AI chatbots face a significant challenge—they incur financial losses with each chat, hampering their quality and potential impact. The exorbitant operational costs of running large language models, like ChatGPT and Bard, limit their deployment and force companies to prioritize profitability over delivering the best versions to the public. The scarcity of computer chips further exacerbates the issue, making it difficult for companies to afford and utilize these models effectively. The high expenses associated with AI chatbots also hinder their accuracy, often resulting in biased or inaccurate outputs.
Why it matters: The challenges related to profitability, operational costs, sustainability, and vendor selection make it important for technology executives to closely monitor and understand the implications of AI chatbots in order to make informed decisions and effectively leverage AI technologies within their organizations.
- AI chatbots’ financial viability is threatened by the high cost of operating large language models.
- Limited availability of computer chips further constrains companies’ ability to afford and utilize these models.
- The deployment of suboptimal models due to cost limitations leads to weaknesses like bias and misinformation.
- The dominance of tech giants in AI language model development and deployment raises concerns about competition and user dependency.
