Generative AI adoption will slow because of copyright, according to Gartner

Key Points:

  • Generative AI has led to a shift in focus for working professionals
  • Concerns around copyright infringement are slowing the adoption of generative AI
  • Enterprises need to balance AI ambition with risk tolerance to maximize results


Generative artificial intelligence has revolutionized how professionals delegate tasks, freeing them to focus on higher-value activities. However, concerns about copyright infringement are casting a shadow over this advancement, according to consulting firm Gartner.


Generative AI models, like ChatGPT, rely on vast amounts of data from the internet, potentially incorporating content without explicit permission from the original creators. This has led organizations, including The New York Times, to take legal action, alleging copyright infringement by AI-generated chatbots.


Such challenges are expected to increase enterprise spending on safeguarding intellectual property rights, potentially slowing down the widespread adoption of generative AI. Gartner warns that defensive spending to mitigate copyright risks may erode returns on investment in this cutting-edge technology by 2026.


Rita Sallam, a distinguished VP analyst at Gartner, emphasizes the urgency for regulators to keep pace with the advancements in generative AI. She highlights the evolving risk landscape, indicating that copyright infringement, once a limited concern, now poses a threat across entire organizations.


Looking ahead, Gartner predicts that by 2028, over half of enterprises embarking on building large language models from scratch may abandon these endeavors due to escalating costs, complexity, and technical liabilities. Chief data and analytics officers are urged to carefully evaluate their AI strategies and risk thresholds to optimize outcomes in this evolving landscape.


Sallam underscores the importance of designing adaptable systems to facilitate model changes as technology evolves, emphasizing the need for flexibility and foresight to navigate the challenges associated with generative AI.



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