BARC: The Future of AI in BI and Analytics
Adopting Generative AI for Analytics
Kevin Petrie, Alexander Seeliger, Robert Tischler, March 2024
im Rahmen unserer groß angelegten Kooperation mit Qlik und BARC stellen wir Ihnen heute einen Meilenstein aus dem KI-Bereich vor: die BARC-Studie „Die Zukunft von BI & Analytics: Adopting Generative AI for Analytics“. Es geht um Early Trends, Lessons, and Best Practices. Sie befasst sich mit der Einführung und den Auswirkungen von generativer KI (GenAI) in Business Intelligence und Analytics.
Die Studie hebt hervor, dass sich die meisten Unternehmen noch ganz in der Anfangsphase der Einführung von GenAI für Business Intelligence und Analytik befinden. Zu den wichtigsten Vorteilen des Einsatzes von GenAI in der BI gehören schnellere Erkenntnisse, geringere Arbeitsbelastung, verbesserte Benutzerinteraktion, höhere Produktivität und tiefere analytische Erkenntnisse. GenAI hat das Potenzial, Unternehmen datenorientierter zu machen.
Die Studie unterstreicht das transformative Potenzial von GenAI in BI und Analytik und hebt die Notwendigkeit für Unternehmen hervor, sich mit den Herausforderungen und Chancen dieser neuen Technologie zu beschäftigen.
Download: The Future of AI in Business Intelligence and Analytics
Mgmt Summary
Generative AI (GenAI) enables business intelligence and analytics (BIA) teams to prepare and analyze data using natural language, thereby boosting productivity and tackling more sophisticated use cases. Both methods go beyond natural language processing to convert human commands to SQL queries, describe findings and perform myriad other tasks while conversing with users. BIA teams are taking advantage of GenAI features within their BIA tools or general-purpose language models.
So, what can we learn from adoption trends so far? This report draws conclusions and provides actionable recommendations based on the survey responses from 238 data leaders and practitioners about their use of GenAI for BIA. We explore adoption status, benefits, risks and use cases, as well as the best practices of leading practitioners.
Adoption of GenAI in BI
Most leaders and practitioners remain in the early stages of adoption: nearly one third (29 percent) of respondents are discussing it, 9 percent are evaluating it and 22 percent are experimenting. Just 9 percent are implementing GenAI; 6 percent have GenAI in partial operational use and 3 percent in full operational use. As one would expect, leaders outpace laggards by a wide margin in adopting both GenAI and AI/ML overall.
Data engineers and business users express the most optimism about GenAI for BIA, given its productivity and self-service benefits. In contrast, heads of business units are ambivalent or even pessimistic given concerns about data governance. Data scientists, developers, consultants and power users also are ambivalent or even pessimistic.
Benefits & Risks
Data privacy and security, skills gaps and training needs, and compliance and regulatory challenges rank as the top risks of GenAI. These responses indicate that analytics teams, familiar with longstanding challenges of data governance, understand well the risks of employing GenAI for BIA.
Faster time to insight, reduced workload, enhanced user interaction, simplified BIA and expanded self-service rank as the top benefits of GenAI for BIA. These and other popular responses illustrate a desire to become more data-driven, democratize data consumption and handle more diverse data sets. Leaders believe the immediate value of GenAI for BIA is getting more valuable insights, faster, out of traditional tabular data sets — rather than adding new data sources.