Interactive AI

In the context of digital workplaces, chatbots are commonly used in just about all sectors, most significantly in the healthcare industry when Covid-19 hit, to handle the massive influx of questions from the public. In all sectors, AI chatbots can enable workers to access the information needed to complete their work.

According to Gartner, 70% of white-collar workers will interact with chatbot platforms daily by the end of 2022.3 Similar to customer service applications, these platforms can provide immediate information and answers to office workers, helping the organization disseminate details about change management, human resources, helpdesk support, general services, anomaly reporting, and organizing meetings.

For logistics operations, chatbots can streamline inventory handling and management, cargo tracking, and delivery schedules, as well as customer relationship management (CRM) and warehouse management system (WMS) updates. The adoption of interactive AI technology within the supply chain automates workflows and order management, freeing up operations employees to focus on more complex and value-adding tasks. In the event of a chatbot being unable to complete an enquiry, it assigns the task to a human for further action while notifying the requestor about this status.

Analytics of data captured on an interactive AI platform can provide valuable insights to the business. For example, companies may better understand customer pain points and consumer behavior patterns, enabling more effective marketing campaigns to attract potential leads. Data analytics can help with price optimization and – for retailers – better in-store and web-based layout mapping based on behavioral data. It can also help retailers and e-commerce businesses efficiently manage the supply chain while ensuring supply and demand are met at operational level.

Start-up vendors delivering sales and marketing intelligence as well as acceleration software tools like Groove and UpLead enable companies to reach their full potential through interactive AI. In recent years, we’ve all become familiar with AI assistants – for example, Amazon’s Alexa which provides consumers with an AI-powered cloud-based voice service accessing hundreds of millions of devices including third-party device manufacturers.

Data captured through Alexa and similar devices enables more individually targeted marketing, with algorithms to analyze consumer behavior. Meta’s chatbot BlenderBot accumulates user data to tailor its responses in accordance with the user’s history, tapping into the vast library of human thought on the internet. The device is trained on large language datasets, allowing it to generate with factual accuracy passably human responses to questions. In the long term, the purpose and goal of this chatbot is a virtual assistant capable of responding to a wide variety of topics with factual intelligence.