At its core, AI today is merely a powerful tool for augmentation. It is most definitely not intelligent in the true sense of the word unlike many erroneous assumptions. While it is incredible at performing certain tasks, it can fool people into believing it is something that it is not, and this is because they do not understand its foundation and nature.

“At its core, AI today is merely a powerful tool for augmentation.”

The most advanced models still fail miserably in aspects such as nuance, authentic lived experience and human intuition because they do not have the intelligence, context and the organs or senses of perception that we have. As of March 2026, it is apparent that AI as we know it is reaching its technological and developmental limits as discussed further below. 

AI has no conscience, no morality, and no clinical discernment. It is a tool like a hammer and not a living thing. One does not use a hammer to tend to a delicate seedling, just as one should not use a sophisticated predictive text engine to understand and improve the complex health issues of a patient.

However, the undeniable fact is that an individual actively resisting or dismissing their engagement with AI while still using the internet is akin to declaring they are not engaging with the automobile industry because they don’t drive, yet they still participate in society. The food they buy, the mail they receive, the fuel that heats their home and any public or personal transport they use all rely on the deeply ingrained petrochemical infrastructure. Likewise, AI is already systematically integrated into the internet, and increasingly into the workflows of businesses. This includes search engines, mailboxes, website hosts, autocorrection and many other services. It is unavoidable.

On the opposite spectrum, overreliance or uninformed use of this new technology can be dangerous, perhaps even more so than its dismissal. Just as driving a car requires training, a licence, and an understanding of the rules of the road to navigate safely, successfully utilising AI in a clinical setting requires some level of AI knowledge and understanding.

This is why the EU has already implemented the EU AI ACT 2024, enforced since February 2025 in European countries which includes mandatory AI literacy for professionals using AI. This particularly affects healthcare, where any AI system used for health-related activities or assessment is considered “High Risk”. This deeply implicates herbalists and other CAM practitioners operating in Ireland or within the EU (1). 

In addition, with patients increasingly turning to “Dr. AI” for quick fixes and diagnosing themselves, practitioners can no longer afford to sit on the sidelines and ignore the pathologies and dangers that come from AI misuse, in particular for mental health or flawed health advice. Practitioners that strive to understand or learn to “drive” these complex models effectively, or at least have the “theory”, cannot only streamline their clinics, but to more importantly protect their patients and professional integrity.

In the EU, AI literacy is no longer an option in healthcare, it is a requirement by law and the UK may follow suit soon with the introduction of the UK AI Bill due to be implemented by 2027.

Both the Medical Council (Ireland) and the GMC (UK) are actively addressing AI use for health and within clinical settings. They insist that AI should augment, not replace clinical judgment and that ultimately the practitioner is responsible for the use of any AI advice (2,3). With regulated health sectors complying, it is vitally important for the self-regulated sectors to follow suit in order to show their ability to self regulate.

We must first dispel a common myth: large language models (LLMs) like ChatGPT, Claude, and Gemini are commonly referred to as AI, AI chatbots, GPAI (general purpose AI) or narrow AI and are not “true AI” otherwise known as artificial general intelligence (AGI). They are, essentially, no more than highly sophisticated multimodal predictive text engines. In other words, an LLM is trained on vast amounts of data from the internet and literature to predict the most statistically likely next word in a sequence, note in a song, pixel in an image and frame in a video.

When it is asked a question, it is not looking up the answer in a database, it is calculating what words usually follow the words in the prompt and what is the most agreeable way of doing so. While an incredible asset for specific tasks, the misunderstanding of this fundamental mechanic underlies the most significant clinical dangers practitioners face today.

In fact, a recent study, along with a mounting body of evidence, suggests that LLMs as they are now, including the most advanced models as of the beginning of 2026, are mathematically reaching their limits and that it is unlikely that AI will significantly develop intelligence this year or any time soon.

No matter how much information is being fed into the AI models, no matter how large the data centre hosting them is, the architecture they are built on will not address the underlying pathologies and errors nor improve their ability to predict or understand context. They are not becoming sentient nor are they near to achieving human intelligence or judgment without a major technological breakthrough and a complete restructuring of their digital synapses (4).

The human analogy

Another way of putting it is to use an analogy of the human brain. The architecture of an LLM can be understood as a disconnected prefrontal cortex functioning without the cerebellum, limbic system and broader nervous system that belong to a whole aware being.

This isolated part of the brain, whose role is to govern executive functions, is structurally incapable of developing into a fully cognitive intelligence. Without the functional equivalents of the cerebellum and limbic system, these models will remain “narrow” and disconnected from full cognitive potential, regardless of the volume of data or computational power fed into them. This illustrates the fundamental limitation we have reached with current LLMs, thus the synonym: narrow AI.

Because AI models are designed to generate plausible sounding text rather than to verify truth, they exhibit specific “pathologies” that can be highly dangerous in a healthcare setting. While companies behind AI models are attempting to mitigate these fundamental flaws, they cannot entirely be eradicated. In fact, improving on how an LLM responds may simply make it more difficult for the person reviewing its output to spot the pathologies, yet these errors persist even on the most advanced models.

