Published on March 13, 2024, 8:30 pm

Generative artificial intelligence (AI) has become increasingly popular among working professionals as it allows them to delegate routine tasks and focus on more critical responsibilities. Despite its benefits, the rise of generative AI has raised concerns about copyright infringement, which may hinder its widespread adoption.

One significant issue highlighted by consulting firm Gartner is that generative AI models require extensive training data, often sourced from the internet. This reliance means that many AI models produce outputs based on existing content, potentially without explicit permission from the original creators. Consequently, organizations like The New York Times have pursued legal action against AI companies for copyright violations as their chatbots produce content derived from copyrighted material.

As the use of generative AI becomes more commonplace, companies are expected to shift towards a proactive stance to mitigate copyright risks. This transition will involve additional time and financial investments to safeguard against intellectual property loss and copyright disputes, slowing down the integration of this technology according to Gartner’s predictions.

Looking ahead, Gartner forecasts that by 2026, defensive expenditures aimed at reducing IP risks and copyright breaches will impede the progress of generative AI technologies within enterprises. Rita Sallam from Gartner emphasizes the urgency for regulators to adapt swiftly to these evolving concerns surrounding IP and copyright infringements in light of broader adoption of Generative AI.

Furthermore, Gartner anticipates that by 2028, over 50% of enterprises opting to develop their substantial language models independently may abandon these efforts due to associated costs, complexities, and ongoing maintenance requirements. Chief data and analytics officers are advised by Gartner to carefully evaluate their organization’s risk tolerance while pursuing AI initiatives efficiently. Sallam suggests a strategy emphasizing adaptable systems capable of accommodating evolving innovations effectively.


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