Artificial intelligence is reshaping pharmacy practice in wealthy countries, from robotic dispensing systems to machine-learning tools that flag dangerous drug interactions. In Jordan, however, a large new survey of working pharmacists shows that the technology has barely penetrated daily practice, and the reasons are more about plumbing than pessimism. A study published in the journal Pharmacia surveyed 901 licensed pharmacists and found that although three-quarters had heard of artificial intelligence, fewer than half had actually used it in the past year. The culprits were not stubborn older practitioners but missing digital infrastructure, lower educational attainment, and workplace settings that lack the connectivity modern AI tools demand.
The research team, drawing on pharmacists recruited through professional social networks and pharmacy association groups between March and June 2025, designed the investigation in two phases. The first phase was a cross-sectional survey intended to map who was using AI and why. The second was a quasi-experimental test of whether a single hour of targeted education could soften the attitudes that keep capable professionals away from the technology. Together, the two phases offer one of the most detailed portraits yet of how the digital divide plays out inside a specific health profession in a developing but technologically ambitious country.
The numbers from the first phase are striking. Of the 901 pharmacists surveyed, 75.1 percent reported familiarity with AI, yet only 41.7 percent of the entire cohort said they had actively used AI tools within the previous twelve months. Among those who were familiar with the technology, 55.5 percent had used it. And what they used it for matters: the most common application, cited by 42.3 percent of users, was verifying medication information, while a mere 8.3 percent used AI to analyze patient data or recommend dosages. The researchers suggest this pattern reflects the easy availability of large language models alongside persistent privacy concerns about patient data, a trend consistent with surveys of primary care providers elsewhere.
When the team ran the sociodemographic variables through a multivariable logistic regression, three factors emerged as independent predictors of AI use. Pharmacists who graduated after 2020 had nearly twice the odds of using AI compared with earlier graduates, an adjusted odds ratio of 1.943. Those holding a postgraduate degree had more than twice the odds of diploma holders, at 2.402. And the availability of digital infrastructure in the workplace, meaning reliable internet access, scalable storage, and application hosting, roughly doubled the odds of adoption as well, with an adjusted odds ratio of 2.099. Hospital pharmacists, who benefit from institutional information technology systems, were also significantly more likely to use AI than colleagues in privately owned or chain pharmacies.
The most intriguing finding came from an interaction analysis. The researchers hypothesized that the quality of the digital environment might moderate the apparent generational gap in AI adoption, and the statistics bore this out. Among pharmacists who graduated before 2020 and lacked workplace digital infrastructure, only 16.0 percent used AI. Yet post-2020 graduates maintained a 67.3 percent adoption rate even in low-infrastructure settings, likely by relying on personal mobile devices. When proper digital infrastructure was available, the pre-2020 cohort’s adoption rate jumped to 52.8 percent, shrinking the generational gap from 51.3 percentage points to just 7.1. The authors describe this as a technological friction effect: older pharmacists are not resisting the technology so much as being locked out of environments where it can run.
This framing challenges a common narrative that attributes slow AI uptake in developing countries to generational resistance. The Jordanian data suggest that basic connectivity is an essential leveler, echoing calls from the European Association of Hospital Pharmacists to invest in digital infrastructure, electronic prescribing, and interoperability as prerequisites for AI integration. Comparable studies in Eastern Romania, Switzerland, Greece, and Bulgaria have documented similar structural and educational barriers, indicating that the problem is not confined to the Middle East but mirrors the digitalization struggles of European pharmacy itself.
Income and workload also mattered. Pharmacists earning more than 600 Jordanian dinars per month had higher odds of AI use than the lowest earners, although the wide confidence interval on that estimate suggests some statistical uncertainty. Seeing more than fifty patients a day was independently associated with adoption, perhaps because high patient volumes create pressure to find efficiency tools. Gender, by contrast, dropped out of the picture once other variables were controlled: although the unadjusted chi-square analysis showed slightly higher use among men, the regression model found no meaningful difference between male and female pharmacists.
The second phase of the study addressed a different question: can attitudes be changed cheaply and quickly? Of the original 901 participants, 301 volunteered for a 60-minute educational webinar delivered by an external expert in health informatics and computational pharmacology. The session combined a thirty-minute lecture on AI basics and job-displacement concerns, a twenty-minute live demonstration of AI checking drug interactions, and a ten-minute ethics discussion on data privacy and algorithmic bias. Sessions were repeated bimonthly from April to July 2025 to accommodate different shift patterns, and attitudes were measured immediately before and after using paired categorical analysis with McNemar’s test.
The results were dramatic, at least in the short term. The share of pharmacists who believed AI will replace the need for pharmacists plummeted from 70.0 percent to 24.6 percent, a drop of 45.4 percentage points. Belief that AI involves high operational costs fell from 88.4 percent to 41.5 percent. Concerns about patient data confidentiality dropped by nearly 40 points, while agreement that AI helps provide optimal pharmaceutical care more than tripled, rising from 20.9 percent to 75.4 percent, and trust in AI’s reliability for drug-related information nearly quadrupled, from 15.3 percent to 60.9 percent. Notably, one belief barely moved: agreement that AI requires human oversight rose only from 19.6 percent to 22.9 percent, a change the authors interpret not as resistance but as evidence that the training successfully framed AI as a decision-support aid rather than an autonomous authority, a stance aligned with the Pharmaceutical Group of the European Union’s position that AI should assist, never replace, professional expertise.
The authors are careful about the limits of these findings. The cross-sectional design cannot establish causation, the intervention lacked a control group, and the posttest was administered immediately after the webinar, so only short-term attitudinal shifts are documented, not lasting changes in practice. The volunteers for Phase II may also have been more motivated or technologically adept than their peers, and the online recruitment method may underrepresent pharmacists in remote areas with poor internet access, precisely the population the infrastructure findings highlight. Still, the study’s practical prescriptions are clear: pharmacies need minimum standards for digital infrastructure, continuing education should incorporate AI fundamentals, and mentoring schemes that pair recent graduates’ digital fluency with senior pharmacists’ clinical experience could help close the gap from both directions. Whether a one-hour webinar produces pharmacists who actually use AI years later remains an open question, but the Jordanian data make a strong case that the first barrier to remove is not fear. It is the missing wiring.
Subject of Research: Socioeconomic determinants of artificial intelligence adoption among Jordanian pharmacists and the effect of an educational intervention on their attitudes
Article Title: The digital divide in pharmacy: Socioeconomic determinants of AI adoption and the impact of educational interventions in Jordan
Article References: Al-Tarawneh, A., Abu Dayyih, W., & Abdel-Qader, D. H. (2026). The digital divide in pharmacy: Socioeconomic determinants of AI adoption and the impact of educational interventions in Jordan. Pharmacia, 73, Article e204786. https://doi.org/10.3897/pharmacia.73.e204786
Image Credits: AI Generated
DOI: 10.3897/pharmacia.73.e204786
Keywords: artificial intelligence, pharmacy, Jordan, digital divide, pharmacists, educational intervention, digital infrastructure, health informatics, cross-sectional survey, technology adoption, job displacement fears, continuing education