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arxiv: 2606.25525 · v1 · pith:D4N7THXAnew · submitted 2026-06-24 · 💻 cs.SE · cs.AI

The impact of artificial intelligence on enterprise software user roles

Isabel Unger , Elizangela Valarini , Martin Schrepp , Nina Hollender , Gabriela Rocha , Erik Bertram This is my paper

Pith reviewed 2026-06-25 20:10 UTC · model grok-4.3

classification 💻 cs.SE cs.AI
keywords artificial intelligenceuser rolesenterprise softwarehuman-AI collaborationagentic AIqualitative studyrole taxonomySAP BTP
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The pith

AI is automating operational tasks in enterprise software development while expanding human-AI collaboration and reliance on agentic systems, which requires updating existing role frameworks such as the BTP User Type Matrix.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This qualitative study examines how artificial intelligence changes professional responsibilities in enterprise software development on SAP's Business Technology Platform. Through expert interviews and a participatory workshop, it finds that day-to-day tasks are shifting due to automation of operational work, more human-AI collaboration, and greater use of agentic AI. These changes mean existing role frameworks need updates to reflect the new workforce landscape. The findings point to the need for revised taxonomies, new oversight functions, and different design approaches for AI-native systems. A sympathetic reader would care because it describes a real transition in how software work is organized and who does what.

Core claim

The results reveal substantial shifts in day-to-day tasks and roles in the development domain, characterized by increasing automation of operational tasks, expanding human-AI collaboration, and growing reliance on agentic AI systems. The study further identifies significant implications for existing user-role frameworks, such as the BTP User Type Matrix, which requires adaptation as the workforce is undergoing significant role specific changes.

What carries the argument

The BTP User Type Matrix, an existing role taxonomy whose adaptation is required to accommodate AI-driven changes in tasks, responsibilities, and human-AI collaboration patterns.

If this is right

  • Existing user-role frameworks require adaptation to reflect the new division of labor.
  • New governance and oversight functions become necessary in enterprise software teams.
  • Design approaches for AI-native enterprise software systems must be revised.
  • The workforce undergoes significant role-specific changes that affect daily responsibilities.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar patterns of role change may appear in other enterprise platforms that adopt comparable AI tools.
  • Organizations may need new training programs focused on overseeing and collaborating with agentic AI.
  • The observed trends suggest that role taxonomies in general will need periodic revision as AI capabilities advance.

Load-bearing premise

The views expressed by the 20 interviewed experts and 24 workshop participants accurately represent the broader population of BTP users and that the qualitative themes generalize beyond this single platform and sample.

What would settle it

A large-scale survey or observational study of BTP users that finds no measurable increase in automation of operational tasks or shift toward agentic AI collaboration would undermine the central claim.

Figures

Figures reproduced from arXiv: 2606.25525 by Elizangela Valarini, Erik Bertram, Gabriela Rocha, Isabel Unger, Martin Schrepp, Nina Hollender.

Figure 1
Figure 1. Figure 1: Visualization of the BTP User Type Matrix1 3.2 Objective and Research Questions The objective of this research is to gain a comprehensive understanding of how AI is reshaping the nature of work for professionals in the software development domain. To this objective, the study aims to: (1) Delineate the current state of AI adoption by characterizing its day-to-day usage across various roles in the context o… view at source ↗
read the original abstract

Artificial Intelligence (AI) is rapidly reshaping the nature of work in software development, transforming user roles, workflows, and collaboration patterns across enterprise platforms. This qualitative study investigates how AI alters professional responsibilities within the context of SAP's Business Technology Platform (BTP), combining expert interviews (n=20) and a participatory workshop (n=24). The results reveal substantial shifts in day-to-day tasks and roles in the development domain, characterized by increasing automation of operational tasks, expanding human-AI collaboration, and growing reliance on agentic AI systems. The study further identifies significant implications for existing user-role frameworks, such as the BTP User Type Matrix, which requires adaptation as the workforce is undergoing significant role specific changes. Collectively, these findings highlight a workforce landscape in transition and underscore the need for revised role taxonomies, new governance and oversight functions, and updated design approaches for AI-native enterprise software systems.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The paper reports a qualitative study of AI's effects on user roles in SAP Business Technology Platform (BTP) development, drawing on 20 expert interviews and a participatory workshop with 24 participants. It claims substantial shifts in day-to-day tasks, including automation of operational work, expanded human-AI collaboration, and increased reliance on agentic AI systems, with consequent implications for existing frameworks such as the BTP User Type Matrix that require adaptation.