Hallucinations (the confident liar)

LLM models are notorious for hallucinating, inventing facts, fabricating botanical actions and contraindications, or generating entirely fake peer reviewed references (5). Because the output is designed to sound authoritative, confident and is grammatically perfect, it is incredibly easy to be fooled. If an LLM is asked to cite a paper on the efficacy of Hypericum perforatum for a specific niche condition, it may simply invent a title, authors, and a DOI link that lead to nowhere. Relying on AI for patient care or professional writing without thoroughly reviewing the output is a direct threat to clinical safety. AI responses cannot be accepted at face value.

Sycophancy (the yes man)

AI models are generally programmed to be helpful, polite, and to please the user. In fact, those who have used the popular model, ChatGPT, will have encountered a prompt for them to “choose the best answer”, which further influences how the model responds. This creates a dangerous phenomenon called sycophancy, where the AI will actively agree with the user’s biases or leading questions which is especially dangerous in a medical setting (6).

If a patient or practitioner inputs a deeply flawed premise, for example, “Tell me why taking high doses of essential oils internally is the best way to cure gut issues”, the AI may validate that dangerous premise and build an argument to support it, rather than offering objective clinical pushback. The chances for sycophancy become more apparent the longer the “conversation” (or context in AI terms), which can often make it more difficult to spot, despite the safety measures AI companies are putting in place. In other words, AI can bypass the safety guards if the context “makes sense” for it to do so.

Regurgitation and model collapse

It is vital to understand what these models are trained on. A significant percentage of the training data for major LLMs comes from Wikipedia, Reddit, Quora, and YouTube transcripts. When patients or practitioners ask general AI models for herbal advice, they are often receiving a regurgitation of internet websites and forums, many of which may have mis- or disinformation. More disturbingly, the popular ChatGPT referenced 47.5% Wikipedia in its responses during a study, which in turn is now being used to write Wikipedia articles in a disturbing positive feedback loop (7,8). 

Furthermore, as AI generates a larger share of online content, newer models are increasingly trained on this ‘AI slop’, which is low-quality synthetic data. This feedback loop leads to the homogenisation of information and a significant loss in performance and accuracy. Over time, this can trigger ‘model collapse’,’ a state where the model’s output becomes a distorted caricature of reality, forcing developers to perform massive, costly resets using strictly curated, human-generated datasets (9). 

“AI psychosis” and mental health risks

A deeply concerning emerging theme in psychiatric literature is AI psychosis or Chatbot psychosis. Some argue that it’s not a new phenomenon as other mediums (books, radio or television) have also caused psychosis in individuals during their emergence (10). Others suggest that there is a growing concern that these convincing AI bots may reinforce cognitive instability, blur reality boundaries and disrupt self-regulation due to their close resemblance to human speech (11). 

In any case, practitioner awareness of the potential convincing delusions of AI chatbots can protect their patients from harm. Notably by educating them on what LLMs are, what they are not and how their predictive algorithms are designed by nature to be great at confidently convincing and affirming our prompts.

Fake AI literature: AI written herbals

It has also become apparent that AI is being used to author misleading and dangerous herbal literature. There was a letter from David Winston circulating in January 2026 warning that “82% of new herb books listed on Amazon for the year 2025 are AI generated”. Rosemary Gladstar had received an email from British publisher Oliver Rathbone indicating this finding (12,13).

More alarming yet, notable herbalist authors such as Simon Mills have already been prey to fake AI herbals attributed to, or using, their names. These fake AI books are using genuine names to increase authority, making it even more dangerous for both herbalists and public scouring the internet for authentic books. While most publishers will remove such books upon request, the danger is the fact that they get published in the first place.

Biases found in general LLMs

The author performs periodic benchmarks to assess the aforementioned flaws as well as biases found in the responses of the major LLMs. While many of them have improved in their logic, the nuances found in each of their answers is something that isn’t often discussed. The Irish Medical Council itself warns against “hidden biases” in AI systems (2).

This is highly relevant for herbal medicine, where AI models may struggle to interpret the nuances of traditional diagnostics such as functional frameworks and heuristics, or tongue and pulse diagnosis. These models can also exhibit bias toward specific modalities, as demonstrated in the author’s December 2025 AI benchmark.

For example, while ChatGPT and Claude ‘red flagged’ physiomedicalist terms in favour of biomedical terminology, Google’s Gemini and China’s DeepSeek were more respectful of diverse traditions, even elaborating on the legitimacy of these systems for health assessment (14). 

This disparity highlights the need for the herbalist sector to adequately be equipped to educate the public, their patients as well as advocating and funding inclusive tools, which remains a challenge for those working with non-standardised models (e.g., there is little to no availability for naturopathic-specific LLMs trained on unbiased, domain appropriate data).

The era of voluntary guidance regarding digital tools in healthcare is over. The legislative landscape has shifted dramatically over the years and has moved towards strict legal obligation, especially with the rise of AI.

