AI-Powered Chatbots for Healthcare: Overview

The ultimate aim should be to use technology like AI chatbots to enhance patient care and outcomes, not to replace the irreplaceable human elements of healthcare. Machine learning, a key component of AI used in healthcare, has significantly reshaped healthcare by enhancing medical diagnosis and treatment. By processing vast amounts of clinical data, algorithms can identify patterns and predict medical outcomes with unprecedented accuracy. You can foun additiona information about ai customer service and artificial intelligence and NLP. This technology aids in analyzing patient records, medical imaging, and discovering new therapies, thus helping healthcare professionals improve treatments and reduce costs.

This doctor-patient relationship, built on trust, rapport, and understanding, is not something that can be automated or substituted with AI chatbots. Additionally, while chatbots can provide general health information and manage routine tasks, their current capabilities do not extend to answering complex medical queries. These queries often require deep medical knowledge, critical thinking, and years of clinical experience that chatbots do not possess at this point in time [7]. Thus, the intricate medical questions and the nuanced patient interactions underscore the indispensable role of medical professionals in healthcare. This form of AI in healthcare is quickly becoming a must-have in the modern healthcare industry and is likely to become even more sophisticated and be used in a wider range of applications.

Greenlight Guru, a medical technology company, uses AI in its search engine to detect and assess security risks in network devices. The company specializes in developing medical software, and its search engine leverages machine learning to aggregate and process industry data. Meanwhile, its risk management platform provides auto-calculated risk assessments, among other services.

In addition, chatbots can help to improve communication between patients and medical staff. Global consulting firm ZS specializes in providing strategic support to businesses across various sectors, with a particular focus on healthcare, leveraging its expertise in AI, sales, marketing, analytics and digital transformation. ZS helps clients navigate complex challenges within industries such as medical technology, life sciences, health plans and pharmaceuticals, using advanced AI and analytics tools.

Reduce care costs

The complex nature of these systems frequently shrouds the rationale behind their decisions, presenting a substantial barrier to cultivating trust in their application. If certain classes are overrepresented or underrepresented, the resultant chatbot model may be skewed towards predicting the overrepresented classes, thereby leading to unfair outcomes for the underrepresented classes (22). One notable algorithm in the field of federated learning is the Hybrid Federated Dual Coordinate Ascent (HyFDCA), proposed in 2022 (14).

While the integration of AI chatbots into healthcare services offers numerous advantages, it is essential to exercise caution and ensure that AI technology is used responsibly. AI chatbots should not be seen as a replacement for human healthcare providers but rather as a tool that can complement and support their work. A chatbot in healthcare can be used to schedule appointments with doctors or other medical professionals. The chatbot will ask the patient a series of questions, such as the reason for the visit, and then use that information to schedule an appointment. It can save time for both patients and medical professionals and helps to reduce no-shows by sending reminders to patients. This is also used to remind patients about their medications or necessary vaccinations (e.g. flu shot).

The therapist often spends about a third of the total appointment time collecting anamnesis. Medical chatbots offer a solution to monitor one’s health and wellness routine, including calorie intake, water consumption, physical activity, and sleep patterns. They can suggest tailored meal plans, prompt medication reminders, and motivate individuals to seek specialized care.

Once this has been done, you can proceed with creating the structure for the chatbot. All these platforms, except for Slack, provide a Quick Reply as a suggested action that disappears once clicked. Users choose quick replies to ask for a location, address, email, or simply to end the conversation. A friendly and funny chatbot may work best for a chatbot for new mothers seeking information about their newborns. Still, it may not work for a doctor seeking information about drug dosages or adverse effects.

These features may include voice assistance, a knowledge center, appointment scheduling, a 24/7 presence, and much more. While chatbots can never fully replace human doctors, they can serve as primary healthcare consultants and assist individuals with their everyday health concerns. This will allow doctors and healthcare professionals to focus on more complex tasks while chatbots handle lower-level tasks.

It can also weed out people who are not interested in a personal visit, and even give initial recommendations for starting treatment. Chatbots can collect and process data in order to deliver a personalized experience for customers. Smart assistants may give you advice, recommend related products or services, and remind you of key dates.

These processes, while critical for ensuring safety and efficacy, can be time-consuming and resource-intensive. Consequently, addressing the issue of bias and ensuring fairness in healthcare AI chatbots necessitates a comprehensive approach. This includes being cognizant of the potential for bias in the data and the model development process, as well as actively implementing strategies to mitigate such bias (24). Furthermore, ongoing monitoring of deployed chatbot models is also required to detect and correct any emergent bias. Only through such multi-faceted efforts can we hope to leverage the potential of AI chatbots in healthcare while ensuring that their benefits are equitably distributed (16). As federated learning continues to evolve, researchers and practitioners are actively exploring various techniques and algorithms to address the complexities of healthcare data privacy, security, and regulatory compliance (15).

