11 data predictions for AI-centric enterprise growth in 2024

In 2023, data technology focused on adopting generative artificial intelligence (AI) and foundation models. Companies soon realized that in order to leverage this tech, they needed to get their data affairs in order. While we know what role high-quality and valuable data can bring to a business’ success, we need to understand how technological advancements such as AI can help leverage your data. VentureBeat shares an insightful article of 11 data predictions for AI-centric enterprise growth in the new year with supporting evidence from tech experts in their fields.

  1. Relational will break free of SQL. “Many organizations continue to rely on outdated operational databases that were built to handle the demands of decades-old technology. SQL is a database language that lacks a standardized approach to procedural logic which, for most applications, is embedded within an application server connected to a SQL database using a stateful, persistent session. Looking ahead, we’ll see businesses adopt more agile database infrastructure that supports the distribution, consistency, scalability and flexibility of modern applications across IoT, edge, and AI. The challenges with legacy databases will only become more costly as their limitations become more burdensome to enterprise developers, and a larger bottleneck for the pace of business innovation.” – Bob Muglia, executive chairman of Fauna and former CEO of Snowflake
  2. Vector databases will become the most sought-after technology. “In an era where data-driven insights fuel innovation, vector databases have swiftly gained prominence due to their prowess in handling high-dimensional data and facilitating complex similarity searches. Whether for recommendation systems, image recognition, natural language processing, financial forecasting, or other AI-driven ventures, understanding the top vector databases will be critical for software development across industries.” – Ratnesh Singh Parihar, principal architect at Talentica Software, and Avthar Sewrathan, GM for AI and vector at Timescale
  3. Fishing for LLM gold in enterprise data lakes. “In 2024, businesses will begin using generative AI to make use of that untamed data by putting it to work building and customizing LLMs. With AI-powered supercomputing, businesses will begin mining their unstructured data — including chats, videos and code — to expand their generative AI development into training multimodal models.” – Charlie Boyle, vice president of DGX Systems, Nvidia
  4. Companies without sophisticated enough automation to power AI will feel the burn. “As businesses implement AI to maintain their competitive edge, many will feel the effects of their disorganized data infrastructure more acutely. The effects of bad data (or not enough data) will be compounded when the stakes are raised from simply serving up bad information on a dashboard to potentially automating the wrong decisions and behaviors based on that data.” – Sean Knapp, CEO of Ascend.io
  5. Cloud FinOps teams will optimize their data pipelines. “In Ascend’s annual research, 48% of respondents cited plans to optimize their data pipelines to reduce cloud computing costs, with 89% of those respondents expecting the number of pipelines to grow in the next 12 months. It will be imperative next year to leverage platforms that pinpoint where extra spending is occurring in data pipelines and push back with rapid demonstrations of cost optimizations to avoid misguided mandates from above.” – Sean Knapp, CEO of Ascend.io
  6. Intent data will become a must-have for go-to-market teams. “With AI becoming more sophisticated every year, we anticipate seeing a continued shift from reactive to proactive customer engagement, boosting conversions and fostering long-term customer loyalty.” –  Henry Schuck, CEO of ZoomInfo
  7. Data and business teams will lock horns over onboarding AI products. “While business users’ demand for AI products like ChatGPT has already taken off, data teams will still impose a huge checklist before allowing access to corporate data. This tail-wagging-the-dog scenario may be a forcing function to strike a balance, and adoption could come sooner rather than later as AI proves itself as reliable and secure.” –  Arina Curtis, CEO and co-founder of DataGPT
  8. Enterprises will get a double whammy from real-time and AI. “AI-powered real-time data analytics will give enterprises far greater cost savings and competitive intelligence than before by way of automation, and enable software engineers to move faster within the organization. With AI, in 2024, we will be able to process these documents in real-time and also get good intelligence from this dataset without having to code custom models.” – Dhruba Borthakur, CTO and co-founder of Rockset
  9. Knowledge graphs will help users eliminate data silos. “As enterprises continue to move more data into a data cloud, they are collecting hundreds, thousands, and sometimes even tens of thousands, of data silos in their clouds. With this, in the new year, we will see a variety of established and novel knowledge graph-based AI techniques that support the development of intelligent applications emerge.” – Molham Aref, CEO and founder of RelationalAI
  10. AI will change the current approach to data management. “Companies will find they need to strike a balance to protect data that is being used by AI models, while still using that data to support valuable decision-making. These innovative data management solutions will continue to evolve alongside regulatory compliance and emerging legislation.” — Osmar Olivo, VP of product management, Inrupt
  11. The role of Chief Data Officer will become a prerequisite for CIO hopefuls. “Organizations looking for great CIOs will choose the ones who truly understand how data moves, flows through and influences organizations, meaning that CDOs will have a natural advantage in pursuing that career path and continue to exert tremendous influence in the enterprise.” – Heath Thompson, president & GM, Quest Software


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