In this article, we look at how AI is currently being used in pharmacy, as well as its benefits, challenges, and future potential.
Key takeaways
- AI is used in pharmacy to automate inventory management and dispensing, support drug discovery and development research, send automated alerts to patients, and conduct automated medication safety reviews
- The Royal Pharmaceutical Society (RPS) introduced an AI use policy for pharmacy professionals in 2025, setting out how AI should and shouldn’t be used in pharmacy practice
- The benefits of using AI in pharmaceutical practice include increased efficiency, a reduced risk of human error, and the potential to improve patient outcomes
- AI use in pharmacy does present some challenges, including concerns around ethics, data security and privacy, bias, and potential ‘hallucinations’
- The future of AI in pharmacy looks to be incredibly exciting, as the sector understands more about how it can be used as an aid, rather than a replacement for human input
AI in pharmacy: the current landscape
AI is already being used in pharmacy settings to automate tasks including:
- Inventory management
- Medication safety checks
- Reading prescriptions and matching them to patient records
- Sending alerts and reminders to patients
In pharmaceutical research, AI is also being used to discover new antibiotics, with a team from the Massachusetts Institute of Technology (MIT) announcing in August 2025 that they had used artificial intelligence to invent two potential new antibiotics, designed to treat drug-resistant gonorrhoea and MRSA.
James Collins, the Termeer Professor of Medical Engineering and Science in MIT’s Institute for Medical Engineering and Science (IMES) and Department of Biological Engineering, said: “We’re excited about the new possibilities that this project opens up for antibiotics development. Our work shows the power of AI from a drug design standpoint, and enables us to exploit much larger chemical spaces that were previously inaccessible.”
The potential of AI in pharmacy is huge, but it’s important for pharmacists to understand its most effective uses, limitations, and best practice governance.
Traditional AI vs generative AI: what’s the difference?
AI is often used as a catch-all term to describe any kind of intelligent automation, but there are nuances to how artificial intelligence is discussed. AI has long been used in healthcare, with computer vision used in robotic surgery, and automated screening processes used in many labs. These are examples of traditional AI use in healthcare, but it’s the introduction of generative AI and the sheer pace of current innovation that are changing the game.
While traditional AI uses machine learning to analyse data or identify patterns to automate processes, generative AI surpasses these data analysis capabilities, while also creating its own content. Generative AI is used in large language models (LLMs) and chatbots, and can essentially communicate with people to provide them with information. This is transformative for the healthcare sector, but also raises concerns regarding ethics and security.
How is the use of AI in pharmacy governed?
It is only recently that policies have been introduced to govern the use of AI in healthcare. The Royal Pharmaceutical Society (RPS) launched an AI policy for pharmacy practice in January 2025, which was developed in conjunction with stakeholders including RPS members, digital technology and AI experts, and the General Pharmaceutical Council (GPhC).
Professor Claire Anderson, President of the RPS, commented: “AI offers exciting potential to transform pharmacy practice and there are some great examples where it’s already in use.
“We must optimise the opportunities that these advancing technologies can bring to enhance patient access to care, improve patient experience, support clinical decision making and improve the safety and efficiency of the medicines supply chain.”
With this in mind, the RPS has introduced guidelines that state the importance of ongoing education and training on the use of AI in pharmacy. Pharmacists must also take steps to protect sensitive patient data when using AI tools, and ensure their use complies with regulatory standards at all times. The RPS is also calling for transparency of its usage across the pharmaceutical industry as healthcare professionals continue to test how AI can be used to enhance patient care.
In September 2025, the Medicines and Healthcare Products Regulatory Agency (MHRA) launched a National commission into the regulation of AI in healthcare. This brings together global AI leaders, clinicians and regulators to advise the MHRA on the development of a new regulatory framework for AI in healthcare, to be published in 2026. The National Commission will produce recommendations to advise the development of MHRA guidance in the interim, addressing urgent areas of uncertainty for the healthcare system and industry. The National Commission will help enable key commitments in the government’s 10-Year Health Plan for England and Life Sciences Sector Plan to transform the NHS for the benefit of patients and drive economic growth in the UK’s life sciences sector.
Potential uses of AI in pharmacy practice
There are many different ways in which both traditional and generative AI can be used in pharmacy. From data analysis to prescription automation and patient-facing AI chatbots, the potential of artificial intelligence in pharmacy is huge. Potential uses of AI in pharmacy settings include:
- Summarise content: AI tools can be used to summarise long-form content, including journal publications or complex datasets, providing busy pharmacists with an overview of the key points
- Data analysis: one of the key uses of AI in pharmacy settings is to analyse large datasets to pull out the most important points. A human with expertise in the field should always sense-check the AI’s conclusions, but the information it pulls can be used to support pharmaceutical research or clinical decisions
- Inventory management: AI-powered automation can be used to automate pharmacy inventory management processes, enhancing efficiency and accuracy. Algorithms can also draw on data to forecast future medication needs to optimise inventories and reduce pharmaceutical waste
- Automated dispensing: some hospital pharmacies use automated dispensing systems that feature AI to dispense medication to patients in the correct doses. This helps to streamline processes and enhance patient safety by reducing the risk of human error
- Medication management: AI algorithms can be engineered to predict patient adherence to prescriptions, based on previous data, to support medication management. Automated reminders can also be set up to try to improve adherence and subsequent patient outcomes
- Medication safety reviews: the use of AI in pharmacy also extends to medication reviews, as algorithms can be set up to check high-risk drug interactions in real time to reduce the risk of adverse effects and support patient safety
- Drug development: AI is already being used in pharmaceutical research, drug discovery, and the development of new medicines – the potential of this in the future is huge
- Personalised recommendations: by analysing patient data, AI has the potential to provide tailored recommendations to individual patients, such as personalised medication plans or alternative treatment suggestions
- Patient-facing chatbots: some healthcare companies use AI chatbots that are able to respond to basic patient queries, freeing up resources while improving customer service. However, these need to be managed carefully to avoid putting patients at risk; for example, by signposting them to the relevant healthcare service if they input certain queries
What are the benefits of using AI in pharmacy practice?
