Provenance record

Prepared Or Unprepared? Evaluating Healthcare Workforce Readiness for Clinical Adoption of Artificial Intelligence in Nigeria

arXiv cs.CY (Computers and Society) (tier 1, academic) 2026-09-17T04:00:00.000Z Original ↗

Source note: Preprints on societal impact.

Discourse valence

-50

Adverse

confidence 80% · 1 item

-100

-50

+50

+100

-50

Adverse readingFavourable reading

Single-model reading. This item did not meet the threshold for a multi-model panel.

Employment and displacement Governance and regulation Medicine and health

Excerpt as ingested

arXiv:2609.19096v1 Announce Type: new Abstract: Artificial intelligence (AI) is increasingly integrated into healthcare systems worldwide, yet its successful clinical adoption depends critically on workforce readiness, particularly in low- and middle-income countries (LMICs) where infrastructural and training gaps persist. This cross-sectional study evaluated awareness, attitudes, preparedness, and barriers to AI adoption among 761 healthcare professionals across multiple disciplines and practice settings in Nigeria. Data were collected between December 2025 and March 2026 using a structured, validated questionnaire. Overall awareness of AI in healthcare was high (92.6%); however, objective knowledge and self-reported preparedness remained limited, with 40.9% reporting low or very low knowledge and only 63.0% feeling adequately prepared. Willingness to adopt AI was high: 92.5% expressed interest in training, and 78.7% supported inclusion of AI education in undergraduate curricula. Key barriers included lack of training (84.7%), poor infrastructure (71.1%), high cost of AI tools (61.0%), fear of job displacement (60.6%), ethical concerns (52.9%), and data privacy concerns (52.7%). Significant differences in preparedness were observed across geopolitical zones (chi-square (5) = 24.28, p < 0.001), and awareness differed across professional groups (chi-square (6) = 68.38, p < 0.001). Attitudes toward AI differed significantly across professional groups (F = 3.32, p = 0.003), with professionals who felt prepared demonstrating more positive attitudes (mean = 3.74) compared to tho

Every model that read this

Model	Provider	Stage	Score	Conf.	Latency	Prompt	When
Llama 3.3 70B	Meta	analysis	-50	80%	4716ms	v1.0.0 / m1.0.1	2026-09-17 05:41

Llama 3.3 70B · reading

High awareness but low knowledge and preparedness among healthcare professionals in Nigeria.

evidence: primary horizon: n/a

Evidence extracted

40.9% of healthcare professionals in Nigeria reported low or very low knowledge of AI
84.7% cited lack of training as a barrier to AI adoption
61.0% cited high cost of AI tools as a barrier

The chain

SOURCE     arXiv cs.CY (Computers and Society) (tier 1)
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DOCUMENT   d781d893-e22c-41c6-a1d6-164e6bea357c
           https://arxiv.org/abs/2609.19096
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EVIDENCE   3 extracted excerpts
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MODEL RUN  1 run, methodology 1.0.1
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SCORE      -50  (Adverse)
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CONFIDENCE 80%