Melola Discovery

← Melola Discovery

Akses terbuka Jurnal

AI Adoption Barriers in SMEs Analyzing Through the Technology Organization Environment TOE Framework

APTISI Transactions on Management (ATM) · Vol. 9 No. 3 (2025) · hlm. 278–289

DOI
10.33050/atm.v9i3.2537
ISSN
2622-6804, 2622-6812
Terbit
2025-10-22
Penerbit
Pandawan
Bahasa
en
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Artificial Intelligence (AI) has become a key driver of innovation, improving efficiency, decision-making, and competitiveness in businesses worldwide. However, the adoption of AI tools among Small and Medium Enterprises (SMEs), especially in developing countries like Indonesia, remains limited. This study aims to explore the barriers hindering AI adoption in SMEs in Indonesia using the Technology Organization Environment (TOE) framework. A survey was conducted among Indonesian SMEs across various sectors to capture their perceptions regarding AI implementation. The survey focused on technological, organizational, and environmental factors that influence AI adoption. The findings reveal that technological barriers, such as high implementation costs and system complexity, are significant challenges for SMEs. Organizational barriers, including limited digital literacy, a lack of skilled workforce, and resistance to change, also hinder AI adoption. Furthermore, environmental barriers like insufficient government support, regulatory uncertainty, and low market pressure constrain SMEs' adoption readiness. This study extends the TOE framework to the context of AI adoption in SMEs in developing economies. Addressing the identified barriers is essential for accelerating digital transformation and enabling SMEs to leverage AI for sustainable growth in the digital economy.

Kata kunci

Jaringan kolaborasi para penulis

22 penulis · 60 tautan kepenulisan bersama

Arahkan kursor atau ketuk sebuah nama untuk menyorot rekan penulisnya. Klik dua kali untuk membuka halaman penulis.

  • Universitas Raharja
  • Afiliasi tidak diketahui
  • Organisasi berbeda
  • Organisasi sama
  • Afiliasi tidak diketahui
  • Garis lebih tebal = lebih banyak artikel bersama · lingkaran lebih besar = lebih banyak artikel
Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Marviola HardiniAfiliasi tidak diketahui2
Dominicus Savio PriyarsonoAfiliasi tidak diketahui2
Anggraini SukmawatiAfiliasi tidak diketahui2
Popong NurhayatiAfiliasi tidak diketahui2
Hilda HildaAfiliasi tidak diketahui1
Aan KaniviaAfiliasi tidak diketahui1
Muhammad Faizal FazriAfiliasi tidak diketahui1
Sabda MaulanaAfiliasi tidak diketahui1
Fitra Putri OgandaUniversitas Raharja1
Aoliyah FirasatiAfiliasi tidak diketahui1
Fadhila AzzahraAfiliasi tidak diketahui1
Sausan Raihana Putri JunaediAfiliasi tidak diketahui1
Amelia EvansAfiliasi tidak diketahui1
Maulana Arif KomaraAfiliasi tidak diketahui1
Yusuf TojiriAfiliasi tidak diketahui1
Nasrul HidayatAfiliasi tidak diketahui1
Cristiano Gatot WagnerAfiliasi tidak diketahui1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://ijc.ilearning.co/ATM/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 6 Nov 2026.
Metadata asli (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">AI Adoption Barriers in SMEs Analyzing Through the Technology Organization Environment TOE Framework</dc:title>
	<dc:creator xml:lang="en">Syahidun</dc:creator>
	<dc:creator xml:lang="en">Susetyono, Eko</dc:creator>
	<dc:creator xml:lang="en">Adiwijaya, Alfri</dc:creator>
	<dc:creator xml:lang="en">Madani, Muchlisina</dc:creator>
	<dc:creator xml:lang="en">Mustafa Kareem, Yasir</dc:creator>
	<dc:subject xml:lang="en">Artificial Intelligence (AI)</dc:subject>
	<dc:subject xml:lang="en">TOE Framework</dc:subject>
	<dc:subject xml:lang="en">SMEs</dc:subject>
	<dc:subject xml:lang="en">Innovation</dc:subject>
	<dc:subject xml:lang="en">Digital Transformation</dc:subject>
	<dc:description xml:lang="en">Artificial Intelligence (AI) has become a key driver of innovation, improving efficiency, decision-making, and competitiveness in businesses worldwide. However, the adoption of AI tools among Small and Medium Enterprises (SMEs), especially in developing countries like Indonesia, remains limited. This study aims to explore the barriers hindering AI adoption in SMEs in Indonesia using the Technology Organization Environment (TOE) framework. A survey was conducted among Indonesian SMEs across various sectors to capture their perceptions regarding AI implementation. The survey focused on technological, organizational, and environmental factors that influence AI adoption. The findings reveal that technological barriers, such as high implementation costs and system complexity, are significant challenges for SMEs. Organizational barriers, including limited digital literacy, a lack of skilled workforce, and resistance to change, also hinder AI adoption. Furthermore, environmental barriers like insufficient government support, regulatory uncertainty, and low market pressure constrain SMEs' adoption readiness. This study extends the TOE framework to the context of AI adoption in SMEs in developing economies. Addressing the identified barriers is essential for accelerating digital transformation and enabling SMEs to leverage AI for sustainable growth in the digital economy.</dc:description>
	<dc:publisher xml:lang="en">Pandawan</dc:publisher>
	<dc:date>2025-10-22</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijc.ilearning.co/ATM/article/view/2537</dc:identifier>
	<dc:identifier>10.33050/atm.v9i3.2537</dc:identifier>
	<dc:source xml:lang="en">APTISI Transactions on Management (ATM); Vol. 9 No. 3 (2025): September; 278-289</dc:source>
	<dc:source xml:lang="id">APTISI Transactions on Management (ATM); Vol 9 No 3 (2025): September; 278-289</dc:source>
	<dc:source>2622-6804</dc:source>
	<dc:source>2622-6812</dc:source>
	<dc:source>10.33050/atm.v10i3</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://ijc.ilearning.co/ATM/article/view/2537/915</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Syahidun, Eko Susetyono, Alfri Adiwijaya, Muchlisina Madani, Yasir Mustafa Kareem (Authors)</dc:rights>
	<dc:rights xml:lang="en">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>