The use of AI in pharmacy settings can deliver multiple benefits, including:
- Enhance efficiency: AI-powered automation can significantly improve efficiency in a pharmacy setting by streamlining processes, such as medication dispensing and prescription reminders. This helps to save time, reduce admin, and free up resources, increasing the amount of time pharmacists can spend delivering patient care
- Reduce human error: pre-programmed algorithms are engineered for accuracy, meaning AI in pharmacy can help to reduce the risk of medication errors. Computer vision can scan information and match it to patient records, but it’s important for humans to carry out regular checks to ensure continued accuracy
- Enhance patient experience: the use of AI in pharmacy settings allows pharmacists to spend more time directly speaking to patients, improving the level of care and service they receive
- Improve patient outcomes: AI can provide personalised medication recommendations and automated alerts to improve patients’ prescription adherence and overall outcomes
Challenges posed by AI in pharmacy
There can be some disadvantages and challenges of AI in pharmacy settings, and these are likely to continue to evolve as the pace of change continues. Common challenges posed by AI in healthcare include:
- Data security: there are widespread concerns regarding AI use and data privacy and security. Extra care needs to be taken when inputting sensitive patient data, as not all AI tools have a transparent data use policy. Patient data should be anonymised and handled carefully when using AI tools
- Ethical concerns: AI usage raises ethical questions, particularly regarding the use of patient data, and on who is ultimately responsible for automated decisions. To mitigate these concerns, a hybrid human:AI approach should be used wherever possible; AI is an aid to pharmacy practice, not a replacement for human experts
- Potential bias: some AI algorithms can be biased, which can impact the information and suggestions they provide. This means that human checks of any AI recommendations are crucial
- Hallucinations: AI tools have been known to ‘hallucinate’, meaning they invent information that has no grounding in fact. It is therefore essential that all AI-generated information is fact-checked by humans with expertise in the specific area in question
- Environmental impact: there are also environmental concerns regarding AI use. Statistics from the Government Digital Sustainability Alliance (GDSA) predict that AI use will increase from 1.1 billion cubic metres in 2025 to 6.6 billion cubic metres by 2027 – equivalent to more than half of the UK’s total water usage. With this in mind, it’s important that pharmacy professionals carefully consider how they are using AI and the impact this may have
What is the future of AI in pharmacy?
The future of AI in pharmacy appears to be limitless. It’s an exciting time for the industry, as AI has the potential to fuel drug discovery programmes, support antimicrobial stewardship, enhance personalised medicine plans, and even predict future disease outbreaks.
Dr Jennifer Dixon of The Health Foundation says, “The NHS needs to find a way of getting results fast on the implementation and impact of a lot of AI applications. This will need to be rapid-cycle, cheap, standardised and easily reproducible. Unless this happens, the risk is a vacuum of information (filled with overclaims from vendors or politicians under pressure to show progress) and a misinformed public.”
As the pace of innovation continues to accelerate, it’s vital that pharmacists continue to test new tools, find out what works and what doesn’t, keep patient data protected, and maintain human checks of any AI-generated information.
Best practice tips for using AI in pharmacy
Pharmacy and other healthcare professionals can get the best results from their AI use is by following these best practice tips:
- Engineer your prompts: getting your prompts right is key to effective AI use. It can take some trial and error to hone these; it’s important to be clear and specific, and don’t be afraid to keep asking the AI for the same information in different ways until you’re happy with its output
- Invest in AI training: spend time training colleagues on how to use AI in pharmacy practice, including what it should never be used for. Make sure this training is updated regularly to reflect changing capabilities
- Prioritise data security: it’s vital to take steps to keep patients’ data protected at all times when using AI in pharmacy settings. Invest in the most secure encryption methods possible to keep sensitive data anonymous and private
- Reference AI usage: healthcare organisations need to devise an AI usage policy that clearly states how any use should be referenced, whether in pharmaceutical studies or when providing patient recommendations. This is vital to ensure transparency and uphold integrity
- Test and learn: take the time to test tools before adopting them, and continuously evaluate their effectiveness to ensure they continue to work for you and your patients
- Integration: look for ways to integrate AI tools with your existing pharmacy systems to power workflow automation and improve efficiency
Join UKCPA to share and evolve your use of AI in pharmacy practice
As the use of AI in pharmacy continues to evolve, joining a professional pharmacy network will provide you with opportunities to share learnings and best practice tips with others in the sector. It costs less than £3 a week to become a member of UKCPA, which provides you with access to:
- A library of peer-submitted resources
- Forums dedicated to a range of pharmacy-related topics
- Expert-led education and training opportunities
- Communities focused on a range of pharmacy specialisms
- A calendar of face-to-face and virtual networking events
