This article investigates whether and how government digital incentives enhance enterprise AI capability (AIC) using empirical evidence from Chinese A-share listed enterprises during 2011–2024. By constructing comprehensive indicators to measure enterprise AIC, we explore the impact of subsidy-based (SDI) and policy-based digital incentive (PDI) on enterprise AIC and their underlying mechanisms. The findings reveal that: (a) Both SDI and PDI enhance enterprise AIC, with results remaining robust after robustness tests. (b) SDI positively influence enterprise AIC by alleviating financing constraints (FC), while PDI exert positive effects through optimising resource allocation efficiency. (c) Executive IT background positively moderates the relationship between both types of digital incentives and enterprise AIC. (d) Heterogeneity analysis demonstrates that SDI have significantly stronger effects on enterprise AIC in eastern regions compared to western and central regions, whereas PDI show more pronounced positive effects in central regions compared to eastern and western regions. SDI exert markedly stronger effects in high-tech industries than in non-high-tech industries, while PDI demonstrate greater positive impacts in non-high-tech industries compared to high-tech industries. Compared to non-state-owned enterprises (SOEs), SDI have more significant positive effects on AIC in SOEs, whereas PDI exhibit stronger positive effects on AI capabilities in non-SOEs.
AfchaS., & LucenaA. (2021). The effectiveness of R&D subsidies in fostering firm innovation: The role of knowledge-sourcing activities. BRQ Business Research Quarterly, 24(4), 302–323.
2.
AghionP., AntoninC., & BunelS. (2022). The power of creative destruction: Economic upheaval and the wealth of nations. Harvard University Press.
3.
BabashahiL., BarbosaC. E., LimaY., LyraA., SalazarH., ArgôloM., AlmeidaM. A. D., & SouzaJ. M. D. (2024). AI in the workplace: A systematic review of skill transformation in the industry. Administrative Sciences, 14(6), 127–154.
4.
BalsmeierB., FabbriM., & DelanoteJ. (2019). R&D delegation in IT firms: Evidence from patent data. Research Policy, 48(7), 1643–1655.
5.
BarneyJ. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.
6.
BresnahanT. F., & TrajtenbergM. (1995). General purpose technologies: Engines of growth?Journal of Econometrics, 65(1), 83–108.
ChatterjeeS. (2020). AI strategy of India: Policy framework, adoption challenges and actions for government. Transforming Government: People, Process and Policy, 14(5), 757–775.
9.
ChenK., ChenX., WangZ. A., & ZvarychR. (2024). Does artificial intelligence promote common prosperity within enterprises? Evidence from Chinese-listed companies in the service industry. Technological Forecasting and Social Change, 200, 123180.
10.
CuiH., WenW., TangY., & FengX. (2024). The impact of government policy on enterprise digital transformation: Evidence from China’s national civilized city award. Applied Economics Letters, 33(3), 422–426.
11.
DaiW., & SiS. (2018). Government policies and firms’ entrepreneurial orientation: Strategic choice and institutional perspectives. Journal of Business Research, 93, 23–36.
12.
DengL., & QianP. (2024). Mitigating effect of digital payments on micro-enterprises’ financing constraints. Finance Research Letters, 62, 105209.
13.
DiMaggioP. J., & PowellW. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), 147–160.
14.
FarboodiM., MihetR., PhilipponT., & VeldkampL. (2021). Big data and firm dynamics. American Economic Review, 111(5), 1695–1727.
15.
GaoY., LiuS., & YangL. (2025). Artificial intelligence and innovation capability: A dynamic capabilities perspective. International Review of Economics & Finance, 98, 103923.
16.
HambrickD. C., & MasonP. A. (1984). Upper echelons: The organization as a reflection of its top managers. Academy of Management Review, 9(2), 193–206.
17.
HowellS. T. (2017). Financing innovation: Evidence from R&D grants. American Economic Review, 107(4), 1136–1164.
18.
HuangK. G., & MurrayF. E. (2009). Does patent strategy shape the long-run supply of public knowledge? Evidence from human genetics. Academy of Management Journal, 52(6), 1193–1221.
19.
KimS. H., JeonJ. H., AridiA., & JunB. (2022). Factors that affect the technological transition of firms toward Industry 4.0 technologies. IEEE Access, 11, 1694–1707.