UK GDPR closely mirrors European standards, and the direction of travel is clear — ignorance of digital privacy is no longer a valid legal defence (15).

Health data is special category data and requires special care

This brings us to one of the most critical vulnerabilities for modern practitioners in the UK and EU, especially for those who would call themselves “technophobes” — the use of “free” digital services. If a practitioner is using free email addresses to communicate with their clients, such as “@gmail.com”, “@hotmail.com”, or even “@protonmail.com”, they most likely do not have a Data Processing Agreement (DPA) in place as required by law. The same applies to free versions of AI tools. Even some premium services may not offer a DPA if they are not specifically designed for business or healthcare use.

Under GDPR Article 28 [and UK-GDPR], a data controller (the practitioner) is strictly required to have a legally binding contract, known as a data processing agreement or addendum (DPA), with all their data processors (web designers, hosts, email providers, AI services, cloud storage, or practice management software). This ensures that personal data is adequately stored, encrypted, and processed on the user’s behalf. Special category data such as health information has even more strict requirements (16,17).

Without valid DPAs, practitioners are strictly liable for privacy violations, not the data processor or service provider. A DPA is a legally binding contract that ensures the tech vendor handles data compliantly and, crucially, guarantees they will not process and sell user data or use it to train AI models. The author has already recommended that professional associations and organisations advise their members that using personal, free email and internet services lacking a DPA represents a severe regulatory and ethical risk. ICO (UK) or the DPC (Ireland) can request a warrant and seize digital assets during an audit such as a personal email inbox if it is implicated in a breach of data.

As data controllers, practitioners are ultimately liable for their clients’ personal data. Whether it is as simple as a contact form on a website, an email from a patient with their name (or worse, blood work results), or a web designer with access to patient user information via an administrative web panel, using a non-compliant internet service means companies can scan and use this data freely. 

Inherently, “free” services are not free. Input user data is given to these companies in exchange for their service. While some companies offer DPAs as part of their terms of service for professional bundles, others require manual activation (e.g., Google Workspace requires a manual signature of their Cloud DPA and HIPAA compliance settings within the Admin Panel). Practitioners are strongly advised to verify they have adequate DPAs with all digital services used to communicate and store patient data.

Note: To confuse the matter, the UK’s primary data protection legislation is the Data Protection Act 2018, which is also abbreviated as “DPA”. While this law works alongside the UK GDPR to enforce the standards discussed in this section, it is a piece of legislation and should not be confused with the Data Processing Agreement (or Addendum) contract required for compliance — i.e. A service advertising that it is “DPA compliant” is the same as saying it is “GDPR compliant” but does not mean that it automatically implements the required legally binding contract.

AI is here to stay, and when used ethically and securely, it can alleviate the administrative burden many practitioners face, speed up workflow as well as be an incredible research assistant. In fact, considering it purely an “assistant” is key to knowing what tools to use and when to use them.

AI can instead be imagined as an intern that is incredible at grammar and can compile existing work or research that has been reviewed and validated, but will still make some mistakes when piecing things together. AI won’t do flawless research, but can compile, adjust, abbreviate or elaborate whatever information it is given. There are brilliant AI tools available that isolate and mitigate some of the deep flaws of AI, making it an incredible tool to boost productivity, research and workflow (allowing for more time to spend outside with the plants). But it requires a certain level of AI literacy, understanding and diligence.

Red light: What to avoid (high risk)

• Diagnostics, formulations and dosages: Use of general AI for final diagnostics without validating the given information with genuine sources, or for any formulation, dosage, or safety profile of a prescription is strongly advised against. The practitioner holds the liability, and basing clinical decisions on AI suggestions has no legal or ethical defence.
• Blind referencing: AI generated script or citation can’t be trusted, so it is always worth clicking the link and reading the primary source — to review, validate and check every piece of information that is given. Some primary sources may be written by AI, so checking the authority of the website is important (e.g. Is the source from Wikipedia, a personal blog or a genuine research paper on an authoritative website?)
• Inputting raw patient data or personal proprietary data: Identifiable patient data is not safe to enter into a public chatbot, nor is any proprietary, unpublished work; not unless the AI service offers a Data Protection Agreement/Addendum. Most “free” services use prompts and data to train AI and some paid services may not have the necessary legal requirements in place.

Warning: As of March 2026, individual paid tiers such as ChatGPT Plus or ChatGPT Pro plans do not offer a Data Processing Agreement (DPA); they are therefore not GDPR compliant for processing patient data. To obtain a DPA from OpenAI, their ChatGPT Team or Enterprise plans must be used, which are costly. Alternatively, business grade services like Gemini for Workspace (by Google) include a DPA that ensures  input data is not used to train their models, making it a viable option for handling identifiable information. Verifying whether a DPA is available, active and signed can be found via specific account settings before uploading sensitive data. Otherwise, the service provider can be contacted by email, if in doubt.

