11 Data Predictions for AI-Centric Business Growth in 2024
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2023 primarily focused on adopting generative AI and foundational models. However, as organizations race to integrate generative AI into workflows, they recognize the importance of organizing data matters.
While businesses have always understood the role of high-quality data in business success, the rise of generative AI has reinforced its value, ensuring it remains a focal point for all. Now, as we enter 2024, this year will bring an even larger-scale generative AI narrative. Leading industry experts and vendors have shared their predictions on how different aspects of the data ecosystem will evolve in the coming months.
Image source note: The image is AI-generated, licensed by Midjourney
1. Relational Databases Will Break Free from SQL Constraints
"Whether expanding business through modern edge computing, IoT, or generative AI applications, enterprises have bold plans for 2024. All these initiatives depend on secure access to corporate data. For many companies, the data infrastructure supporting these applications remains stagnant. Many organizations still rely on outdated operational databases built to handle technological needs from decades ago.
SQL is a database language that lacks standardized methods for procedural logic. For most applications, procedural logic is embedded in application servers connected to SQL databases, using stateful, persistent sessions. This design approach for SQL made sense 50 years ago, but it has become a painful legacy for modern, connectionless cloud services. It typically requires application code and databases to co-reside in the same data center region, which severely hinders today's serverless or geographically distributed applications that are critical to enterprises, such as IoT and edge applications...
Looking ahead, we will see enterprises adopting more flexible database infrastructures that support the distribution, consistency, scalability, and flexibility of modern applications in IoT, edge, and AI domains. As the limitations of traditional databases become increasingly apparent to enterprise developers, they will grow more expensive and become a greater bottleneck to the pace of business innovation.
— Bob Muglia, Executive Chairman of Fauna, former CEO of Snowflake
2. Vector databases will become the most sought-after technology
In 2024, vector databases will become the most sought-after technology. In an era where data-driven insights fuel innovation, vector databases have rapidly risen to prominence due to their ability to handle high-dimensional data and facilitate complex similarity searches. Whether for recommendation systems, image recognition, natural language processing, financial forecasting, or other AI-driven projects, understanding top-tier vector databases is crucial for software development across industries.
As new applications adopt AI from the ground up... vector databases will play an increasingly vital role in technology stacks, much like application databases did in the past. Teams will require scalable, user-friendly, and operationally simple vector data storage solutions as they strive to create AI products with novel LLM-powered functionalities.
— Ratnesh Singh Parihar, Chief Architect at Talentica Software, General Manager of Timescale AI and Vector
3. Finding LLM Gold in Enterprise Data Lakes
Statistics about how much information enterprises store vary widely, with large companies potentially holding hundreds of petabytes. However, many report mining less than half of their data—primarily structured—for actionable insights. In 2024, businesses will begin using generative AI to tap into this untapped data by employing it to build and customize LLMs. Through AI-driven supercomputing, enterprises will start mining unstructured data—including chats, videos, and code—to expand their generative AI development for training multimodal models. This leap beyond tabular and structured data mining will enable companies to provide more precise answers to problems and uncover new opportunities. Applications include detecting anomalies in health scans, identifying emerging retail trends, and enhancing operational safety.
— Charlie Boyle, VP of Nvidia DGX Systems
4. Companies Without Advanced Automation to Support AI Will Suffer
"As businesses implement AI to maintain competitive advantages, many will feel the impact of their messy data infrastructure more acutely. When transitioning from simply displaying incorrect information on dashboards to potentially automating wrong decisions and actions based on that data, the consequences of poor or insufficient data will intensify. It's only a matter of time before organizations without robust data infrastructure and governance deploy generative AI in critical contexts and suffer losses due to declining accuracy."
