Insights / Research Report / Beyond the GenAI Hype: Real-world Investments, Use Cases, and Concerns
August 18, 2023

Beyond the GenAI Hype: Real-world Investments, Use Cases, and Concerns

Mike Leone
Principal Analyst, Data Analytics & AI

Market Topics

Application Modernization Customer Experience Cybersecurity Data Analytics & Artificial Intelligence Data Management Data Protection End-user Computing Infrastructure Networking Operations Unified Communications & Collaboration

Research Objectives

While AI in general was already assimilating into the everyday business and IT lexicon thanks to ongoing AI and analytics strategies and initiatives, GenAI recently stormed the market and mindshare of decision makers across industries and major geographic markets. Business leaders see a massive opportunity to positively impact operations and customer strategies with GenAI, but its adoption and use across all business units carry a fair share of trepidation.

Most organizations are aware of GenAI, and a rising percentage are currently formulating strategies to both harness the technology’s benefits and control its use to prevent data quality issues and information leaks. To assess the state of GenAI strategies and plans, TechTarget’s Enterprise Strategy Group surveyed 670 IT professionals and business decision makers in North America (65%), EMEA (18%), APAC (16%), and LATAM (2%) involved with generative AI initiatives in their organization. This study sought to answer the following questions:

  • What is the status of GenAI initiatives within organizations?
  • How are organizations using, or planning use, large language models (LLMs) to support GenAI initiatives?
  • Are organizations allocating, or planning to allocate, budget to support GenAI initiatives? If so, what is the percentage of IT budgets allocated to GenAI?
  • In which lines of business are organizations currently applying GenAI? Moving forward, which of these areas will benefit most from the use of GenAI?
  • Which teams or stakeholders actively contribute to shaping GenAI initiatives in organizations?
  • What technology investments are needed to support GenAI initiatives?
  • What do organizations identify as the primary benefits of using GenAI in their environments?
  • What are the most prioritized use cases for GenAI, particularly in environments where the technology is applied across multiple areas?
  • What are the biggest challenges organizations face in GenAI implementations?
  • In which areas do organizations feel they need to invest (time and/or money) to support the use of GenAI?
  • What type of third parties do organizations currently, or plan to, work with to support GenAI initiatives?
  • Are organizations more or less likely to consider vendors that incorporate GenAI capabilities as part of their products or services?
  • How much more, if at all, are organizations willing to pay for a product or service that uses GenAI versus a comparable product or service that does not use GenAI?
  • What types of information or media would help organizations assess GenAI?
  • For which application development use cases are organizations using, or planning to use, GenAI? What about use cases for security and customer experience (CX)? Where will investments be made?
  • How do, or will, organizations ensure the security and privacy of data used in GenAI models?
  • For which security use cases are organizations using, or planning to use, GenAI?
  • Which areas of the analytics lifecycle will benefit most from the use of GenAI?

Survey participants represented a wide range of industries, including financial, manufacturing, retail/wholesale, and healthcare, among others. For more details, please see the Research Methodology and Respondent Demographics sections of this report.


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