When Does AI Capability Convert to Advantage? A Complementarity-Gated Framework for Startups in Resource-Constrained Economies

Authors

  • Mwita Wanyancha Nelson Mandela African Institution of Science and Technology image/svg+xml Author https://orcid.org/0009-0009-7416-9531
    • Writing – Review & Editing
    • Writing – Original Draft Preparation
    • Visualization
    • Validation
    • Supervision
    • Resources
    • Project Administration
    • Methodology
    • Investigation
    • Formal Analysis
    • Data Curation
    • Conceptualization
  • Moureen Lembris Mollel Author https://orcid.org/0009-0001-0488-3643
    • Investigation
    • Project Administration
    • Supervision
    • Writing – Review & Editing
    • Resources

DOI:

https://doi.org/10.70715/jitcai.2026.v3.i4.091

Keywords:

Artificial intelligence capability, emerging economies, Competitive Advantage, startup performance

Abstract

Purpose: This paper develops a conceptual framework linking artificial intelligence (AI) capability, competitive advantage, and startup performance in emerging economies, addressing the limited and fragmented understanding of how AI capability translates into venture outcomes in resource-constrained contexts.
Design/methodology/approach: The paper employs a structured review of empirical and theoretical literature, grounded in the resource-based view (RBV) and the dynamic capabilities perspective. It synthesizes evidence across studies to identify points of convergence, divergence, and unresolved tension, and on this basis derives a set of testable propositions.
Findings: The review shows that AI capability is a multidimensional construct whose translation into competitive advantage is conditional rather than automatic: it depends on complementary resources such as digital skills, infrastructure, organizational and absorptive capacity, and strategic alignment that are systematically scarce in emerging-economy startups. The paper advances a framework in which competitive advantage mediates the AI capability–performance relationship, but in which that mediating pathway is itself gated by the availability of complementary resources, making the capability–advantage link contingent on context rather than a general regularity.
Originality: The paper's contribution is not that AI capability requires complements, a point established in prior literature, but that it formalises where complementarity binds: not on the path from advantage to performance, where most mediation literature locates contingency, but on the prior path from capability to advantage itself. It specifies this as three concrete, measurable gating conditions: digital infrastructure, founder AI literacy, and ecosystem support, rather than treating resource scarcity as unmodelled context. This repositions AI capability from a resource assumed to convert into advantage into one whose conversion is itself the object of theoretical and empirical explanation, with the moderated pathway as the paper's central, testable claim.

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Author Biography

  • Moureen Lembris Mollel

    I am a Tanzanian innovation, product, and programmes leader with more than seven years of experience designing, building, and scaling entrepreneurship and digital-innovation initiatives across Tanzania and the wider East African region. I currently serve as Ecosystem & Communications Manager (Policy & Advocacy) at the Tanzania Startup Association (TSA), Tanzania's national member-based association for the startup and innovation ecosystem. In this role, I convene multi-stakeholder platforms linking startups, policymakers, development partners, and private-sector actors; lead startup-policy advocacy that strengthens the enabling environment for innovation and entrepreneurship nationally; and build the public-sector and institutional partnerships needed to scale new solutions.

    My research interests centre on entrepreneurship-ecosystem development in emerging markets, and specifically on the structural and linguistic barriers that limit entrepreneurial participation. I hold an MSc in Entrepreneurship and Innovation from the University of Sussex (United Kingdom), completed as a Chevening Scholar (2024-25 cohort), with a focus on digital transformation, innovation management, Design Thinking and strategic leadership. My thesis, "Bridging the Divide: How Swahili-language resources can boost entrepreneurial success in Tanzania," examined how the near-total dominance of English-language business, financial, and digital-skills resources constrains entrepreneurial capability among Swahili-first populations, and what localisation strategies could close that gap. This work anchors the themes I continue to pursue: language and access in entrepreneurship support; human-centred design (HCD) and design-thinking as methodologies for translating user and market insight into market-ready products and programmes; digital and financial-services innovation; gender-inclusive entrepreneurship support; and innovation-policy design for under-resourced ecosystems. My earlier BSc in General Science (Biology major, Chemistry minor), Open University of Tanzania (2016-2020), gave me an early grounding in structured, evidence-based analysis that has carried into the monitoring, evaluation, and learning (MEL) work underpinning every programme I have led since.

