies, including machine learning operations (MLOps) systems, to increase productivity and deployment rates. Automation, especially through automated machine learning tools, is playing a crucial role in enhancing data science productivity.

?

3. Dominance of Two Versions of Data Products:

Data products, which package data, analytics, and AI into software offerings, are gaining prominence. Two views on data products emerge – one including analytics and AI capabilities, and another treating them as separate entities. Clarity in defining and discussing data products is crucial to avoid confusion in product development.

?

4. Diminished Stardom of Data Scientists:

The allure of data scientists, once considered "unicorns" with the "sexiest job of the 21st century," is diminishing. The rise of alternative roles, such as data engineers, machine learning engineers, translators, and data product managers, is reshaping the landscape. Citizen data science, facilitated by automated machine learning tools, is reducing the exclusive demand for professional data scientists.

?

5. Integration of Data, Analytics, and AI Leadership:

Organizations are streamlining their technology and data leadership roles, moving away from standalone chief data and analytics officers. The functions previously performed by these roles are being absorbed by a broader set of technology, data, and digital transformation functions managed by a "supertech leader." Collaboration among tech-oriented leaders within organizations is identified as a key challenge.

?

Conclusion:

As we progress through 2024, these trends highlight the ongoing evolution and maturation of AI and data science. While generative AI holds promise, the industry must focus on delivering tangible value. The shift to industrialized data science, the emergence of two versions of data products, the changing role of data scientists, and the integration of leadership functions are all indicative of a dynamic and transformative year ahead. Organizations must stay agile, invest wisely, and adapt to these evolving trends to harness the full potential of AI and data science.

Note: Lets talk if you are looking into Generative AI to add value in your business.