New Research Study Reveals Trends in GenAI Technology Investment

Today, solutions based on AI have largely become widespread and affordable, putting the technology into the hands of smaller businesses who could never have afforded it even just a few years ago.

In this vein, a new study released by ISG Software Research (formerly Ventana Research) has found that GenAI is leading the charge when it comes to making artificial intelligence more accessible and more easily used; at least, for a broader portion of the workforce and general public. The ISG AI Platforms Buyers Guides found that 85% of enterprises say they believe that investment in GenAI technology in the next 24 months is important or critical.

The most common tasks where GenAI is being applied include natural language processing (NLP) such as chatbots, copilots and assistants, extracting information from and summarizing documents, and assisting with software development tasks such as code generation and application migration. GenAI is expected to have a bigger impact in these areas than predictive AI.

As with any new technology, however, there are challenges to companies adopting GenAI-based solutions. The ISG report noted that hiring and retaining experienced AI professionals is the biggest IT resource challenge and the biggest impediment to enterprises adopting AI on a broader scale.

In addition, companies with little experience with the technology may not be certain how to implement it and for which business processes, or even which company to approach as a best fit for their needs.

“Enterprises need objective, independent assessments of AI software providers,” said David Menninger, Executive Director, ISG Software Research. “Capabilities vary widely among these providers. The lack of AI-talented resources makes it even more difficult for enterprises to evaluate which vendors can best meet their needs.”

The study also noted that while the rise of GenAI has been meteoric, enterprises still plan to invest one-half of their AI spend on predictive or traditional AI. Predictive AI is expected to have a bigger impact in areas such as credit risk, fraud detection, algorithmic trading and customer acquisition.