AI Needs Better Connection and Logic
Many companies struggle with AI systems, like e-commerce platforms, that don't share customer data. 'Reasoning' AI that connects signals is a growing trend.
Companies are encountering issues with their artificial intelligence systems, such as e-commerce platforms, failing to share customer information across various channels. This often results in redundant or irrelevant marketing actions, like offering a customer another dishwasher shortly after they have purchased one.
While current AI models can process vast amounts of data and generate content, they may not fully grasp a user's real context and needs. The emerging solution to this challenge lies in 'reasoning engines'—AI systems capable of making logical inferences based on multiple data sources and channels simultaneously.
These systems act as a central nervous system, integrating disparate technology components. For instance, in e-commerce, search functions handle direct queries, recommendation engines predict interests, and marketing systems manage communications. A reasoning layer synthesizes this data for a more cohesive and relevant customer experience.
Applications are already seen in banking for analyzing risk signals and in supply chains for orchestrating decisions. In retail, this enables systems to recognize a customer's past behavior and purchase history, subsequently suggesting suitable complementary products like vacation gear, rather than another appliance.
Businesses are advised to begin building the foundation for this 'connected intelligence' by breaking down data silos, improving data quality, and designing systems around the user's journey, rather than waiting for the technology to become widespread.