B2C leaders are increasingly focused on developing generative AI tools and agentic solutions. However, the foundational element influencing AI performance is the quality of data used for training, with unstructured data playing a pivotal role. This includes diverse formats such as images, video, speech, and behavioral signals, which are inherently complex but invaluable for AI learning.
Generative AI leverages this messy unstructured data to create more sophisticated and effective models, thus enabling brands to innovate and optimize their operations in new ways. The reliance on unstructured data underscores challenges in data management and integration, which could pose risks if not handled properly. Moreover, organizations need to invest in capabilities to collect, store, and process this data responsibly to maximize AI benefits.
The implications of deploying AI primarily fed by unstructured data extend beyond technical enhancements; they influence customer engagement, personalization strategies, and overall business transformation. Effective use of such data could lead to competitive advantages but also requires managing privacy, quality, and bias concerns.
👉 Pročitaj original: Forrester
