Transform from big to better data using the knowledge from our top 10 trends in AI. Until now, data access for GenAI has been a massive free-for-all, with no traceability of data origin or quality control. It’s time to step up a chain from Volume, Velocity and Variety (big data) to Validity and Value (better data). Will your data be ready?
Whether ML or augmentations, it’s time to put traditional AI into production and scale, especially in well-established use cases like fraud analytics and churn analysis.
Generative AI is expected to achieve ~30% share of the overall AI market by 2025.Source: Boston Consulting Group
This user base appreciates auto-generated visualizations and insights, enhanced with explanations in natural language.
By 2025, 66% of G2000 will adopt AI-driven headless BI and analytics with chat, Q&A, and proactive notification functionality — quadrupling the number of users with access to contextual information.Source: IDC FutureScape: Worldwide Data and Analytics 2024 Predictions
By using knowledge graphs and vector databases, complemented by RAG (Retrieval, Augmentation, Generation), the opportunities for combining structured and unstructured data in a trusted way are endless.
Unstructured data managed by enterprises will double in 2024Forrester, Predictions 2024: Data And Analytics
We'll toggle between these two different modes — enabled by embeddability, connectivity, and APIs — to get maximum benefits from each platform.
By 2026, Generative AI will significantly alter 70% of the design and development efforts for new web applications and mobile apps.Source: Gartner, Top Strategic Technology Trends for 2024, 16 October 2023 GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
We need a mechanism to clearly label and signpost data, using techniques of provenance and cryptography alongside techniques we haven’t yet invented to create the equivalent of a "DNA test for your data".
90% of online content will be generated by AI by 2025.Source: Nina Schick interview with Yahoo Finance Live, January 7, 2023
With an explosion of apps built by the ‘everyday developer,’ organizations must take steps to educate their workforce in the benefits and pitfalls of generative AI.
To mitigate new risks created by the pervasive workforces use of generative AI, by the end of 2025, 60% of large enterprises will mandate formal data literacy and responsible AI training.Source: IDC FutureScape: Worldwide Future of Enterprise Intelligence 2024 Predictions, IDC #US51293423, Oct 2023
This will empower business analysts, for example, who can now go back earlier in the pipeline to do data management and preparation tasks. That same analyst can also apply advanced statistical models to the data and tools they work with every day, without needing to export it to an advanced workbench.
By 2026, 50% of organizations will have to evaluate ABI and DSML platforms as an all-in-one, composable platform due to market convergence.Source: Gartner, Predicts 2023: Analytics, BI and Data Science Composability and Consolidation
So far, LLMs and generative AI have mainly been used to support reasoning and conduct analysis, rather than for iPaaS and actioning. Now, there are several exciting efforts underway to support the latter, including an approach to LLMs that involves synergizing reasoning and action.
By 2027, outlier detection and other augmented analytics capabilities will evolve into autonomous analytics platforms that fully manage and execute 20% of business processes.Source: Gartner, Predicts 2023: Analytics, BI, and Data Science Composability and Consolidation
Your proprietary organizational data will be a valuable raw material here and “solution fabrics” will emerge where domain-specific data and apps can be shared and traded.
By 2026, more than 80% of generative AI use cases in enterprises will leverage customized, specialized AI models rather than generic foundation models offered via public APIs.Source: IDC FutureScape: Worldwide Future of Enterprise Intelligence 2024 Predictions, IDC #US51293423, Oct 2023
The concept of treating data as a valuable asset or product means it can be surfaced in a catalogue, used for various purposes internally, and even evolve into a tradable good. Like with music’s rise of streaming platforms, creators of quality data products must have more exchanges on which to trade them.
By 2026, 60% of leading enterprise intelligence companies will have identified data products, and 15% will have attributed business value to the products with a data valuation methodology.Source: IDC FutureScape: Worldwide Future of Enterprise Intelligence 2024 Predictions, IDC #US51293423, Oct 2023
Imagine a product fundamental to AI that can be traded and becomes more valuable the more it’s used. How do we get to this promised future? The path to trusted data is filled with challenges and opportunities that savvy organizations must be aware of.