Five Trends in Data Science and Machine Learning According to Gartner

Gartner points to data in the cloud, data ecosystems, edge AI, accountable AI, data-centric AI and continued investment in AI.

Data science and machine learning continue to evolve, driven by advances in generative artificial intelligence, and Gartner has identified five key trends that will shape the future of the field.

These trends reflect a shift from predictive models to a more democratised and dynamic approach in the data analytics discipline.

  • Data Ecosystems in the Cloud: The first trend relates to cloud data ecosystems, which are evolving from standalone solutions or manual integrations to cloud-native solutions. Gartner predicts that by 2024, 50% of cloud system deployments will be complete data ecosystems rather than standalone solutions. Organisations should evaluate these ecosystems based on their ability to solve distributed data challenges and their integration with external data sources.
  • Edge AI: The second trend focuses on Edge AI, which involves processing data where it is generated, enabling real-time insights and compliance with strict privacy requirements. Gartner predicts that more than 55% of deep neural network data analytics will be performed at the point of capture in edge systems by 2025, compared to less than 10% in 2021.
  • Responsible AI: The third trend is responsible AI, which addresses business and ethical issues related to the adoption of artificial intelligence technology. Gartner predicts that the concentration of pre-trained AI models among the top 1% of AI vendors by 2025 will make responsible AI a societal concern. Organisations should adopt a risk-proportionate approach and seek assurances from vendors to manage risk and comply with regulations.
  • Data-centric AI: The fourth trend involves a shift towards a data-centric rather than code-centric approach to building more effective AI systems. AI-specific data management, synthetic data and data tagging technologies are solutions that address challenges related to data accessibility, privacy and complexity. The use of generative AI to create synthetic data is expected to grow rapidly, accounting for 60% of data for AI by 2024.
  • Continued investment in AI: Finally, Gartner forecasts that investment in AI will continue to accelerate, and companies will emerge whose business will be based on this technology. It is expected that by the end of 2026, more than $10 billion will be invested in AI startups based on fundamental models. A recent Gartner survey showed that 45% of executives increased their investments in AI due to advances in generative artificial intelligence.

These trends reflect the continued growth and change in the field of data science and machine learning, and offer a glimpse into how these technologies will continue to transform the way businesses operate and make decisions. With the momentum of generative artificial intelligence, the adoption of these trends is expected to accelerate further in the coming years.