Green light: What to do (low risk, high reward)

• Brainstorming and drafting: AI can be used to overcome writer’s block or aid in structuring a paragraph or section in a document. It is also excellent for drafting general patient handouts, writing newsletter outlines, or structuring an educational talk based on information and resources already acquired.
• Tone adjustments: AI can rewrite a complex, jargon-heavy email or handout into simpler, more compassionate language for a patient, using one’s own input and information.
• Research assistance and grammar review: Appropriate AI tools may be used to review, draft or compile existing information and data sets into an output adapted to desired needs, saving time and effort. This still will require careful review and manual adjustments.

Not all AI tools are created equal. Moving beyond the standard chatbot means utilising specialised tools that circumvent common multilingual and classification failures:

• For research: Instead of asking ChatGPT or any general AIs for medical studies, use tools like Consensus or Elicit. These AI-enhanced search engines only pull data from peer reviewed scientific journals, drastically reducing the risk of hallucinations.
• For private and health data analysis: For AI to analyse clinical notes or summarise complex blood work, there is a “walled garden” tool. These tools are called retrieval augmented generation (RAG) systems where AI assists the user by purely using the user trusted PDFs, literature, sources and documents. NotebookLM Plus, for instance, is an available service that never trains AI models and is also DPA compliant when used as part of “Google Workspace”. The AI will only search, synthesise and reference the documents provided, and it does not use data given by the user to train its foundational models. The DPA compliant version can be used, for example, to assess the blood work of a patient directly without worrying about censoring their identifiable data by inputting trusted books, presentations and literature alongside their results or to assist in structuring or summarising patient notes and individualised handouts. As a contracted data processor, they would be fully liable for a breach of a practitioner’s patient’s data, so long as they have a DPA in place.

There are countless other tools and systems available, and a core component of AI literacy is the discernment of which platforms are suitable for specific tasks. The above section is not intended to be an exhaustive list of rules, nor is it a complete directory of AI tools, but rather a foundational framework for safe clinical practice.

We are currently navigating a profound and complicated transition, comparable to the rise of the internet itself. The goal of AI literacy is not to turn herbalists into software engineers, but to ensure that emerging technologies are used to safeguard patients, their privacy and to preserve the integrity of our profession.

AI is brilliant at parsing massive datasets, organising administrative chaos, and synthesising clear and concise text. But it cannot feel a pulse, read the subtle shifts in a patient’s body language, or understand the complex energetics of a living plant interacting with a living human being.

AI organises information but the practitioner provides it. AI will never replace healthcare professionals. But professionals who understand AI, who know its pitfalls, and who wield it with ethics in mind will inevitably get ahead of those who do not and will be appropriately equipped to safeguard the patients who may overuse the technology.

Future development of AI technologies specifically curated for herbalists is not as far reaching as we might think. The primary roadblock is financial, as basic AI hosting servers can cost from one hundred to several hundred pounds a month. However, if resources are pooled within the herbalist community as a collective, and authors are willing to contribute their books and research to the cause, training and hosting a dedicated herbalist AI model is highly feasible. 

By building AI systems based strictly on authentic medical and herbal literature, the profession could create a secure ecosystem of knowledge untainted by the biases and limitations of conventionally trained general LLMs. While it would not be a flawless approach, it would ultimately be the safest method for integrating AI into herbal medicine and would bypass the requirement to rely on the proprietary “big tech” models currently dominating the market or systems solely orientated towards the biomedical model.

NotebookLM was used to assist in compiling the background research. Gemini for Workspace was utilised to aid the author in structuring the manuscript and refining the grammar. The final document was thoroughly reviewed, manually adjusted, and verified by the author.