Appointment scheduling

Similarly, a picture of a doctor wearing a stethoscope may fit best for a symptom checker chatbot. This relays to the user that the responses have been verified by medical professionals. Similarly, conversational style for a healthcare bot for people with mental health problems such as depression or anxiety must maintain sensitivity, respect, and appropriate vocabulary. A drug bot answering questions about drug dosages and interactions should structure its responses for doctors and patients differently. Woebot is a chatbot designed by researchers at Stanford University to provide mental health assistance using cognitive behavioral therapy (CBT) techniques.

The world witnessed its first psychotherapist chatbot in 1966 when Joseph Weizenbaum created ELIZA, a natural language processing program. It used pattern matching and substitution methodology to give responses, but limited communication abilities led to its downfall. The benefits are many, particularly when conversational AI is viewed as a strategic tool for enhancing patient engagement and satisfaction.

By leveraging the capabilities of ChatGPT, healthcare providers can automate certain aspects of patient communication, allowing them to focus on more complex and critical tasks. Developed using advanced natural language processing techniques, ChatGPT has the ability to generate human-like text responses to a wide range of topics. It has quickly gained recognition for its ability to provide quality and empathetic responses to patient questions, as demonstrated in a recent research study. In this study, ChatGPT’s responses to patient questions posted on a public social media forum were compared to those of physicians. The results showed that evaluators preferred ChatGPT’s responses over physician responses in a majority of cases, with the chatbot receiving higher ratings for both the quality of information provided and the empathy conveyed. In March, the University of Kansas health system started using medical chatbots to automate clinical notes and medical conversations.

By automating certain aspects of patient communication, chatbots can help prevent healthcare professionals from becoming overwhelmed and improve their overall well-being. In conclusion, the integration of ChatGPT and other AI chatbots into the healthcare industry has the potential to transform patient communication and improve healthcare outcomes. By leveraging the capabilities of AI technology while maintaining human oversight and ethical standards, we can create a healthcare system that is more efficient, responsive, and patient-centered.

Nevertheless, the advent of the digital age has presented both opportunities and challenges to traditional healthcare communication approaches. AI chatbots need lots of data to train their algorithms, and some top-rated chatbots like ChatGPT will not work well without constantly collecting new data to improve the algorithms. This implies that AI chatbots will continue to compromise data security and privacy. Nevertheless, there are many ways to improve the collection, use, and disclosure of data, including overall data management and the algorithms themselves. Future studies are required to explore data desensitization methods, secure data management, and privacy-preserving computation techniques in web-based AI-driven health care applications. Another challenge involves the data provided to ChatGPT in the form of user prompts.

• With this conversational AI, WHO can reach up to 1 billion people across the globe in their native languages via mobile devices at any time of the day.
• Chatbots can also provide reliable and up-to-date information sourced from credible medical databases, further enhancing patient trust in the information they receive.
• Additionally, bots can also access medical records and databases to provide doctors with more accurate information.
• Additionally, deep learning, a subset of AI, is used in healthcare for tasks like speech recognition through natural language processing.
• According to the analysis made by ScienceSoft’s healthcare IT experts, it’s a perfect fit for more complex tasks (like diagnostic support, therapy delivery, etc.).

Chatbots with access to medical databases retrieve information on doctors, available slots, doctor schedules, etc. Patients can manage appointments, find healthcare providers, and get reminders through mobile calendars. This way, appointment-scheduling chatbots in the healthcare industry streamline communication and scheduling processes. A healthcare chatbot is an AI-powered software program designed to interact with users and provide healthcare-related information, support, and services through a conversational interface.

Our journey takes us through the evolution of chatbots, from rudimentary text-based systems to sophisticated conversational agents driven by AI technologies. We delve into their multifaceted applications within the healthcare sector, spanning from the dissemination of critical health information to facilitating remote patient monitoring and providing empathetic support services. Healthcare payers and providers, including medical assistants, are also beginning to leverage these AI-enabled Chat GPT tools to simplify patient care and cut unnecessary costs. Whenever a patient strikes up a conversation with a medical representative who may sound human but underneath is an intelligent conversational machine — we see a healthcare chatbot in the medical field in action. Chatbots are software developed with machine learning algorithms, including natural language processing (NLP), to stimulate and engage in a conversation with a user to provide real-time assistance to patients.