    My career spans both financial-services and ecosystem-support institutions. At CRDB Bank Plc, as Business Transformation Coordinator, I supported enterprise-wide transformation initiatives, conducted market research and data-driven assessments, and contributed to the bank's medium-term (3-5 year) strategy. At Ennovate Ventures, as Head of Programs, I built the Difigy digital-skills programme end-to-end, reaching more than 1,000 youth since 2020 through a human-centred design approach, and contributed to ecosystem learning and innovation mapping through initiatives such as the AfriLabs Learning Week. At the Westerwelle Foundation (Startup Haus Arusha), as Programme Coordinator, I mobilised approximately EUR 187,000 from international partners - including YY Ventures, the Friedrich Naumann Foundation, and the Embassy of the Netherlands - to design and deliver the Imarisha, AfroGreen 2.0, and DigiTalents programmes for youth and women entrepreneurs, with training delivered across Mwanza, Mbeya, Zanzibar, Dar es Salaam, and Arusha. At Anza Entrepreneurs, as Fundraising and Partnerships Manager, I designed fundraising and partnership strategies for early-stage ventures, delivered accelerator training under the Pesatech Startup Accelerator, and led a communications strategy that materially strengthened the organisation's digital presence and ecosystem engagement. I have also provided pro bono strategic, fundraising, and impact-tracking support to Mrembo Naturals, a Tanzanian social enterprise, and mentored a Tanga-based startup through the INCO Mawimbi Programme.

    Beyond my primary employment, I contribute to regional innovation governance and knowledge-sharing as Curator of the Arusha hub of the Global Shapers Community (a World Economic Forum initiative), as a Learning Facilitator for AfriLabs' regional programmes, and as a Gender Track contributor at the AfriLabs Annual Gathering in Kigali. My leadership practice began with AIESEC, where I served as Local Chapter President in Tanzania and, in 2018, led an international volunteer cohort on a community-education project that reached over 200 children and ten families in Tanzania. I am fluent in both English and Kiswahili (reading, writing, and speaking) - a bilingual foundation that directly informs my research interest in localisation and language access within entrepreneurship-support systems. I am based in Arusha, Tanzania, and remain committed to advancing inclusive, evidence-based entrepreneurship and innovation policy that expands economic opportunity for youth and women across Tanzania and East Africa.

References

[1] P. Mikalef and M. Gupta, ‘Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance’, Information & Management, vol. 58, no. 3, p. 103434, Apr. 2021, doi: 10.1016/j.im.2021.103434. DOI: https://doi.org/10.1016/j.im.2021.103434

[2] J. Barney, ‘Firm Resources and Sustained Competitive Advantage’, Journal of Management, vol. 17, no. 1, pp. 99–120, Mar. 1991, doi: 10.1177/014920639101700108. DOI: https://doi.org/10.1177/014920639101700108

[3] B. Wernerfelt, ‘A Resource-Based View of the Firm’, Strategic Management Journal, vol. 5, no. 2, Art. no. 2, 1984. DOI: https://doi.org/10.1002/smj.4250050207

[4] K. M. Eisenhardt and J. A. Martin, ‘Dynamic Capabilities: What Are They?’, Strategic Management Journal, vol. 21, no. 10/11, pp. 1105–1121, 2000. DOI: https://doi.org/10.1002/1097-0266(200010/11)21:10/11<1105::AID-SMJ133>3.0.CO;2-E

[5] D. J. Teece, ‘Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance’, Strategic Management Journal, vol. 28, no. 13, pp. 1319–1350, Dec. 2007, doi: 10.1002/smj.640. DOI: https://doi.org/10.1002/smj.640

[6] D. J. Teece, G. Pisano, and A. Shuen, ‘Dynamic Capabilities and Strategic Management’, Strategic Management Journal, vol. 18, no. 7, Art. no. 7, 1997. DOI: https://doi.org/10.1002/(SICI)1097-0266(199708)18:7<509::AID-SMJ882>3.0.CO;2-Z

[7] D. J. Teece, ‘Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy’, Research Policy, vol. 15, no. 6, pp. 285–305, Dec. 1986, doi: 10.1016/0048-7333(86)90027-2. DOI: https://doi.org/10.1016/0048-7333(86)90027-2

[8] W. M. Cohen and D. A. Levinthal, ‘Absorptive Capacity: A New Perspective on Learning and Innovation’, Administrative Science Quarterly, vol. 35, no. 1, p. 128, Mar. 1990, doi: 10.2307/2393553. DOI: https://doi.org/10.2307/2393553

[9] J. B. Barney and W. S. Hesterly, Strategic Management and Competitive Advantage: Concepts. Pearson Prentice Hall, 2008.