1. European Union. (2024). Chapter 1 Article 4 AI literacy. Regulation (EU) 2024/1689 (Artificial Intelligence Act). Official Journal of the European Union, L series. [Accessed 25 January 2026] https://eur-lex.europa.eu/eli/reg/2024/1689/oj/eng#art_4 
2. Medical Council (Ireland). (n.d.). Medical Council (Ireland) Statement on AI. [Accessed 25 January 2026] https://www.medicalcouncil.ie/public-information/artificial-intelligence-in-medicine/medical-council-position-statement-on-artificial-intelligence.html 
3. General Medical Council (GMC). (n.d.). GMC (UK) Research on AI in Medicine. [Accessed 25 January 2026] https://www.gmc-uk.org/professional-standards/learning-materials/artificial-intelligence-and-innovative-technologies 
4. Sikka, V., & Sikka, V. (2025). Hallucination Stations: On Some Basic Limitations of Transformer Based Language Models. ArXiv, abs/2507.07505. https://doi.org/10.48550/arxiv.2507.07505 
5. Rumale Vishwanath, P., Tiwari, S., Naik, T. G., Gupta, S., Thai, D. N., Zhao, W., Kwon, S., Ardulov, V., Tarabishy, K., McCallum, A., & Salloum, W. (2024, June 29). Faithfulness hallucination detection in healthcare AI. OpenReview. [Accessed 22 January 2026] https://openreview.net/forum?id=6eMIzKFOpJ 
6. Chen, S., Gao, M., Sasse, K., & Topaz, M. (2025). When helpfulness backfires: LLMs and the risk of false medical information due to sycophantic behavior. npj Digital Medicine, 8(1), Article 605. [Accessed Sunday 25 January 2026] https://doi.org/10.1038/s41746-025-02008-z 
7. Lafferty, N. (2025, June 5). AI platform citation patterns: How ChatGPT, Google AI Overviews, and Perplexity source information. Try Profound. [Accessed Sunday 25 January 2026] https://www.tryprofound.com/blog/ai-platform-citation-patterns 
8. Tangermann, V. (2025, May 23). Terrifying survey claims ChatGPT has overtaken Wikipedia. Futurism. [Accessed Wednesday 4th March 2026] https://futurism.com/survey-chatgpt-overtaken-wikipedia 
9. Shi, L., Wu, M., Zhang, H., Zhang, Z., Tao, M., & Qu, Q. (2025). A Closer Look at Model Collapse: From a Generalization-to-Memorization Perspective. ArXiv, abs/2509.16499. https://doi.org/10.48550/arXiv.2509.16499 
10. Carlbring, P., & Andersson, G. (2025). Commentary: AI psychosis is not a new threat: Lessons from media induced delusions. Internet Interventions, 42, Article 100882. [Accessed Wednesday 4th March 2026] https://doi.org/10.1016/j.invent.2025.100882 
11. Morrin, H., Nicholls, L., Levin, M., Yiend, J., Iyengar, U., DelGuidice, F., … Pollak, T. (2025, July 11). Delusions by design? How everyday AIs might be fuelling psychosis (and what can be done about it). [Accessed 22 January 2026] https://doi.org/10.31234/osf.io/cmy7n_v5 
12. Tarita, T. (2025, November 4). Amazon’s bestselling herbal guides are overrun by fake authors and AI. ZME Science. https://www.zmescience.com/tech/amazons-bestselling-herbal-guides-are-overrun-by-fake-authors-and-ai/ 
13. National Forum for Herbalists. (2026). I’ve noticed many members asking about regulatory updates for 2026. Here is a summary of what to expect for the [Status update]. Facebook. [Accessed 26 January 2026] https://www.facebook.com/groups/NFHERB/posts/25584812314449057/ 
14. Ó hErodáin, L. (2026) AI in Herbal Medicine: Benchmarking Safety & Clinical Nuance. [Accessed 4 March 2026] https://celticfoxherbal.com/wp-content/uploads/2026/02/AI-Benchmark-results-Dec-2025.pdf 
15. The Medical Defence Union (The MDU). (2024). Introduction to data protection for independent practitioners. [Accessed 25 January 2026] https://www.themdu.com/guidance-and-advice/guides/introduction-to-the-gdpr-for-independent-practitioners 
16. Harper James. (2024, January 30). The controller to processor agreement: A GDPR guide. [Accessed 25 January 2026] https://harperjames.co.uk/article/controller-to-processor-agreement/ 
17. Ambit Compliance. (2024). Is your data processing agreement worth the paper it’s written on? [Accessed Sunday 25 January 2026] https://www.ambitcompliance.ie/blog/is-your-data-processing-agreement-worth-the-paper-its-written-on

In 2013, the German Federal Institute for Risk Assessment (BfR) published a risk assessment of botanicals that recommended prohibiting ashwagandha from use in food supplements, due to concerns about effects on the endocrine system and its safety in pregnancy (2). A lack of consensus about how to proceed led to no change.

However, in 2019, the Danish Food and Drug Administration suggested they also had concerns due to traditional use of ashwagandha as an abortifacient, as well as effects on sex and thyroid hormones. In 2020, Polish authorities limited the intake of ashwagandha to 3 g daily. In 2023, Denmark banned the use of ashwagandha in food supplements, with Dutch, French, German and Swedish authorities advising people against its use (2). 

In the UK, ashwagandha has not been accepted as a medicine under the traditional herbal medicinal products framework, but has not been banned, and its history of use in India could be used to support an application. Whether it can be used in foods and supplements in the future will depend on the outcome of the FSA consultation (2).

Multiple clinical trials and systematic reviews have concluded that the side effects from taking ashwagandha are minimal (7,8). Many of the clinical studies that have been published in the past have only assessed the effects of taking ashwagandha for 8–12 weeks, which doesn’t reflect the long-term use that is sometimes advised.

A recent 12-month multi-centre clinical study in 191 men and women was conducted to assess safety over a longer period of time (7). There were 18 mild adverse events of nausea, digestive upset and headache, none of which required an intervention. Liver, renal and thyroid function were all found to be unaffected. Cortisol was reduced, testosterone increased and self-reported quality of life was significantly improved; all of which are outcomes considered to be beneficial effects (7). 

The repeated demonstration of the safety of ashwagandha in clinical trials has not reassured regulatory authorities, however, and concerns have remained.

