  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.