[10] N. Cardeal, ‘Valuable, rare, inimitable resources and organization (VRIO) resources or valuable, rare, inimitable resources (VRI) capabilities: What leads to competitive advantage?’, Afr. J. Bus. Manage., vol. 6, no. 37, Sep. 2012, doi: 10.5897/AJBM12.295. DOI: https://doi.org/10.5897/AJBM12.295

[11] D. J. Teece, ‘Hand in Glove: Open Innovation and the Dynamic Capabilities Framework’, Strategic Management Review, vol. 1, no. 2, pp. 233–253, Jun. 2020, doi: 10.1561/111.00000010. DOI: https://doi.org/10.1561/111.00000010

[12] A. S. Bharadwaj, ‘A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation1’, MIS Quarterly, vol. 24, no. 1, pp. 169–196, Mar. 2000, doi: 10.2307/3250983. DOI: https://doi.org/10.2307/3250983

[13] P. Mikalef, S. O. Fjørtoft, and H. Y. Torvatn, ‘Developing an Artificial Intelligence Capability: A Theoretical Framework for Business Value’, in Business Information Systems Workshops, vol. 373, W. Abramowicz and R. Corchuelo, Eds, in Lecture Notes in Business Information Processing, vol. 373. , Cham: Springer International Publishing, 2019, pp. 409–416. doi: 10.1007/978-3-030-36691-9_34. DOI: https://doi.org/10.1007/978-3-030-36691-9_34

[14] P. Mikalef et al., ‘Examining how AI capabilities can foster organizational performance in public organizations’, Government Information Quarterly, vol. 40, no. 2, p. 101797, Apr. 2023, doi: 10.1016/j.giq.2022.101797. DOI: https://doi.org/10.1016/j.giq.2022.101797

[15] Y. Gao, S. Liu, and L. Yang, ‘Artificial intelligence and innovation capability: A dynamic capabilities perspective’, International Review of Economics & Finance, vol. 98, p. 103923, Mar. 2025, doi: 10.1016/j.iref.2025.103923. DOI: https://doi.org/10.1016/j.iref.2025.103923

[16] S.-L. Wamba-Taguimdje, S. F. Wamba, J. R. K. Kamdjoug, and C. E. T. Wanko, ‘Impact of Artificial Intelligence on Firm Performance: Exploring the Mediating Effect of Process-Oriented Dynamic Capabilities’, in Digital Business Transformation, vol. 38, R. Agrifoglio, R. Lamboglia, D. Mancini, and F. Ricciardi, Eds, in Lecture Notes in Information Systems and Organisation, vol. 38. , Cham: Springer International Publishing, 2020, pp. 3–18. doi: 10.1007/978-3-030-47355-6_1. DOI: https://doi.org/10.1007/978-3-030-47355-6_1

[17] A. A. Alhelal, A. A. Alshiha, and B. S. Al-Romeedy, ‘AI-Driven Sustainable Competitive Advantage in Tourism and Hospitality: Mediating Roles of Digital Culture and Skills’, Sustainability, vol. 17, no. 19, p. 8903, Oct. 2025, doi: 10.3390/su17198903. DOI: https://doi.org/10.3390/su17198903

[18] L. Ardito, R. Filieri, E. Raguseo, and C. Vitari, ‘Artificial intelligence adoption and revenue growth in European SMEs: synergies with IoT and big data analytics’, Internet Research, vol. 35, no. 4, pp. 1508–1534, Nov. 2025, doi: 10.1108/INTR-02-2024-0195. DOI: https://doi.org/10.1108/INTR-02-2024-0195

[19] A. Cimino, V. Corvello, C. Troise, A. Thomas, and M. Tani, ‘Artificial Intelligence Adoption for Sustainable Growth in SMES : An Extended Dynamic Capability Framework’, Corp Soc Responsibility Env, vol. 32, no. 5, pp. 6120–6138, Sep. 2025, doi: 10.1002/csr.70019. DOI: https://doi.org/10.1002/csr.70019

