Artificial intelligence in innovation activities: Firm practices and managerial perspectives in Kazakhstan
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DOIhttp://dx.doi.org/10.21511/ppm.24(4).2026.17
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Article InfoVolume 24 2026, Issue #4, pp. 254–273
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Type of the article: Research Article
Abstract
Artificial intelligence (AI) is increasingly used in innovation activities, yet firm-level evidence on variation across innovation stages and organizational conditions remains limited in emerging economies such as Kazakhstan. This study examines AI use among surveyed firms in Kazakhstan, focusing on stage-specific influence, organizational correlates, barriers, reported effects, and managerial perceptions. A cross-sectional voluntary survey yielded a non-probability sample of 93 firms; data were analyzed using descriptive statistics, reliability analysis, Friedman and Wilcoxon tests, exploratory bivariate analysis, multinomial logistic regression, and descriptive review of open-ended recommendations. In the sample, 39.8% reported no AI use in innovation activities; 23.7% used AI frequently or always. Idea generation was rated higher than idea testing and selection (r = .398), although concordance in stage rankings was weak (Kendall’s W = .077). The reported AI-related resource-category count was associated with both occasional (RRR = 6.98) and frequent AI use (RRR = 7.10) relative to no reported AI use in innovation activities. At the same time, firm size and age were not significant. Skills shortages, financial constraints, regulatory uncertainty, and ethical concerns were the leading barriers. Among firms reporting AI use in innovation activities, the most frequently reported effects were greater innovation-process efficiency (46.4%) and improved understanding of industry opportunities and trends (30.4%). The findings provide exploratory firm-level evidence and highlight the relevance of organizational resource support, pilot-based implementation, and human oversight.
Acknowledgment
This research was funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP23487651).
The authors sincerely thank JSC "Center for International Programs" and the "500 Scientists" research internship program of the Republic of Kazakhstan. A. Zhidebekkyzy's participation in the "500 Scientists" program provided a valuable academic environment that inspired the initial idea for this study.
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JEL Classification (Paper profile tab)O32, M15, O33
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References56
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Tables7
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Figures3
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- Figure 1. Sample screening and key-informant selection process
- Figure 2. Corporate AI adoption profile: Use intensity, budget allocation, and perceived influence of AI on firm profitability
- Figure 3. Reported organizational purposes of AI use among surveyed firms (%)
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- Table 1. Characteristics of the surveyed firms and managerial informants
- Table 2. AI-related organizational resources reported by surveyed firms
- Table 3. Perceived AI influence across innovation stages: Descriptive statistics and Friedman test results
- Table 4. Multinomial logistic regression of AI-use intensity
- Table A1. Pairwise comparisons of perceived AI influence across innovation stages
- Table A2. Firm-level barriers, reported effects, and future plans for AI Use in innovation activities
- Table A3. Managers’ industry-level perceptions and assessments of AI
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