In this paper, we describe some abstract features of human/machine interaction systems that are required for the production of intelligent behaviour. We introduce a subset of intelligent systems called human-centered intelligent systems (HCIS) and argue that such systems must be autonomous, robust and adaptive in order to be intelligent. We also propose soft computing as a promising new technique that can be used to build HCIS, and present examples where this is already being done. The paper defines flexibility to be a combination of the often-conflicting requirements of robustness and adaptability, and based on this we claim that the right balance between these two features is necessary to achieve intelligent behaviour. We describe the intelligent assistant (IA) system and its various components which automatically perform helpful tasks for its user, so as to enable the user to improve productivity. These tasks include time, information and communication management. Time management involves planning and scheduling, decision making and learning user habits. Information management involves information seeking and filtering, information fusion, decision making and learning user preferences. Communication management involves recognising user behaviour and learning user priorities. All these tasks depend on many factors including the type of activity, its originator, the mood of the user, past experience, and the priority of the task. The IA uses a multimodal interface with conventional interfaces such as keyboard and mouse enhanced to include vision, speech and natural language processing. The inclusion of such extra modalities extends the capabilities of existing systems at the cost of introducing extra complexity. The IA is 'smart' because it has the knowledge about tasks and the capability to learn and adapt to new interactions with its user and with other systems.