Generative AI has capabilities that go beyond simple chatbots with normal query-answering features to write essays, debug codes, and explain complex topics.
According to GlobalData, the technology gains investor attention to find new applications such as data augmentation, product development, and risk management across sectors.
Kiran Raj, practice head of disruptive tech at GlobalData, says: “Generative AI has expanded beyond the conventional use of AI for tasks such as malware detection, recommendation engines, and forecasting models to create new content such as text, code, image, simulations, and video based on the user text input (text-to-x), opening up a broad spectrum of use cases across various industries.”
Saurabh Daga, associate project manager of disruptive tech at GlobalData, adds that the generative AI space is witnessing a two-pronged growth: on one hand, we see an evolving application landscape across sectors, and on the other hand a continuous improvement in AI models with a shift towards multimodality.
He pointed out that OpenAI’s recently released generative pre-trained transformer 4 (GPT-4) goes beyond its predecessor GPT-3.5 to accept images as a part of the input prompt.
The GlobalData report, “Text-to-X: how ChatGPT and generative AI can transform the future of business,” highlights the recent developments on how generative AI can be a transformational technology for enterprises with key use cases such as advanced search, content generation, customer management, and data augmentation.
“The growing interest in generative AI has caught the attention of technology regulators, who want to curb its potential misuse. Enterprises should also be mindful of several potential drawbacks associated with the use of this technology."
Saurabh Daga
He cautioned that although generative AI can offer useful content, it is an energy-intensive technology and not suited for tasks that require understanding, planning, and problem-solving.
"Moreover, it suffers from the inherent biases in the models it is trained on. Nevertheless, proper governance and regulatory mechanisms can ensure that the potential of generative AI technologies is realized fully,” he concluded.
