Enterprises embrace hybrid Gen AI approach, Data Fabric investments: Report

Enterprises are gearing up for substantial investments in data fabric technologies to facilitate the success of generative artificial intelligence (Gen AI). They are adopting a hybrid approach that combines generative AI with traditional AI to expand its impact within their organisations, according to a new report by business intelligence platform Qlik. 

In response to how they plan to implement generative AI, 68% intend to use public or open-source models refined with proprietary data, while 45% are exploring the possibility of constructing models from scratch using proprietary data. 

Having expertise in these areas is crucial to addressing issues such as data security, governance, bias, and hallucinations associated with generative AI. Many respondents, 60% to be precise, acknowledge the need for external assistance to bridge this knowledge gap. 

James Fisher, Chief Strategy Officer at Qlik, noted, "Generative AI's potential has sparked considerable investment and interest in both specific generative AI tools and technologies that facilitate risk management, complexity handling, and scaling of generative AI and traditional AI for impactful outcomes." 

The report reveals that while the initial excitement surrounding generative AI persists, leaders understand the necessity of aligning these tools with appropriate data strategies and technologies to unlock their transformative potential fully. They seek guidance on initiating and advancing generative AI while maintaining focus on risk and governance concerns. 

Despite the spotlight on generative AI, respondents acknowledge the continued value of traditional AI in areas like predictive analytics. Generative AI is expected to extend AI's capabilities beyond data experts, making it accessible to a broader audience. This approach is envisioned to scale the ability to uncover deeper insights and solve problems more efficiently. 

This promising vision has triggered a significant influx of investment. 79% of respondents have either procured generative AI tools or invested in generative AI projects. Furthermore, 31% plan to allocate over $10 million to generative AI initiatives in the upcoming year. However, 44% of organisations risk operating in silos as they lack a clear generative AI strategy. 

As per the report, many organizations view data fabrics as a central element of their strategy to address these challenges. Respondents admit that their data fabrics require enhancements or aren't adequately prepared for generative AI. Just 20% believe their data fabric is well-equipped to meet generative AI needs. Consequently, 73% plan to increase spending on technologies supporting data fabrics. 

To facilitate this, investments must target data volume management, as nearly three-quarters of respondents anticipate increased data movement and management for current analytics. Data quality, ML/AI tools, data governance, data integration, and BI/Analytics are all identified as vital elements for creating a data fabric conducive to generative AI success. 

The report said these investments will help organisations overcome common barriers, including regulatory compliance, data security, and resource constraints. 

A recent report by McKinsey & Company from June highlights the significant potential of generative AI. It could boost global productivity by $2.6 trillion to $4.4 trillion annually. Additionally, the report suggests that the combined value of artificial intelligence and analytics could reach $11 trillion to $17.7 trillion each year. By incorporating generative AI into these applications, the potential value could rise by 15% to 40%.