Interest in GenAI Is High, but Significant Investment Is Lacking

GenAI investments can transform the future of modern businesses. During our analysis of the gen AI marketplace for organizations, I typically ask these questions:

“What is the impact of unstructured data on GenAI adoption?”

“What is the impact of GenAI on unstructured data analysis?”

Do you see how these two approaches can help an organization create a fine-tuned model to flex their data governance and operational efficiencies?

Despite growing buzz around Generative Artificial Intelligence or GenAI applications, organizations have been slow to respond to the real needs in these areas. In the latest research, only 22% of enterprise leaders are making any kind of “significant” investments in AI technologies. The new research on GenAI investments reveal that while enterprises recognize the significant potential of unstructured data to enhance operational efficiency and drive meaningful insights, many are struggling to effectively leverage this resource. The survey shows that a lack of expertise and insufficient tools are major barriers, with only a small percentage of enterprises dedicating more than a quarter of their GenAI investments / budget to unstructured data initiatives.

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Here are the key takeaways from the report on GenAI investments, with the focus highlighting initiatives and opportunities with unstructured data.

GenAI to Analyze Unstructured Data Black Box

46% of business leaders are planning GenAI investments to analyze unstructured data in the next 12 months. 21% are planning to buy in the next 6 months while 14% expressed their disinterest in GenAI investments in the near future.

A streamlined access to unstructured data or the lack of it has the biggest impact on GenAI development. According to Qlik’s benchmark report on unstructured data and GenAI, 16% of business leaders have already purchased a tool to report insights extracted from unstructured data. 70% agree they have barely begun to realize the value of unstructured data. This leaves a wide gap in GenAI investments and related operational costs within an organization.

Using Unstructured Data for Automation, Search and Productivity 

Why organizations need insights from unstructured data?

Qlik’s survey found unstructured data insights can deeply impact operational efficiency and automation workflows. 46% of leaders believe insights from unstructured data can enhance efficiency and automation. 45% feel that these insights can deliver better search and chat results with internal documentation. A similar percentage of business leaders attribute success with CX efforts and personalization (41%), team productivity (40%), and reduction in operational costs (36%), to unstructured data insights.

Barriers to New Funding

Business leaders named the lack of experience in working with AI and unstructured data tools as major barriers to funding for new tools. 77% of leaders said extracting the right answers and insights as their biggest challenge with unstructured data management. Identifying the right information (66%), and ensuring accuracy and trustworthiness of information (57%) were other prominent challenges with managing unstructured data. To solve these unstructured data-related problems, 64% of leaders have identified an AI strategy. 57% already have a strategy for structured data. 79% of leaders have a formalized AI strategy to manage both type of data.

Approaches to GenAI Investments

Qlik’s report on unstructured data and generative AI revealed more than half of business leaders are at a “moderate” level of AI investments. A majority of them adopted a public AI model to meet their current needs, while 59% have integrated public models, open source models and proprietary data models. 21% of leaders are building their AI strategy from the scratch using proprietary data. When it comes to standardization of AI workflows for projects, 28% of leaders assess ROI and value of their AI investments on a case-by-case basis without a standard framework. 24% of leaders don’t assess ROI at all in their current strategy.

Data Privacy and Compliance Concerns Dominate

Data privacy, security, and regulatory compliance emerged as the biggest concerns for companies starting their GenAI investments for managing unstructured data. 86% of leaders are also concerned about the high costs or budget restrictions in their AI strategy. Data integration, uncertainty about ROI and access management are other major challenges identified in the report. Considering the GenAI maturity within the industry, organizations are still not prioritizing too much on vendor reputation. However, system integrations and governance features remain top priorities for improving the top or bottom lines using unstructured data.

At the time of this announcement, Qlik’s GM (Analytics Business Unit) Brendan Grady highlighted the need to tap into the vast pool of unstructured data. Brendan said, “With many sources citing that unstructured data makes up to 80% of the world’s data, it is no surprise that enterprise leaders want more real value from this untapped source. Yet, our survey highlights that nearly 70% agree their organization is not well equipped to understand how GenAI can be leveraged on their unstructured data.”

Brendan added, “Companies are looking for solutions that enable GenAI adoption without requiring them to overhaul their existing skillsets and technology stack. The opportunity is finding ways to integrate AI seamlessly into current analytics environments, allowing organizations to extract the right answers from unstructured data and drive meaningful business outcomes.”

Conclusion

Centralized governance is a key to GenAI investments in 2024. Trash the belief that mentioning GenAI models would continue to be your “breaking news” headline anymore in 2024. Unless, of course, you take charge of your unstructured data right now with GenAI models. If you baulk at the idea of pushing back on GenAI investments any further for different reasons, fears, or limitations, you’re just going to put yourself out of favor with your customers, partners, and employees and associates. Investments in GenAI tools could start with upskilling of workforce, re-engineering existing IT and data governance frameworks, and securing unstructured data with world-class governance and compliance management.