Task-oriented Prompting: Structuring AI Workflows

Sunil Kumar (), Atreya ‘Chuck’ Chakraborty () and Poojan Patel ()
Additional contact information
Sunil Kumar: Roger Williams University
Atreya ‘Chuck’ Chakraborty: University of Massachusetts System
Poojan Patel: Bryant University

Chapter 7 in Prompt Engineering for Accounting and Finance, 2026, pp 209-255 from Springer

Abstract: Abstract This chapter develops task-oriented prompting as a methodology for structuring AI interactions around multi-step workflows common in accounting and finance. Moving beyond single-turn responses, it introduces prompt chaining and meta prompting as techniques for decomposing complex tasks into sequenced or adaptive processes. Prompt chaining enables structured execution of defined steps such as reconciliation, valuation modeling, audit testing, and financial forecasting, improving transparency and reliability through intermediate outputs. Meta prompting extends this approach by allowing AI systems to dynamically propose or refine prompts, enhancing adaptability in evolving or exploratory tasks. Through applied examples in financial analysis, audit planning, consolidation, and scenario forecasting, the chapter demonstrates how structured workflows reduce logical gaps, improve oversight, and strengthen decision support. By positioning AI as a collaborative workflow assistant rather than a static question-answering tool, this chapter establishes process control and structured reasoning as central competencies in professional AI use.

Keywords: Task-Oriented Prompting; Prompt Chaining; Meta Prompting; AI Workflow Design; Financial Modeling Automation; Audit Process Structuring; Structured AI Decision Support (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-032-11195-1_7

Ordering information: This item can be ordered from
http://www.springer.com/9783032111951

DOI: 10.1007/978-3-032-11195-1_7

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().