Qlik：非结构化数据和GenAI洞察报告_14页_7mb

Summary of the Benchmark Report: Untapped Insights: Unstructured Data & GenAI

Core Content

This benchmark report explores the current state and future potential of using generative AI (GenAI) to analyze unstructured data in enterprises. It is based on a survey conducted with ETR in April 2024, involving 200 directors and above from companies of all sizes across various industries.

Main Findings

Unstructured Data Landscape

• Unstructured data is prevalent in most organizations, existing across multiple formats and locations.
• The majority of respondents (62%) have not yet used unstructured data to derive insights, and only 16% have invested in tools to analyze it.
• Unstructured data types include:
  • 95% text documents
  • 83% emails
  • 72% images and videos
  • 34% social media posts
• Common storage locations:
  • 62% internal knowledge libraries
  • 52% internal systems
  • 45% CMS
• Volume of unstructured data has increased slightly or significantly for one third of respondents, highlighting the growing challenge in managing and extracting value from this data.

Potential Value of GenAI

• The top four anticipated impacts of GenAI on unstructured data are:
  1. Enhancing operational efficiency and automation (62%)
  2. Improving customer experience through personalized insights (41%)
  3. Improving team productivity (40%)
  4. Controlling and reducing operational costs (36%)
• The most valuable insights from unstructured data are:
  • 45% better search/chat with internal documentation
  • 28% identifying trends/patterns
  • 21% analyzing customer or employee behavior
• Expected financial gains:
  • 23% estimate 0% to 10% gains
  • 45% estimate 10% to 30% gains
  • 14% are unsure

Challenges with Unstructured Data

• The top three challenges in managing unstructured data are:
  1. Extracting the right answers and insights (77%)
  2. Identifying the right information (66%)
  3. Ensuring accuracy and trust of information (57%)
• 66% of respondents believe traditional tools are ineffective in deriving insights from unstructured data.
• Barriers to funding include:
  • 19% lack AI and unstructured data experience
  • 20% find it difficult to quantify value by business line

GenAI Adoption Plans

• 55% of respondents are interested in exploring GenAI for unstructured data analysis.
• 36% have already begun to explore.
• 9% have no plans.
• Over two-thirds plan to invest in GenAI tools in the next 6-12 months.
• 48% of AI budgets are allocated to unstructured data challenges, with Customer Support and IT/Security as the top functional areas to prioritize.

AI Strategy and Investment

• 25% of all respondents have a formalized AI strategy.
• 53% are currently developing one.
• 19% plan to develop one in the next year.
• 33% find it challenging to quantify ROI, but recognize the strategic importance of AI projects.
• 24% do not currently assess ROI specifically for AI projects.
• Global 2000 organizations are more cautious in using public models and prefer refinement with proprietary data over building from scratch.

Key Concerns and Governance Priorities

• The biggest concerns when using GenAI to manage unstructured data are:
  • Legal & Regulatory Compliance (Very concerned)
  • Lack of Skilled Staff or Experts
  • High Costs or Budget Limits
  • Integrating with Current Data
  • Uncertainty About ROI
  • Outdated Source Material
  • Authorized Access to Info
  • Answers & Source Material Available
  • Audits & Data Transparency
• All governance priorities are ranked as important, with a particular emphasis on consistency of answers and access control.

Key Takeaways

• Unstructured data is underutilized in enterprises, with only 16% currently using tools to analyze it.
• GenAI is seen as a transformative opportunity, especially for improving operational efficiency and customer experience.
• Major challenges include data extraction, accuracy, and ROI quantification.
• Funding for GenAI tools is limited due to difficulty in quantifying value and lack of experience.
• AI strategy is still in development for most organizations, with a growing interest in exploring GenAI for unstructured data.
• Customer Support and IT/Security are the primary functional areas to prioritize for GenAI implementation.
• Governance is a critical focus, with concerns around data privacy, access control, and transparency.

Conclusion

The report underscores the growing recognition of the value of unstructured data and the potential of GenAI to unlock insights from it. However, significant challenges remain in terms of tool effectiveness, ROI measurement, and expertise. As enterprises move forward, they must address these challenges to fully realize the benefits of GenAI in managing unstructured data. Qlik is positioned as a solution provider that offers intuitive, real-time analytics and enterprise-grade AI/ML capabilities to help organizations harness unstructured data effectively.