AI Connecting Business and Consumers

AIArtificial Intelligence (AI) technology has enabled new roles for machines and enhanced the processing of information by fuelling autonomous characteristics. Not surprisingly then, the potential of AI autonomous agentsAutonomous agents is embraced by brands to easily connect with consumers, to speed up management and operation processing. Entering the transformational era from conventional HCI systems focusing on human interaction with non-AIArtificial Intelligence (AI) computing systems to human interaction with AI systems, companies could see a real upscale. Doing business is facilitated by substituting various manpower activities with human–machine systems mirroring human agency. AI agentsAI agents are developed to exhibit unique behaviour, as well as to demonstrate autonomyAutonomy with certain levels of human-like intelligence abilities. The development of usable and explainable AIArtificial Intelligence (AI) systems as demonstrated in the two models suggested hereby (Chaps. 5 and 7 ) could spark the launch of AI applications that appropriately meet consumer needs and market demand. By assembling human and machine intelligence, AIArtificial Intelligence (AI) technology may augment human capabilities by integrating human roles into human–machine systems. Introducing new channels, however, fosters some new challenges, and thus requires further exploration. For example, understanding under which conditions a mutual trustTrust between humans and AI agentsAI agents will be established is essential. Another puzzling question is whether an AI agentAI agents would be able to take over the controlControl of a system for a human in specific domains and activities. In this respect, it is important to look at the open AIArtificial Intelligence (AI) dialogue generative pre-trained transformer (GPT)Generative Pre-trained Transformer (GPT). Gaining enormous popularity, it is perhaps the most frequently used transformer for conversational AI and natural language generation. The current chapter will address several of these AIArtificial Intelligence (AI) application challenges in an attempt to recommend channel deployment that integrates decision-making systems encompassing interpretable primitives. These should describe the decision-making steps in a human-understandable manner. Furthermore, human-driven decision making should be guaranteed. It is recognised as a success factor in implementing human-centred design processes and is discussed in detail below.