AI has become a game-changer tool in the IT sector. Artificial intelligence and automation have significantly transformed how organizations run their production lines. As AI tools can garner real-time insights, it has facilitated the companies' design and product innovation techniques. When applied correctly, AI and automation can help develop better, faster, and cheaper business techniques. Automation tools can be deployed to automate repetitive tasks, allowing the IT staff to focus on strategic tasks instead of administrative work.
Business process automation is a booming multi-billion-dollar industry that promises to remove menial tasks from workers' plates -- through the introduction of autonomous agents -- and free up their time and brain power for more creative and engaging tasks. However, an essential component to the successful deployment of such autonomous agents is the ability of business users to monitor their performance and customize their execution. A simple and user-friendly interface with a low learning curve is necessary to increase the adoption of such agents in banking, insurance, retail and other domains. As a result, proactive chatbots will play a crucial role in the business automation space. Not only can they respond to users' queries and perform actions on their behalf but also initiate communication with the users to inform them of the system's behavior. This will provide business users a natural language interface to interact with, monitor and control autonomous agents. In this work, we present a multi-agent orchestration framework to develop such proactive chatbots by discussing the types of skills that can be composed into agents and how to orchestrate these agents. Two use cases on a travel preapproval business process and a loan application business process are adopted to qualitatively analyze the proposed framework based on four criteria: performance, coding overhead, scalability, and agent overlap.
Once the stuff of science fiction stories, artificial intelligence (AI) is moving into the mainstream. Practical applications are rapidly emerging and businesses are exploiting AI apps to deliver significant value. In particular, cognitive computing capabilities are now performing many routine, mundane tasks that humans have been saddled with in the past. The real payoff is that cognitive apps are handling those tasks faster and at a lower cost. Examples include customer service bots that walk users through installing software and smart, context-based recommendations that give novice agents the ability to perform like experts.
Successful AI-powered customer service systems will depend on bots working with humans, not replacing them. Customer service is traditionally considered a cost center, so many organizations have focused their customer improvement efforts on reducing costs. This proves to be a critical mistake, as everyone is left unhappy. Even as customers are sick of pressing two for reservations and three for service, service reps are sick of answering the same questions over and over. The latest technology for service is virtual agents: Automated systems, trained on service transcripts, that can use AI to recognize and respond to customer requests whether by phone or chat.