Evidence map›Paper›PMID 42857033›Full record

ArticleFrontiers in artificial intelligence2026

Drivers and barriers of AI tool adoption in Jordanian SMEs: a qualitative TOE-based study.

Hamad Alsawalqah, Yazn Alshamaila, Ons Al-Shamaileh, Ibrahim Aljarah, Ahmad Abadleh, Nailah Al-Madi

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Hamad AlsawalqahKing Abdullah II School of Information Technology, The University of Jordan, Amman, Jordan.
Yazn AlshamailaKing Abdullah II School of Information Technology, The University of Jordan, Amman, Jordan.
Ons Al-ShamailehCollege of Interdisciplinary Studies, Zayed University, Dubai, United Arab Emirates.
Ibrahim AljarahKing Abdullah II School of Information Technology, The University of Jordan, Amman, Jordan.
Ahmad AbadlehDepartment of Computer Science, Mutah University, Al Karak, Jordan.
Nailah Al-MadiComputer Science Department, Princess Sumaya University for Technology, Amman, Jordan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence tools are increasingly used in business. However, small and medium-sized enterprises (SMEs) continue to face challenges in deciding whether to adopt them and how to. This study examines the factors that encourage or hinder the adoption of AI tools by SMEs in the Jordanian context. The study uses the technology-organisation-environment framework (TOE) and draws on 15 semi-structured interviews with AI solution providers, AI adopters, and firms considering adoption. The data was analysed thematically using TOE-guided deductive coding alongside inductive coding. The findings show that technological and organisational factors, including relative advantage, compatibility, managerial support, financial resources, and prior experience, influence AI adoption decisions. Environmental factors, such as competitive pressure, regulation, industry conditions, and public awareness, also affect adoption, but their role differs across firm categories. AI solution providers mainly emphasised expertise, market scope, and client readiness. Adopters focused more on organisational readiness and competitive pressure, while firms considering adoption reported uncertainty, cost, and employee acceptance as prominent barriers. Resistance to change and public awareness also appeared as context-sensitive factors within the organisational and environmental dimensions of TOE. The study provides qualitative evidence from Jordanian SMEs and offers practical implications for SMEs, AI solution providers, and support bodies in Jordan and similar regional contexts. The findings should be read as exploratory and context-specific, not as broad evidence for all SMEs in developing countries.

Indexed as

AI adoptionartificial intelligencedigital transformationsmall and medium-sized enterprises (SMEs)technology organisation environment (TOE) framework

Identifiers

PMID42857033
PMCPMC13649747

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.