As healthcare becomes increasingly complex, patients have more and more questions about their care, from understanding medical bills to managing chronic conditions. The need for a more sophisticated tool to handle these queries led to the evolution of chatbots from simple automated responders to query tools that can handle complex patient inquiries. By handling these actions, healthcare professionals can focus their energy where it’s needed most, on complex care tasks. In the fast-paced healthcare industry, healthcare organizations are fiercely competing to raise the bar and ensure they provide reliable and personalized medical assistance. Patients expect real-time support covering the full spectrum of health topics, from well-being and mental health to medical advice on health issues.

The Physician Compensation Report states that, on average, doctors have to dedicate 15.5 hours weekly to paperwork and administrative tasks. With this in mind, customized AI https://chat.openai.com/ chatbots are becoming a necessity for today’s healthcare businesses. The technology takes on the routine work, allowing physicians to focus more on severe medical cases.

Chatbots collect patient information, name, birthday, contact information, current doctor, last visit to the clinic, and prescription information. The chatbot submits a request to the patient’s doctor for a final decision and contacts the patient when a refill is available and due. The proportion of responses rated as “empathetic” or “very empathetic” (a score of 4 or higher) was 45.1% for the chatbot, compared to just 4.6% for physicians. This amounted to a 9.8 times higher prevalence of empathetic or very empathetic responses for the chatbot. The results of the study were striking, revealing a strong preference for ChatGPT responses over physician responses.

Users usually prefer chatbots over symptom checker apps as they can precisely describe how they feel to a bot in the form of a simple conversation and get reliable and real-time results. A healthcare chatbot also sends out gentle reminders to patients for the consumption of medicines at the right time when requested by the doctor or the patient. Patients appreciate that using a healthcare chatbot saves time and money, as they don’t have to commute all the way to the doctor’s clinic or the hospital. Among these tools, AI chatbots stand out as dynamic solutions that offer real-time analytics, revolutionizing healthcare delivery at the bedside. These advancements eliminate unnecessary delays, effectively bridging the gap between diagnosis and treatment initiation.

In the realm of healthcare, LLM healthcare chatbots offer a promising avenue for enhancing patient care and streamlining administrative workflows. They can automate bothersome and time-consuming tasks, like appointment scheduling or consultation. An AI chatbot can be integrated with third-party software, enabling them to deliver proper functionality. Such an interactive AI technology can automate various healthcare-related activities.

Stay on this page to learn what are chatbots in healthcare, how they work, and what it takes to create a medical chatbot. With that being said, we could end up seeing AI chatbots helping with diagnosing illnesses or prescribing medication. We would first have to master how to ethically train chatbots to interact with patients about sensitive information and provide the best possible medical services without human intervention.

What is an example of using AI chatbots in healthcare?

This free AI-enabled chatbot allows you to input your symptoms and get the most likely diagnoses. Trained with machine learning models that enable the app to give accurate or near-accurate diagnoses, YourMd provides useful health tips and information about your symptoms as well as verified evidence-based solutions. Furthermore, it is important to engage users in protecting sensitive patient and business information. For many people, it might be common sense not to feed ChatGPT PHI, source code, or proprietary information; however, some people might not fully understand the risks attached to it.

Patients can quickly assess symptoms and determine their severity through healthcare chatbots that are trained to analyze them against specific parameters. The chatbot can then provide an estimated diagnosis and suggest possible remedies. Chatbots gather user information by asking questions, which can be stored for future reference to personalize the patient’s experience. With this approach, chatbots not only provide helpful information but also build a relationship of trust with patients.

A recent study showed that after chatting with a chatbot on an asthma website, users were able to take a test that would have otherwise been difficult to access. Chatbots can be used on social media to help answer questions and make users feel more comfortable with their healthcare decision. They are ideal for answering questions that people have about insurance, prescriptions, and health-related matters. A chatbot needs training data in order to be able to respond appropriately and learn from the user.

Chatbots provide 24/7 availability, allowing patients to access information and support whenever needed, increasing their engagement with the healthcare system. They can answer basic questions, schedule appointments, and manage tasks, all within the comfortable environment of a digital interface, attracting patients who prefer a self-service approach. Talking about healthcare, around 52% of patients in the US acquire their health data through healthcare chatbots, and this technology already helps save as much as $3.6 billion in expenses (Source ). Challenges like hiring more medical professionals and holding training sessions will be the outcome.

