Research opportunity · Organizational absorption: Why micro gains do not become macro outcomes
In small Greek firms, does generative AI stay a personal tool or change how teams work?
In short: has this been done?
Related work: Partly addressed. Related studies cover parts of this question; what they leave open is set out below. Only a first-pass search has been done, so it is not yet known whether a fuller search would find a study that does the whole design.
How far checked: First-pass screen only. A first-pass AI web search on 18 October 2026. No deeper check yet. Every search and check so far was done by AI; no person or domain expert has checked them yet.
The searches, the nearest work found and what the search could not reach
This page shows RO-LD03-08 version v1, whose record never changes. It is the current version; if the opportunity is revised, the newer version appears at its main page.
Question
In small firms in Greece outside tourism (for example accounting offices, shops, small manufacturers and software companies), who uses generative AI and for which tasks, and has any firm changed how work is divided, checked or handed over because of it?
Gap type: Untested beyond the original settingUndergraduate thesisLow costRelated work: Partly addressed
Why it matters
LD-03 asks why gains for individual users do not add up to gains for organizations. Its case studies, of Chinese newsrooms, three German organizations and a large software company, find generative AI used as a personal tool, or adopted unevenly, without changes to team work, and the authors of a survey of European public managers describe use without policies. Small firms are absent from this evidence, and the only Greek interview study found concerns hotels. A small case study can show whether the same pattern appears in firms with few staff and no IT department.
Evidence that motivates it
- In 27 interviews in regional Chinese newsrooms, journalists used generative AI frequently in their own tasks, but its use stayed disconnected from team workflows, hindered by structural barriers and a reluctance to share practices, and no formal mechanism coordinated individual use. (LD03-SL-C07 v1.0)
How this study uses it: In regional Chinese newsrooms, journalists used generative AI often in their own tasks, but its use stayed disconnected from team workflows. - In a case study of three German organizations, generative AI was used mainly as a personal assistant rather than changing team processes, the effort of validating its output partly offset efficiency gains, and policies written in response to regulation without regard to actual use led to gaps between policy and practice and to shadow IT. (LD03-SL-C08 v1.0)
How this study uses it: In three German organizations, generative AI was used mainly as a personal assistant rather than changing team processes. - In paired interviews with 54 developers in 27 teams at a large software company committed to AI adoption, the authors identify a 'Productivity Pressure Paradox': management expected rapid productivity gains without supporting learning, which left developers without the time to build the skills that would save time. (LD03-SL-C09 v1.0)
How this study uses it: Developers at a large software company described management expecting rapid gains without supporting learning. - The authors of a survey of 576 public managers in seven EU member states describe public servants using generative AI to draft reports, refine policy proposals and generate content, often without explicit approval or institutional policies, which they call 'shadow use'; the abstract does not say how much of this the survey itself measured. (LD03-SL-C10 v1.0)
How this study uses it: The authors of a survey of public managers in seven EU member states describe public servants using generative AI to draft reports and content, often without explicit approval or institutional policies.
Each claim is shown as it read when this version was published.
A possible design
Case studies of four to six small firms (under 50 staff) in two or three sectors. In each, interview the owner or manager and one or two employees, and ask for recent concrete examples: a task done with AI, who checked it, and whether anyone else's work changed as a result. Where a firm has a written rule or note on AI use, ask to see it. Compare individual and team use across firms with thematic analysis, and say which patterns from the debate's case studies appear here and which do not.
Data needed
Access to four to six firms through personal networks, the university careers office or a local chamber of commerce; about 10 to 15 interviews; consent and anonymisation under the university's ethics procedure.
Feasibility
Undergraduate thesis. Very low; interviews in person or by video call and free transcription software. Owners may describe intended rather than actual use, so interview at least one employee per firm and ask for examples. The findings describe these firms only. RO-LD03-06 asks the related question of policy against practice in larger organizations.
Has this been done?
Partly done already: related work covers some of this question (first-pass screen of 18 October 2026; not yet checked in depth).
One interview study covers owner-managers of small hotels in a Greek tourist destination and their views of ChatGPT, and Finnish theses interview marketing staff in small firms, who start with individual chat tools. Greek surveys report how many firms use AI, not how its use is organised. No interview study was found of small Greek firms outside hospitality that asks whether generative AI changed how teams work. The search was web-based and partial.
How strong this evidence is
- Who searched and checked: no checker is recorded beyond the first-pass screen, which was part of the AI drafting (Claude (SocioLens Project Lead), AI-drafted from the LD-03 debate as an undergraduate-scale project, after the 17 October 2026 reader tests found no opportunity a final-year student could take on). Every check so far was done by AI; no person or domain expert has checked it yet.
- What was read: 2 of the 2 nearest works below were judged from an abstract, summary or search listing only, and 2 have details that could not be confirmed; each is marked. Not every entry says how much of the work was read.
- Where the search could not reach: Screened by four web searches (three in English, one in Greek) on the date shown; neither nearest work could be opened, Greek university repositories were not searched, and management and tourism databases were only reached through web search. Absence of a hit is not proof that the work does not exist.
- Before building a project on it, run your own search in a scholarly database such as Scopus, Web of Science, Google Scholar or SSRN.
Nearest work found
- Koukopoulos, Vrechopoulos and Lazaris, "Managers' perceptions on Generative AI-based services' role in SMEs hotels", International Hospitality Review, doi:10.1108/IHR-06-2025-0057 Judged from an abstract, summary or search listing onlySome details not confirmed
Seen in search results only; the publisher page could not be opened and the publication year is not confirmed. In-depth interviews with hotel owner-managers in a Greek tourist destination about ChatGPT, finding hopes for efficiency and personalisation and worries about cost, training and lost human contact. Hospitality only, and managers only. - Generative AI in SME marketing, thesis in the Finnish Theseus repository (author and title not confirmed) Judged from an abstract, summary or search listing onlySome details not confirmed
Seen in search results only. Eleven interviews with marketing practitioners and AI experts in Finnish small firms; marketers start individually with chat-based tools, and AI built into shared workflows is not yet common. Finland, marketing only.
Search queries used
small and medium enterprises Greece generative AI adoption interviews qualitative studyGreek SMEs generative AI hotel managers interviews International Hospitality Review 2025 "Generative AI"μικρές επιχειρήσεις Ελλάδα τεχνητή νοημοσύνη ποιοτική έρευνα συνεντεύξεις ChatGPT εργαζόμενοιSME marketing practitioners generative AI semi-structured interviews individual chat-based tools Finland
Cite this page
SocioLens project. (2026, October 18). In small Greek firms, does generative AI stay a personal tool or change how teams work? [Research opportunity RO-LD03-08, version v1]. SocioLens. https://sociolens-web.pages.dev/opportunities/ro-ld03-08/v1/
@misc{sociolens_ro_ld03_08_v1,
author = {{SocioLens project}},
title = {In small Greek firms, does generative AI stay a personal tool or change how teams work?},
year = {2026},
date = {2026-10-18},
howpublished = {\url{https://sociolens-web.pages.dev/opportunities/ro-ld03-08/v1/}},
note = {Research opportunity RO-LD03-08, version v1}
}The link points to this version, whose record never changes. For a finding, cite the original study as well: SocioLens summarizes research and does not replace it.
Provenance
RO-LD03-08 v1. Drafted by Claude (SocioLens Project Lead), AI-drafted from the LD-03 debate as an undergraduate-scale project, after the 17 October 2026 reader tests found no opportunity a final-year student could take on on 2026-10-18. Not yet reviewed. Not yet reviewed by a domain expert. This is a research hypothesis, not a finding.