Concerns about ashwagandha’s safety in pregnancy surprised herbalists, as most traditional texts make no mention of this. In 2013, the BfR raised concerns that ashwagandha had abortifacient effects based on a World Health Organisation monograph for ashwagandha, which itself referenced an American Herbal Pharmacopoeia (AHP) monograph (4). However, the AHP monograph has been misrepresented. The original text is as follows:

“There are conflicting reports regarding the use of ashwagandha in pregnancy. Large but undefined doses have been reported to possess abortifacient activity. Of several ayurvedic practitioners consulted, none reported having observed an abortifacient activity clinically. Conversely, ashwagandha has, traditionally and in modern ayurvedic practice, been used to prevent miscarriage and stabilize the fetus.”

Concerns that the WHO monograph has distorted information from other sources has been shared by other authors and the AHP published a press report to respond to the claims (9,10). 

A detailed review of pharmacokinetics and toxicity studies of ashwagandha found no cause for concern from in vitro, in vivo and ethnobotanical sources (9). This is supported by preclinical and clinical evidence from the Ministry of AYUSH in India that demonstrates no toxicity to mother or foetus when pregnant women use ashwagandha root (10). As with any other herb, more research is needed to have complete certainty of ashwagandha safety.

Withanolides and withanosides are rapidly absorbed into the systemic circulation within 1 and 1.5 hours and withanolides are present for between 6 and 15 hours. Some withanolides are able to cross the blood-brain barrier, while others (such as withanoside IV and withanoside V) do not. The impact of ashwagandha phytochemicals on cytochrome P450 enzymes is not clear. Some studies show no impact, while others have found that CYP2B6 is inhibited and CYP3A4 is induced (9). It is likely that there are differences between individuals.

A safe dose of 2 g/kg has been found in animal studies and animal studies generally show low or no toxicity, unless high-alkaloid extracts are used (3). Williamson and Brendler conclude that ashwagandha “is an unusually safe herb” (3).

The complexity of plants and humans makes predicting the effects of consumption of herbs challenging. The presence of certain phytochemicals can prevent or enhance the absorption of others in the body. Ronen et al. described how they validated the use of AI to predict toxicity based both on published literature and on molecular structure of the phytochemicals in ashwagandha (6).

Out of 1396 publications mentioning ashwagandha 97% did not highlight any toxicity concerns; those that did refer to toxicity were mostly discussing cytotoxicity in the context of cancerous cells. There were nine articles that included concerns of liver toxicity and one mention of an adverse effect on thyroid activity (6). AI analysis of the structure of phytochemicals in ashwagandha found that all of those present in the roots of the plant were predicted to have low liver, reproductive and hormone toxicity, with only two of the phytochemicals found in the leaves of the plant being predicted to have liver toxicity (6).

It has always been challenging to confidently reassure regulatory authorities about the safety of herbs. The perspective of the herbalist who focuses on therapeutic benefits clashes with that of the regulator who disregards benefits and focuses on minimising risks. Ethics prevents us from conducting randomised controlled trials in pregnant individuals and herbs should always be prescribed cautiously in pregnancy, but it is important for experts to highlight when traditional understanding has been misrepresented.

Ashwagandha has a long history of traditional use and demonstrated clinical safety. More modern techniques may help to convince those who remain wary of herb safety.

1. Mills, S. Threats to ashwagandha safety: How do we respond to new reports of liver damage? Herbal Reality 2024. Threats to ashwagandha safety: How do we respond to new reports of liver damage? | Safety | Herbal Reality
2. Brendler T, Al-Mondhiry R, Lang L, Marles R, Tallon M, Raghu A. Ashwagandha: Is It Safe? Part 1: A Regulatory Review. Phytother Res. 2025 Dec 19. https://doi.org/10.1002/ptr.70151 
3. Williamson EM, Brendler T. Ashwagandha: Is It Safe? Part 2: A Preclinical Evidence Review. Phytother Res. 2025 Sep 18. https://doi.org/10.1002/ptr.70090 
4. Brendler T. Is Ashwagandha an Abortifacient? Phytother Res. 2025 Dec 26. https://doi.org/10.1002/ptr.70150
5. Li L, Zhang X, Hao J, Tian X, Zhu Y, Yang Y, Qiu B, Wen J. Evaluating the Safety of Ashwagandha as a Food Additive: A Focus on Reproductive, Thyroid, and Immune System Effects. Phytother Res. 2025 Dec 26. https://doi.org/10.1002/ptr.70157 
6. Ronen Y, Ebert C, Tamim-Yecheskel BC, Zev S, Kantor O, Arbel HB. Comprehensive safety evaluation of Withania somnifera (Ashwagandha): an AI-driven meta-analysis and quantitative structure-activity relationship based toxicity assessment. Front Nutr. 2025 Nov 24;12:1658265. https://doi.org/10.3389/fnut.2025.1658265 
7. Salve J, Kale S, Prajapati BL, Sparavigna A, Savant M, Ademola J, Langade D. Safety of 12-Months Administration of Ashwagandha (Withania somnifera) Standardized Root Extract in Healthy Adults: A Prospective, Observational Study. Phytother Res. 2025 Oct 8. https://doi.org/10.1002/ptr.70096 
8. Sharma E, Ganu G, Kshirsagar K, Shah A, Mahale U, Mehta A, Nair S. An open-label, single dose, safety and pharmacokinetic study of Withania somnifera root extract in healthy volunteers. Drug Metab Pers Ther. 2025 Feb 19;40(1):23-34. https://doi.org/10.1515/dmpt-2024-0089 
9. Tallon MJ, Koturbash I, Blum JL. A Systematic and Ethnobotanical Review of Ashwagandha’s (Withania somnifera) Teratogenic and Abortifacient Potentials. Phytother Res. Published online August 31, 2025. https://doi.org/10.1002/ptr.70079 
10. Upton, R. Press Release: AHP Responds to Claims of Ashwagandha Abortifacient Effects. 2024. American Herbal Pharmacopoiea. Press-Release-Ashwagandha-Abortifacient-Assessment_06-24-2024.pdf