[20] F. Ul Haq, N. M. Suki, H. Zaigham, A. Masood, and A. Rajput, ‘Exploring AI Adoption and SME Performance in Resource-Constrained Environments: A TOE–RBV Perspective with Mediation and Moderation Effects’, Journal of Digital Economy, p. S2773067025000330, Jul. 2025, doi: 10.1016/j.jdec.2025.07.002. DOI: https://doi.org/10.1016/j.jdec.2025.07.002

[21] C. A. Gunawan and G. Ongkowijoyo, ‘Assessing the Mediating Role of Competitive Advantage: The Influence of Innovation Capabilities and Strategic Flexibility on Firm Performance in East Java’s F&B Industry Post COVID-19’, Dinasti International Journal of Economics, Finance & Accounting, vol. 6, no. 1, pp. 516–534, Mar. 2025, doi: 10.38035/dijefa.v6i1.4004. DOI: https://doi.org/10.38035/dijefa.v6i1.4004

[22] M. Novitasari and D. Agustia, ‘Competitive advantage as a mediating effect in the impact of green innovation and firm performance’, Business: Theory and Practice, vol. 24, no. 1, pp. 216–226, May 2023, doi: 10.3846/btp.2023.15865. DOI: https://doi.org/10.3846/btp.2023.15865

[23] Z. Zahara, M. Muslimin, A. Rumijati, and Z. T. Rony, ‘Competitive Advantage as Mediating Role to Enhance MSMES Performance’, Journal of Small Business Strategy, vol. 34, no. 2, Sep. 2024, doi: 10.53703/001c.121131. DOI: https://doi.org/10.53703/001c.121131

[24] E. A. Gani, C. Herdinata, and L. Dewi, ‘Digital Transformation on Competitive Advantage through Customer Experience in Indonesian Companies’, JIMKES, vol. 13, no. 6, pp. 4321–4334, Nov. 2025, doi: 10.37641/jimkes.v13i6.3978. DOI: https://doi.org/10.37641/jimkes.v13i6.3978

[25] K. Kiyabo and N. Isaga, ‘Strategic entrepreneurship, competitive advantage, and SMEs’ performance in the welding industry in Tanzania’, J Glob Entrepr Res, vol. 9, no. 1, p. 62, Dec. 2019, doi: 10.1186/s40497-019-0188-9. DOI: https://doi.org/10.1186/s40497-019-0188-9

[26] N. Venkatraman and V. Ramanujam, ‘Measurement of Business Performance in Strategy Research: A Comparison of Approaches’, The Academy of Management Review, vol. 11, no. 4, p. 801, Oct. 1986, doi: 10.2307/258398. DOI: https://doi.org/10.2307/258398

[27] J. Dawes, ‘The Relationship between Subjective and Objective Company Performance Measures in Market Orientation Research: Further Empirical Evidence’, 1999, [Online]. Available: http://marketing-bulletin.massey.ac.nz/v10/mb_v10_n3_dawes.pdf

[28] D. Welbotha and C. van den Berg, ‘Big Data Analytics Capabilities and the Organisational Performance of South African Retailers’, South African Computer Journal, vol. 36, no. 2, 2024, doi: 10.18489/sacj.v36i2.17937. DOI: https://doi.org/10.18489/sacj.v36i2/17937

[29] F. M. Omambia, ‘Artificial Intelligence (AI) And Financial Performance of the Financial Service Industry in Kenya’, AJOCS, vol. 6, no. 4, pp. 86–94, Jul. 2025, doi: 10.59413/ajocs/v6.i4.8. DOI: https://doi.org/10.59413/ajocs/v6.i4.8

[30] National Council for Artificial Intelligence, ‘Egypt National Artificial Intelligence Strategy: Second Edition (2025–2030)’, Ministry of Communications and Information Technology (MCIT), Cairo, Egypt, 2025. [Online]. Available: https://ai.gov.eg/SynchedFiles/en/Resources/AIstrategy%20English%2016-1-2025-1.pdf

[31] D. Hanyurwimfura, ‘Rwanda: Advancing Science Through the Development of Artificial Intelligence’, in Preparing National Research Ecosystems for AI: Third Edition, D. Castle, V. McBride, and J. Randles, Eds, International Science Council, 2026. [Online]. Available: https://council.science/wp-content/uploads/2026/02/Rwanda-AI.pdf

