Sure, here is a rephrased version of the title:

Sure, here is a rephrased version of the title:

“Forecasting AI-Driven Enterprise Expansion: 11 Data Trends for 2024”

Subscribe to our daily and weekly newsletters for the latest updates and exclusive content on leading AI trends.

2023 was a big year for embracing generative AI and foundational models. As organizations hurried to integrate AI into their systems, they soon realized the crucial need to organize their data properly.

Though businesses have always known the importance of high-quality data, the rise of generative AI has highlighted its significance even more. Looking ahead to 2024, which promises even more advancements in AI, industry experts and vendors predict significant changes in the data ecosystem.

1. Moving Beyond SQL in Relational Databases
Enterprises planning for growth in 2024 need secure access to their data. Modern applications are pushing the boundaries of traditional SQL databases. While SQL will remain popular, many developers will turn to document-relational databases that fit modern development workflows and support strict transactions.

For analytical needs, large language models (LLMs) require detailed context. Retrieval Augmented Generation (RAG) using vector databases will become mainstream. Structured knowledge graphs will emerge as a new database architecture to support AI solutions.

2. The Rise of Vector Databases
Vector databases will become essential in 2024. These databases handle complex similarity searches and high-dimensional data, making them crucial for recommendation systems, image recognition, financial forecasting, and more. As AI-centric applications are built, scalable and user-friendly vector data storage will become vital.

3. Unlocking Enterprise Data Lakes with LLMs
In 2024, businesses will harness generative AI to tap into their massive stores of unstructured data—like chats, videos, and code—to train multimodal models. This will allow companies to extract more specific insights and discover new opportunities, such as detecting health anomalies or identifying retail trends.

4. The Pitfalls of Poor Data Infrastructure
As companies rush to implement AI, those with disorganized data systems will face significant challenges. Bad or insufficient data can lead to poor automated decisions. It’s only a matter of time before a lack of strong data infrastructure causes a major setback in a mission-critical AI deployment.

5. Optimizing Cloud Spending with FinOps
In 2024, businesses will need to address cloud spending by fostering cross-team collaboration between finance and engineering. Nearly half of respondents in recent research plan to optimize data pipelines to reduce costs. Effective platforms will help identify and rectify unnecessary expenses quickly.

6. The Necessity of Intent Data for Marketing
Intent data will become indispensable for sales and marketing teams in 2024. By predicting customer needs through behavioral data analysis, businesses can shift from reactive to proactive engagement, improving conversions and fostering customer loyalty.

7. Data and Business Teams Aligning Over AI Adoption
While demand for AI products like ChatGPT is growing, data teams will impose strict guidelines before granting access to corporate data. Businesses will prioritize clean datasets for successful AI deployment, allowing them to gain valuable insights and stay competitive.

8. Real-Time AI and Data Analytics
AI-powered real-time data analytics will offer significant cost savings and competitive intelligence in 2024. Companies will be able to process large datasets in real-time, eliminating the need for extensive coding and reducing the need for large teams dedicated to data extraction.

9. Eliminating Data Silos with Knowledge Graphs
As companies move more data to the cloud, they accumulate numerous data silos. Knowledge graphs will help navigate these silos by leveraging relationships between different data sources. This approach will support the development of intelligent applications and new AI techniques.

10. Evolving Data Management Approaches
Businesses recognize AI’s potential for enhancing value and competitiveness. However, they must balance the protection of personal and proprietary data with AI’s need for diverse data input. Data management solutions will evolve alongside regulatory and legislative changes.

11. The Chief Data Officer’s Path to CIO
In 2024, the role of Chief Data Officer (CDO) will become a stepping stone to achieving the position of Chief Information Officer (CIO). As organizations invest more in AI and cloud technologies, CDOs, who understand the flow and impact of data, will be well-positioned to advance to CIO roles.