“Everybody had the same terrible, terrible fatigue. So I just told everybody about the ‘trial’ and everybody… and, and those who signed up… you know, just, just got better. Really, really quickly.” – JSP service user

The Jade Screen Project (JSP) offers immune-enhancing and anti-viral herbal formulae for people working in the NHS, care homes, and those providing essential support services, that might reduce the risk and potential severity of infection.

We want to step forward to help those who are on the front line at greater risk of infection from Covid-19, by offering free CHM. We want to give it for free because we feel they deserve this level of support, as they are putting their lives on the line.

The Jade Screen is taken from the name of an ancient formula, which was used to protect people from infection. The formula’s name was derived from the Feng Shui practice of placing a screen made of the jade stone in rooms to protect people from draughts, the reference to jade reflects value and strength, and screen indicates a barrier – together it is considered something both protective and precious to have around the home.

The Jade screen, both the formula and the metaphor of protection, is our inspiration to offer our support to people working in environments where there is an increased risk due to high viral load.

The Jade Screen Project (JSP) was set up in April 2020 by a small group of Chinese herbal medicine practitioners in response to the rapidly developing healthcare crisis caused by Covid-19, and its potentially devastating effect on frontline workers. The name of the project was derived from a famous 13^th century Chinese herbal formula designed to protect against infectious disease.

Our aims were to replicate findings in Hong Kong from the 2002-3 SARS epidemic and anecdotal reports from Wuhan, China, in 2020, that described the use of immune regulating and anti-viral herbal medicines in helping to protect healthcare workers from contracting disease.

Our second aim was to provide herbal support for people who had contracted the virus and were managing the disease at home, and our third objective was to use herbal medicine to promote recovery from the chronic symptoms of disease now known as ‘Long Covid’.

Setting up the project was exciting and exhausting. We conducted rapid reviews on all the English and Chinese language literature describing the treatment of Covid-19 and similar coronaviruses with Chinese herbal medicine (CHM). Most of the data described the treatment of acute disease and various protocols that had been tested or were biologically plausible as preventative interventions.

We quickly formulated this review into treatment guidelines and ran three training seminars to inform our herbal colleagues of our findings. Seminars were free and were conducted via Zoom. Over 100 herbal practitioners attended, 50 of whom then signed up to provide a network of herbalists prepared to treat frontline workers.

We now had a theoretical framework we could apply to treating Covid and a group of practitioners prepared to treat frontline workers free of charge. In parallel to these encouraging developments we approached Balance Healthcare Ltd, who agreed to provide heavily discounted herbs for the project.

We desperately needed funding to enable to project to become operational and this was generously provided in the form of two £5000 grants from the Earthsong Foundation. Chinese herbal medicine in the UK now had a portal which it could use to make a contribution to the fight against the pandemic.

We saw our first patient, a policeman with acute Covid symptoms, on May 1^st 2020, and we have now treated 230 frontline workers coming from an astonishing array of occupational backgrounds including surgeons, care workers, teachers, GPs, youth workers, nurses, mental health workers, pharmacists, train and bus drivers, and physiotherapists. Initially our treatments tended to focus on providing preventative herbal formulae with a smaller number of people presenting with acute disease.

Over time there has been an increasing emphasis on helping people with the debilitating chronic symptoms of Long Covid. In light of the recent introductions of the vaccine we decided that from January 2021 we should focus our limited resources on supporting people with acute disease and with Long Covid.

In addition to the generous support of Earthsong we have raised over £10,000 in donations from professional bodies and individuals who have want to help the project, or who have been the recipients of JSP treatments. This is fantastic but unfortunately it is not enough to enable us to continue providing free herbal care-especially to patients with Long Covid who require complex and expensive interventions to help restore them to good health and enable their return to work. We need to find new sources of funding to enable us to continue to provide herbal support to frontline workers who have risked their health to provide vital services that we all depend on.