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However, with the use of a healthcare chatbot, patients can receive personalized information and recommendations, guidance through their symptoms, predictions for potential diagnoses, and even book an appointment directly with you. This provides a seamless and efficient experience for patients seeking medical attention on your website. Harness the full potential of healthcare chatbots and create a more engaging and efficient experience for your patients and healthcare professionals.

Share information about your working hours, clinicians, treatments, and procedures. Explainable AI (XAI) emerges as a pivotal approach to unravel the intricacies of AI models, enhancing not only their performance but also furnishing users with insights into the reasoning behind their outputs (26). The Rule requires that your company design a mechanism that encrypts all electronic PHI when necessary, both at rest or in transit over electronic communication tools such as the internet. chatbot technology in healthcare Furthermore, the Security Rule allows flexibility in the type of encryption that covered entities may use. This safeguard includes designating people, either by job title or job description, who are authorized to access this data, as well as electronic access control systems, video monitoring, and door locks restricting access to the data. Using these safeguards, the HIPAA regulation requires that chatbot developers incorporate these models in a HIPAA-complaint environment.

With the use of sentiment analysis, a well-designed healthcare chatbot with natural language processing (NLP) can comprehend user intent. The bot can suggest suitable healthcare plans based on how it interprets human input. ScienceSoft is an international software consulting and development company headquartered in McKinney, Texas. They can also take action based on patient queries and provide guidance on the next steps.

In drug discovery, AI accelerates the drug development process by predicting how different drugs will react in the body, significantly reducing the time and cost of clinical trials. AI chatbots have the potential to aid healthcare professionals by drafting responses to patient inquiries that can then be reviewed and edited by clinicians. This approach ensures that patients receive accurate and personalized information while still benefiting from the efficiency and speed of AI technology. As we have seen, AI chatbots like ChatGPT have the potential to revolutionize the way healthcare providers interact with patients.

Kaia Health also features a PT-grade automated feedback coach that uses AI technology. Deepcell uses artificial intelligence and microfluidics to develop technology for single-cell morphology. The company’s platform has a variety of applications, including cancer research, cell therapy and developmental biology. The primary goal of BenevolentAI is to get the right treatment to the right patients at the right time by using AI to produce a better target selection and provide previously undiscovered insights through deep learning. BenevolentAI works with major pharmaceutical groups to license drugs, while also partnering with charities to develop easily transportable medicines for rare diseases.

For example, the Health Insurance Portability and Accountability Act (HIPAA) imposes strict requirements on how patient data can be collected, used, and shared. Chatbots that collect or store patient data must take these requirements into account to avoid violating HIPAA. Healthcare chatbots handle a large volume of inquiries, although they are not as popular as some other types of bots. Medical chatbots help the patient to answer any questions and make a more informed decision about their healthcare. They answer questions outside of the scope of the medical field such as financial, legal, or insurance information. An internal queue would be set up to boost the speed at which the chatbot can respond to queries.

It uses natural language processing (NLP) and Machine Learning (ML) techniques to understand and respond to user queries or requests. McGuire said chatbots can allow healthcare providers to offer unprecedented access to tailored medical advice. Detailed chatbot inquiries can also help healthcare providers connect patients with the specific medical services they need.

Check for symptoms

They are not just tools for providing answers to common questions but have now become proactive interfaces capable of performing actions based on patient queries. The AI-driven chatbot, equipped with the necessary permissions and data access, can retrieve personalized billing information and offer to facilitate a payment transaction right within the chat interface. AI-powered healthcare chatbots are capable of handling simple inquiries with ease and provide a convenient way for users to research information. In many cases, these self-service tools are also a more personal way of interacting with healthcare services than browsing a website or communicating with an outsourced call center. In fact, according to Salesforce, 86% of customers would rather get answers from a chatbot than fill out a website form. While advancements in AI and machine learning could lead to more sophisticated chatbots, their potential to entirely replace medical professionals remains remote.

After the bot collects the history of the present illness, machine learning algorithms analyze the inputs to provide care recommendations. Healthcare chatbot use cases go a step further by automating crucial tasks and providing accurate information to improve the patient experience virtually. If you are interested in knowing how chatbots work, read our articles on voice recognition applications and natural language processing. Chatbots ask patients about their current health issue, find matching physicians and dentists, provide available time slots, and can schedule, reschedule, and delete appointments for patients. Chatbots can also be integrated into user’s device calendars to send reminders and updates about medical appointments.