20.
KouJ., ZhangY., & ChenK. (2022). Digital transformation and corporate risk-taking: Evidence from China. Journal of Corporate Finance, 75, 102234.
LiX., & YueS. (2025). Does government digital attention improve China’s digital economy output efficiency: Accelerator or inhibitor?Economic Analysis and Policy, 85, 607–625.
23.
LiX., YueZ., & WuY. (2025). Impacts of financial technology on resource allocation efficiency: A perspective based on distribution differences of inter-enterprise total factor productivity. International Review of Economics & Finance, 99, 104006.
24.
MateutS. (2018). Subsidies, financial constraints and firm innovative activities in emerging economies. Small Business Economics, 50(1), 131–162.
25.
RajaramK., & TinguelyP. N. (2024). Generative artificial intelligence in small and medium enterprises: Navigating its promises and challenges. Business Horizons, 67(5), 629–648.
26.
ShangY., ZhouS., ZhuangD., ŻywiołekJ., & DincerH. (2024). The impact of artificial intelligence application on enterprise environmental performance: Evidence from microenterprises. Gondwana Research, 131, 181–195.
27.
ShaoK., & WangX. (2023). Do government subsidies promote enterprise innovation? Evidence from Chinese listed companies. Journal of Innovation & Knowledge, 8(4), 100436.
28.
ShiP., & HuangQ. (2025). Alignment of words and actions? Government environmental attention and enterprise digital transformation. Technological Forecasting and Social Change, 210, 123888.
29.
StraubV. J., MorganD., BrightJ., & MargettsH. (2023). Artificial intelligence in government: Concepts, standards, and a unified framework. Government Information Quarterly, 40(4), 101881.
TianL., LiX., LeeC. W., & SpulbărC. (2024). Investigating the asymmetric impact of artificial intelligence on renewable energy under climate policy uncertainty. Energy Economics, 137, 107809.
32.
WanQ., YeJ., ZhengL., TanZ., & TangS. (2023). The impact of government support and market competition on China’s high-tech industry innovation efficiency as an emerging market. Technological Forecasting and Social Change, 192, 122585.
33.
WanX., & DingH. (2024). Can government subsidies for the digital economy promote corporate innovation?European Journal of Innovation Management, 28(7): 2995–3023.
34.
WangA., LuoK., & NieY. (2024). Can artificial intelligence improve enterprise environmental performance: Evidence from China. Journal of Environmental Management, 370, 123079.
35.
WangJ., XingY., & XiaoD. (2025). An empirical study on the relationship between executives’ financial background and corporate ESG performance. International Review of Financial Analysis, 102, 1–7.
36.
WangS., LiX., LiZ., & YeY. (2023). The effects of government support on enterprises’ digital transformation: Evidence from China. Managerial and Decision Economics, 44(5), 2520–2539.
37.
WernerfeltB. (1984). A resource-based view of the firm. Strategic Management Journal, 5(2), 171–180.
38.
WhitleyR. (2000). The institutional structuring of innovation strategies: Business systems, firm types and patterns of technical change in different market economies. Organization Studies, 21(5), 855–886.
39.
XingZ., FangD., WangJ., & ZhangL. (2024). How does institutional theory illuminate the influence of the digital economy on R&D networks?European Journal of Innovation Management, 28(8): 3418–3439.
40.
XuJ., WangX., & LiuF. (2021). Government subsidies, R&D investment and innovation performance: Analysis from the pharmaceutical sector in China. Technology Analysis & Strategic Management, 33(5), 535–553.
41.
XuW., PengZ., FengZ., & PengC. (2024). The impact of government digital attention on enterprise digital transformation: Empirical insights from China. Applied Economics Letters, 32(18): 2713–2718.
42.
YeJ., WangS., & TsaiS. B. (2024). Impact of generative AI on enterprise performance in China: Mediating role of managerial relationships. Journal of Global Information Management, 32(1), 1–20.
43.
ZhangL., & ZhangX. (2025). Impact of digital government construction on the intelligent transformation of enterprises: Evidence from China. Technological Forecasting and Social Change, 210, 123787.
44.
ZhouH., & LiC. (2020). Government subsidies, R&D investment and innovation performance: Evidence from Chinese manufacturing enterprises. Economic Research Journal, 55(8), 100–116.
