Adoption Factors of Artificial Intelligence and the Performance of Infrastructure Projects in Kenya
DOI:
https://doi.org/10.53819/81018102t5405Abstract
This study explored the adoption factors of Artificial Intelligence (AI) and the performance of infrastructure projects in Kenya, with a focus on Nairobi County Constituency. A mixed-methods approach was applied, combining quantitative surveys with qualitative interviews, and data were collected from 60 respondents out of a targeted 65, representing a high response rate of 92%. The findings revealed that organisational factors strongly affect AI adoption: 72.2% of respondents confirmed that top management supports AI initiatives, yet 61.1% reported that employees' capacity is low, 66.7% indicated that budget allocations for digital innovation are inadequate, and 55.6% pointed to an organisational culture resistant to change. Awareness levels showed a similar pattern, with 61.1% of participants indicating they understood how AI could be applied in construction workflows, but only 38.9% had received any form of AI-related training or exposure. Despite this gap, optimism about AI's value was high, with 77.8% agreeing that AI improves decision-making and project efficiency. Technological readiness was identified as the most critical barrier, as only 38.9% reported system compatibility with AI tools, 72.2% cited the unavailability of relevant software as a major limitation, and 66.7% agreed that technological complexity hinders adoption. Qualitative insights echoed these challenges but also revealed cautious optimism, with respondents highlighting AI's potential to enhance project scheduling, cost control, risk management, and workplace safety. The study concludes that for AI adoption to progress meaningfully in Kenya's construction industry, firms must strengthen organisational capacity, invest in awareness and training programmes, and upgrade technological infrastructure. Addressing these barriers will enable firms to unlock AI's transformative potential, enhance efficiency and safety, and accelerate digital transformation toward global competitiveness. The study recommends targeted AI training, improved technological infrastructure, dedicated innovation funding, effective change management, and supportive government policies to enhance AI adoption in the construction sector.
Keywords: Artificial intelligence, performance, infrastructure projects, Kenya
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