The scenario describes a common challenge in AI projects: identifying the appropriate level of technology for different tasks. The project team correctly identifies that not all tasks require advanced cognitive AI. For tasks that are repetitive, rule-based, and do not require complex decision-making or learning, traditional automation solutions like Robotic Process Automation (RPA) are more efficient, cost-effective, and simpler to implement. Therefore, after segregating tasks based on cognitive requirements, the logical and prudent consideration is to utilize traditional automation for the noncognitive tasks. This "right-tool-for-the-job" approach optimizes resource allocation and reduces unnecessary project complexity.

A. This is too general; the key insight is that not all tasks need intelligent functionalities, making this an incomplete consideration.

B. This is counter-intuitive and inefficient. Applying complex AI to noncognitive tasks is a form of over-engineering that increases cost and complexity without adding value.

D. This assessment is a prerequisite for or part of the task segregation already being performed, not the next consideration after segregation has begun.

1. Van der Aalst, W. M., Bichler, M., & Heinzl, A. (2018). Robotic Process Automation. Business & Information Systems Engineering, 60(4), 269-272. In Section 2, "What is RPA?", the authors explicitly state, "RPA is intended for automating repetitive, rule-based tasks... It is important to distinguish RPA from other technologies such as Business Process Management (BPM) and Artificial Intelligence (AI)." This supports the segregation of tasks and using traditional automation (RPA) for appropriate workloads. (DOI: https://doi.org/10.1007/s12599-018-0542-4)

2. Agostinelli, S., Marrella, A., & Mecella, M. (2020). Research Challenges for Intelligent Robotic Process Automation. In Engineering Intelligent Systems (pp. 141-155). Springer, Cham. Section 2, "Background," distinguishes between RPA for "repetitive and deterministic processes" and Intelligent Process Automation (IPA) which incorporates AI for tasks requiring "cognitive capabilities." This distinction justifies using traditional automation for noncognitive tasks. (DOI: https://doi.org/10.1007/978-3-030-37038-99)

3. Lacity, M., & Willcocks, L. (2017). A new approach to automating services. MIT Sloan Management Review, 59(1), 1-17. The article discusses the spectrum of automation, from basic RPA for structured data and rule-based processes to cognitive automation (AI) for unstructured data and judgment-based tasks. It advocates for a pragmatic approach, applying the right level of automation to the right task, which directly supports the action in option C. (Available at: https://sloanreview.mit.edu/article/a-new-approach-to-automating-services/)