It seems like everyone is exploring generative artificial intelligence (AI) these days. From developers writing code to marketers creating content, people in various roles are finding ways to increase their productivity with this new technology. Analyst Gartner predicts that over 80% of enterprises will be using generative AI application programming interfaces, models, and software in production environments by 2026.
However, despite the hype, many businesses are not currently using generative AI, at least not officially. Gartner reports that less than 5% of enterprises are using the technology in production. Most organizations are still in the early exploratory stages, experimenting with small pilots and limited projects, rather than implementing generative AI on a large scale.
Despite this, a significant number of IT professionals are already using AI in their programming work. According to research by O’Reilly, 44% of IT professionals use AI, with 34% experimenting with it.
While the interest in generative AI is growing rapidly, organizations need to be aware of the risks associated with hurried adoption of the technology. For instance, CIOs are most concerned about data privacy, followed by hallucinations, and then security. It is important for businesses to manage these risks before they become unmanageable.
Risks related to adopting generative AI include data privacy and protection, input and output risks, and new cybersecurity risks. It is vital for organizations to establish policies for acceptable use and access management. The technology market is evolving to provide solutions to these risks, and business leaders should begin to prioritize and prepare for the integration of generative AI one step at a time.