[32] Tanzania Startup Association, ‘Tanzania Startup Ecosystem Status Report 2025’, Tanzania Startup Association, Dar es Salaam, Annual Ecosystem Report, 2025. [Online]. Available: https://www.tsa.co.tz

[33] D. Utonga, C. S. Tundui, and E. Mkuna, ‘Harnessing performance through digital technology adoption: an empirical analysis of SMEs in the Tanzanian fruit juice processing industry’, Cogent Business & Management, vol. 13, no. 1, p. 2612771, Dec. 2026, doi: 10.1080/23311975.2026.2612771. DOI: https://doi.org/10.1080/23311975.2026.2612771

[34] Md. A. I. Gazi et al., ‘AI Capability and Sustainable Performance: Unveiling the Mediating Effects of Organizational Creativity and Green Innovation with Knowledge Sharing Culture as a Moderator’, Sustainability, vol. 16, no. 17, p. 7466, Aug. 2024, doi: 10.3390/su16177466. DOI: https://doi.org/10.3390/su16177466

[35] J. F. Hair, J. J. Risher, M. Sarstedt, and C. M. Ringle, ‘When to use and how to report the results of PLS-SEM’, EBR, vol. 31, no. 1, pp. 2–24, Jan. 2019, doi: 10.1108/EBR-11-2018-0203. DOI: https://doi.org/10.1108/EBR-11-2018-0203

[36] P. M. Podsakoff, S. B. MacKenzie, J.-Y. Lee, and N. P. Podsakoff, ‘Common method biases in behavioral research: A critical review of the literature and recommended remedies.’, Journal of Applied Psychology, vol. 88, no. 5, pp. 879–903, 2003, doi: 10.1037/0021-9010.88.5.879. DOI: https://doi.org/10.1037/0021-9010.88.5.879

[37] E. Roemer, F. Schuberth, and J. Henseler, ‘HTMT2–an improved criterion for assessing discriminant validity in structural equation modeling’, IMDS, vol. 121, no. 12, pp. 2637–2650, Nov. 2021, doi: 10.1108/IMDS-02-2021-0082. DOI: https://doi.org/10.1108/IMDS-02-2021-0082

[38] X. Zhao, J. G. Lynch, and Q. Chen, ‘Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis’, J Consum Res, vol. 37, no. 2, pp. 197–206, Aug. 2010, doi: 10.1086/651257. DOI: https://doi.org/10.1086/651257

[39] J. Henseler, C. M. Ringle, and M. Sarstedt, ‘A new criterion for assessing discriminant validity in variance-based structural equation modeling’, J. of the Acad. Mark. Sci., vol. 43, no. 1, pp. 115–135, Jan. 2015, doi: 10.1007/s11747-014-0403-8. DOI: https://doi.org/10.1007/s11747-014-0403-8

[40] K. Abrokwah-Larbi and Y. Awuku-Larbi, ‘The impact of artificial intelligence in marketing on the performance of business organizations: evidence from SMEs in an emerging economy’, JEEE, vol. 16, no. 4, pp. 1090–1117, Jun. 2024, doi: 10.1108/JEEE-07-2022-0207. DOI: https://doi.org/10.1108/JEEE-07-2022-0207

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Published

07/31/2026

Data Availability Statement

No primary data were generated or analysed in this study. The paper is a conceptual, theory-building contribution developed through a structured review of published literature; all sources are cited in the reference list.

Issue

Vol. 3 No. 4 (2026): Emerging Frontiers and Intelligent Solutions in Information Technology, Cybersecurity, and Artificial Intelligence

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Articles

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Copyright (c) 2026 Mwita Wanyancha, Moureen Lembris Mollel (Author)

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2026 Author(s). Authors retain copyright and grant JITCAI the right of first publication. This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) License.

How to Cite

[1]
M. Wanyancha and M. L. Mollel, “When Does AI Capability Convert to Advantage? A Complementarity-Gated Framework for Startups in Resource-Constrained Economies”, Journal of Information Technology, Cybersecurity, and Artificial Intelligence, vol. 3, no. 4, pp. 121–134, Jul. 2026, doi: 10.70715/jitcai.2026.v3.i4.091.

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