CIOs Urged to Audit AI Dependencies Amid Bubble Concerns
SAN FRANCISCO – IT leaders are being advised to proactively assess their reliance on external AI models as concerns mount over a potential “bubble burst” in the generative AI market. Experts warn that over-dependence on single models – whether proprietary or open source – could leave organizations vulnerable to legal complications, vendor lock-in, and operational disruption.
The current enthusiasm for generative AI, while promising, carries inherent risks. While open-source options offer the appeal of data control, they aren’t without caveats. “You can own your future,” said Carreon from Almacenes Distribuidores de la Frontera, emphasizing the control offered by deploying AI infrastructure internally. Though, Info-Tech’s Jackson cautioned that open source “is not just a free pass to anything and everything,” and could potentially trigger royalty obligations, citing Meta as a potential example. He added, “you can own that on your own premises,” but warned of potential “traps” within the open-source landscape.
Recent legal battles surrounding WordPress serve as a cautionary tale. The disputes, involving legal filings between WordPress.org and WP Engine, highlight the risks inherent in relying on open-source projects.
Beyond legal concerns, experts emphasize the danger of “too much dependence” on any single model. Carreon advocates for building adaptability into AI deployments, stating, “Make sure that you can easily swap from GPT to Gemini or to Claude. It’s not really that hard [because] the models behave very similarly in terms of their APIs.”
However, Gartner VP analyst Kjell Carlsson disagreed on the ease of switching, stating that while redirecting API calls is possible, “switching from one model to another is a lot more painful than that,” requiring significant code rewriting and testing. Srini PagiDyala, a co-founder of Aigo.ai, advises CIOs to promptly analyze their current genAI setups to determine their dependency on external models and experiment with swapping them out.
Even without an immediate market correction, understanding current dependency levels provides valuable leverage for contract negotiations and allows time to explore alternative approaches.As the industry matures, a potential market adjustment could reinforce the importance of sound business planning and profitability.