We are a group of experienced practitioners and researchers of Chinese herbal medicine (CHM) who want to make a positive contribution during the current pandemic. We are committed to providing accessible, high quality, evidence-based care using herbal medicines.

We are very moved by the response from the CHM community, who have registered as JSP practitioners and are all offering their services free of charge.

As a measure of our offering the best service we can, we have elected to choose practitioners for our service who are registered members of their professional association, so we can be sure of the high standard of the treatment we are offering.

These practitioners have also undergone specialised training in Covid-19 infection management based on research from Chinese treatment protocols currently used in the pandemic.

We also carried out our own survey of experienced practitioners based in different countries to find out their own clinical CHM experience with patients who have been affected by COVID-19.

Chinese herbal medicine (CHM) is an ancient system of medicine developed and refined in China and other East Asian countries over the past 2000 years, using the active compounds available from hundreds of different plants. Although they are not refined and isolated as they are in modern drugs these plants enable what has been described as a polypharmacy that allows many compounds to operate together to generate a therapeutic effect.

CHM herbal formulas are normally between 10-15 different herbs containing plant extracts that have immune-regulating, anti-viral, and anti-inflammatory effects. These individualised formulas are worked out after the practitioner notes down the precise nature of the symptoms, as well as any underlying health conditions and medication being taken.

CHM has demonstrated a preventative effect in previous coronavirus epidemics – a large study from 2003 during the SARS outbreak in Hong Kong compared 1,063 healthcare workers taking CHM with 36,111 who did not, and found that those who did had a much lower infection rate.

CHM is part of an array of support and advice that a qualified herbalist can offer. Having seen the evidence from both our clinical practice and research into the benefits of herbal medicine, we feel strongly about stepping forward to support those who are putting their lives on the line, and helping them during this incredibly difficult and stressful time.

We have seen in our clinics the results of the support we offer our clients, and through researching treatment protocols used over centuries in response to pandemics, infectious respiratory diseases and rehabilitation from chronic illness, we strongly believe that our skills and experience will be useful for those right at the edge of the crisis. 

A final word on how we are evaluating the project. In April we submitted a research proposal on preventative care to St Thomas’s Hospital and over the summer we had discussions with the Department of Primary Care in Southampton University about a research project treating patients with Long Covid.

Sadly, for reasons that to be frank escape me, neither project was considered to be worth developing. In the absence of formal academic support we have used MYMOP (a validated patient centred outcomes measure) to assess the results of our interventions and we have also conducted a number of in-depth interviews with JSP patients to explore their experience of the project.

We are currently conducting a service evaluation to look at all aspects of what we do that will hopefully result in quantitative and qualitative data being written up and published. We hope that this might provide a rigorous rationale to persuade funders and professional researchers to investigate the project.

There are studies on the front page of the Jade Screen Project website, for those interested in the science behind CHM being able to supress viral replication, and inhibition of the SARS protein entering the cell’s receptor sites, which is how the virus enters the cells. There are also studies showing how herbs may have anti-inflammatory and immunoregulatory effects by reducing cytokine levels and enhancing immune mechanisms.

Several studies have confirmed the ability of mushrooms in general to increase the effectiveness of both our innate and adaptive immune response to a range of pathogens, including viruses. Reishi has a strong anti-inflammatory activity, as well as the quality to curb viral replication. Covid-19 enters cells via angiotensin-converting receptors, which the triperpenes and proteins from Reishi have been shown to block.

Herbs such as Patchouli and Japanese Knot Weed are considered to have anti-inflammatory and immune-protective qualities, that are amongst a wide range of herbs available to herbalists. These three herbs in particular are very useful in our formulae, where we call them by their Chinese names of Ling Zhi, Huo Xiang and Hu Zhang.

“Good luck with the project and everything. I hope that would be great to see it more in the mainstream and helping more and more people because I know it can do that now.” – JSP service user

In the meantime we soldier on, making a small but meaningful contribution in the fight against Covid-19. My experience, and that of my colleagues, is that CHM can help manage acute disease and significantly speed up recovery from Long Covid. I hope we can find a way to continue and develop the support we provide to frontline workers and to extend it to the growing numbers of people who have been laid low by this disease.

We’re not asking the people on the frontline to pay for either the herbs, or the consultations, as we feel they deserve our support and have put their lives on the line for all of us.

All donations we receive will go towards paying for their herbs. Our time, research and consultations are being gifted as a token of our thanks for their courageous work. We are hopeful that our support will help to protect those who are in such a perilous situation.

All the money donated via our donation pages goes directly to paying for the herbs, which have been provided at a generous discount, allowing your money to go even further.

All admin costs are covered by internally generated donations, meaning all our fundraising from the public can go directly to covering the cost of the herbs.

Please help us to support those who really deserve it! If you can’t support us financially, please do share our page on Facebook and Instagram, and let your friends know, especially if they are working on the front-line and you feel they would benefit from our support.

All donations that were received by the Jade Screen Project went towards funding herbal medicine for our frontline workers.