— Sean Knapp, CEO of Ascend.io
5. Cloud FinOps teams will optimize their data processes
"Facing the reality of runaway cloud computing costs this year, true cross-organizational collaboration will be necessary in 2024 to identify unnecessary expenditures, with both finance and engineering teams playing critical roles. In Ascend's annual study, 48% of respondents said they plan to optimize their data workflows to reduce cloud costs, with 89% expecting workflow volumes to grow in the next 12 months. Next year, leveraging platforms that can precisely pinpoint excess spending in data workflows and quickly demonstrate cost optimization will be essential to avoid misleading directives from leadership."
— Sean Knapp, CEO of Ascend.io
6. Intent Data Will Become an Indispensable Part of Marketing Teams
“In 2024, intent data for marketing teams will no longer be ‘nice-to-have.’ As companies strive to align sales and marketing efforts, the ability to predict customer needs through behavioral data analysis of intent data will become increasingly important. With AI growing more sophisticated each year, we expect to see a continued shift from passive to proactive customer engagement, enhancing conversion rates and promoting long-term customer loyalty.”
— Henry Schuck, CEO of ZoomInfo
7. Data and business teams will diverge in introducing AI products
Although business users' demand for AI products such as ChatGPT has taken off, data teams will still impose extensive checklists before permitting access to enterprise data. This tail-wagging-the-dog scenario could become a balancing force, potentially accelerating adoption earlier than expected as AI demonstrates reliability and safety.
Moreover, enterprises will prioritize clean datasets to ride the wave of AI-driven analytics. Clean datasets will serve as the foundation for successful AI implementation, enabling businesses to derive valuable insights and maintain competitiveness.
— Arina Curtis, CEO and Co-founder of DataGPT
8. Enterprises Will Face Dual Impact from Real-Time and Artificial Intelligence
"AI-driven real-time data analytics will bring greater cost savings and competitive intelligence to enterprises through automation, enabling software engineers to move faster within organizations. For example, insurance companies store thousands of terabytes of data in their databases. By 2024, with AI, we will be able to process these files in real-time and derive valuable insights from this dataset without the need to write custom models.
So far, software engineers have been required to write code to parse these files, then write more code to extract keywords or values, and finally put them into a database and query to generate actionable insights. With real-time AI, the cost savings for businesses will be enormous, as companies no longer need to hire large teams to derive competitive value from data.
– Dhruba Borthakur, CTO and Co-founder of Rockset
9. Knowledge Graphs Will Help Users Eliminate Data Silos
"As enterprises continue to migrate more data to the data cloud, they accumulate hundreds, thousands, and sometimes even tens of thousands of data silos in the cloud. Knowledge graphs will effortlessly enable language models to navigate all existing data silos by leveraging relationships between various data sources. Therefore, in the new year, we will see the emergence of various established and novel knowledge graph-based AI technologies that support the development of intelligent applications."
– Molham Aref, CEO and Founder of RelationalAI
10. AI will transform current data management approaches
"Enterprises are recognizing the potential of artificial intelligence for their overall value proposition and competitive advantage. To achieve this, AI needs to be trained and process different types of data. Some data is public, but much of it pertains to organization-specific personal consumer information or intellectual property. Companies will find they need to protect the data used by AI models while still utilizing it to support valuable decision-making. These innovative data management solutions will continue to evolve alongside regulatory compliance and emerging regulations."
— Osmar Olivo, Vice President of Product Management at Inrupt
11. The Role of Chief Data Officer Will Become a Prerequisite for Aspiring Chief Information Officers
"In 2024, a new and proven career path will emerge for those aspiring to become Chief Information Officers—excelling in the role of Chief Data Officer. Over the past few years, the Chief Data Officer has evolved from a low-budget advisory role to a critical asset for helping businesses fully leverage their data. As more organizations invest in AI and cloud computing to democratize data and drive innovation, the Chief Data Officer is in the driver's seat—closer than ever to the Chief Information Officer and the success of the enterprise. Organizations seeking exceptional Chief Information Officers will prioritize those who truly understand how data moves, flows, and impacts the organization. This means Chief Data Officers will have a natural advantage in pursuing this career path and will continue to make a significant impact within enterprises."