Significance. The topic is timely for software engineering. If the themes are shown to be robust and transferable, the work could usefully inform revisions to role taxonomies and governance practices in AI-native enterprise platforms. The current manuscript, however, supplies insufficient methodological detail to allow readers to assess the strength or scope of those themes.

major comments (2)
  1. [Abstract/Methods] Abstract and (presumed) Methods section: the study reports n=20 interviews and n=24 workshop participants but supplies no information on sampling frame, interview protocol, coding scheme, inter-rater reliability, or saturation criteria. These omissions leave the central claims of 'substantial shifts' and 'requires adaptation' only weakly anchored.
  2. [Results/Discussion] Results and Discussion: statements about implications 'across enterprise platforms' and a 'workforce landscape in transition' rest on a single-platform (SAP BTP) convenience sample of 44 individuals. Without explicit transferability arguments or cross-platform comparison data, the generalization from this sample to broader enterprise software user roles is not supported.
minor comments (1)
  1. [Abstract] The abstract would benefit from a single sentence stating the primary data-analysis approach (e.g., thematic analysis) to orient readers before the findings are presented.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive feedback, which highlights important areas for improving methodological transparency and the scope of our claims. We address each major comment below.

read point-by-point responses

  1. Referee: [Abstract/Methods] Abstract and (presumed) Methods section: the study reports n=20 interviews and n=24 workshop participants but supplies no information on sampling frame, interview protocol, coding scheme, inter-rater reliability, or saturation criteria. These omissions leave the central claims of 'substantial shifts' and 'requires adaptation' only weakly anchored.

    Authors: We agree that additional methodological detail is needed to allow readers to evaluate the study. In the revised manuscript we will expand the Methods section to describe the sampling frame and participant recruitment, the semi-structured interview protocol, the thematic coding approach and scheme, any inter-rater reliability procedures employed, and the saturation criteria applied during analysis. revision: yes

  2. Referee: [Results/Discussion] Results and Discussion: statements about implications 'across enterprise platforms' and a 'workforce landscape in transition' rest on a single-platform (SAP BTP) convenience sample of 44 individuals. Without explicit transferability arguments or cross-platform comparison data, the generalization from this sample to broader enterprise software user roles is not supported.

    Authors: The study is explicitly situated within the SAP BTP context. We will revise the abstract, results, and discussion to qualify the scope of the findings more precisely, add an explicit transferability subsection that articulates the platform characteristics that may support analogous role shifts elsewhere, and remove or soften language that implies broader generalization without supporting evidence. revision: partial

Circularity Check

0 steps flagged

No circularity: empirical qualitative study with no derivations or fitted predictions

full rationale

The paper reports results from 20 expert interviews and a 24-participant workshop on AI impacts in SAP BTP. It contains no equations, no parameter fitting, no predictions derived from models, and no self-citation chains used to justify central claims. All load-bearing statements are grounded in the collected qualitative data rather than reducing to inputs by construction. This matches the default expectation for non-circular empirical work.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the assumption that a modest number of expert interviews and one workshop yield representative insights into role change; no free parameters, new entities, or non-standard mathematical axioms are introduced.

axioms (1)
  • domain assumption Expert interviews and participatory workshops produce valid and generalizable descriptions of role changes induced by AI.
    The study draws its conclusions directly from the n=20 interviews and n=24 workshop without additional validation steps described in the abstract.

pith-pipeline@v0.9.1-grok · 5691 in / 1319 out tokens · 27260 ms · 2026-06-25T20:10:14.142641+00:00 · methodology

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