Ai-driven Process Automation and Its Impact on Operational Agility and Efficiency
Year: 2025
Type: article
Abstract: AI-driven process automation is transforming fragile economies by cutting task times, improving responsiveness, and expanding innovation. This study assessed Iraq from 2020 to 2024 to explain how automation tools, workforce readiness, and governance support shaped operational agility and efficiency while facing fiscal volatility and resistance. A descriptive and explanatory design was used, relying on 105 secondary data cases analyzed through descriptive statistics, correlation, and regression. Findings show robotic automation adoption rose from 12 to 37 percent, intelligent document processing from 8 to 31 percent, and chatbots from 10 to 35 percent. Training programs expanded from 7 to 25, skilled operators grew from 400 to 1,000, and innovation labs from 2 to 9. Processing times fell by 22 percent, flexibility rose to 33 percent of firms, responsiveness improved by 21 percent, and innovation outputs reached 23 percent of organizations. Correlation analysis revealed strong associations with automation tools (0.83), human capacity (0.77), and governance support (0.72), while contextual constraints had a negative effect (-0.59). Regression confirmed automation tools had the strongest impact (β = 0.45), followed by human capacity (β = 0.30) and governance (β = 0.23), while constraints reduced gains (β = -0.21). The results imply that scaling inclusive automation, strengthening skills, and enforcing governance while stabilizing fiscal policy are essential for national competitiveness. Recommendations include expanding adoption to SMEs and rural areas, building stronger retention pipelines for skilled staff, and improving enforcement of digital governance frameworks.
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7082373802
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