Machine learning algorithms enable the system to learn from interactions, adapting and improving its responses over time. From those who have a coronavirus symptom scare to those with other complaints, AI-driven chatbots may become part of hospitals’ plans to meet patients’ needs during the lockdown. Many health professionals have taken to telemedicine to consult with their patients, allay fears, and provide prescriptions. Conversational chatbots can be trained on large datasets, including the symptoms, mode of transmission, natural course, prognostic factors, and treatment of the coronavirus infection.

A recent research study set out to investigate the effectiveness of an AI chatbot, ChatGPT, in comparison to physicians when it comes to answering patient questions. In this section, we will summarize the research study and highlight its key findings, which demonstrate the potential of ChatGPT to provide quality and empathetic responses to patient inquiries. While virtual healthcare has undeniably improved access to medical services, it has also placed a considerable burden on healthcare professionals. Each electronic message adds minutes of work to a clinician’s already busy schedule, contributing to longer working hours and increased after-hours work.

A medical bot can recognize when a patient needs urgent help if trained and designed correctly. It can provide immediate attention from a doctor by setting appointments, especially during emergencies. Discover what they are in healthcare and their game-changing potential for business.

Health care institutions that use ChatGPT should implement strict data security measures for the use and disclosure of PHI. They should conduct regular risk assessments and audits to ensure compliance with HIPAA and any applicable privacy law. It can also suggest when someone should attend a healthcare institution, when they should self-isolate, and how to manage their symptoms. Advanced conversational AI systems also keep up with the current guidelines, ensuring that the advice is constantly updated with the latest science and best practices. For doctors, AI’s analytical capabilities provide access to structured dashboards where all information gathered about each patient finds its home.

Of course, no algorithm can compare to the experience of a doctor that’s earned in the field or the level of care a trained nurse can provide. However, chatbot solutions for the healthcare industry can effectively complement the work of medical professionals, saving time and adding value where it really counts. Once again, answering these and many other questions concerning the backend of your software requires a certain level of expertise. Make sure you have access to professional healthcare chatbot development services and related IT outsourcing experts. Acropolium has delivered a range of bespoke solutions and provided consulting services for the medical industry.

Furthermore, this rule requires that workforce members only have access to PHI as appropriate for their roles and job functions. Furthermore, Rasa also allows for encryption and safeguarding all data transition between its NLU engines and dialogue management engines to optimize data security. As you build your HIPAA-compliant chatbot, it will be essential to have 3rd parties audit your setup and advise where there could be vulnerabilities from their experience. Before chatbots, we had text messages that provided a convenient interface for communicating with friends, loved ones, and business partners.

In the United States alone, more than half of healthcare leaders, 56% to be precise, noted that the value brought by AI exceeded their expectations. It’s advisable to involve a business analyst to define the most required use cases. Also, they will help you define the flow of every use case, including input artifacts and required third-party software integrations. It proved the LLM’s effectiveness in precise diagnosis and appropriate treatment recommendations.

For healthcare institutions when it comes to increasing enrollment for different types of programs, raising awareness, medical chatbots are the best option. The healthcare sector has turned to improving digital healthcare services in light of the increased complexity of serving patients during a health crisis or epidemic. One in every twenty Google searches is about health, this clearly demonstrates the need to receive proper healthcare advice digitally.

Some experts also believe doctors will recommend chatbots to patients with ongoing health issues. In the future, we might share our health information with text bots to make better decisions about our health. Case in point, people recently started noticing their conversations with Bard appear in Google’s search results.

This way, hospitals can release patients earlier and ensure a smoother transition while remotely monitoring their progress. Babylon is on a mission to re-engineer healthcare by shifting the focus away from caring for the sick to helping prevent sickness, leading to better health and fewer health-related expenses. Highly valuable information can sometimes get lost among the forest of trillions of data points.

Chatbots are conversation platforms driven by artificial intelligence (AI), that respond to queries based on algorithms. Since healthcare chatbots can be on duty tirelessly both day and night, they are an invaluable addition to the care of the patient. Among those who believe AI will make bias and unfair treatment based on a patient’s race or ethnicity worse, 28% explain their viewpoint by saying things like AI reflects human bias or that the data AI is trained on can reflect bias. Another reason given by 10% of this group is that AI would make the problem worse because human judgment is needed in medicine. These responses emphasized the importance of personalized care offered by providers and expressed the view that AI would not be able to replace this aspect of health care. Large language models (LLMs) have revolutionized the field of chatbots, enabling them to provide more natural, sophisticated and informative interactions.

For example, a chatbot may remind a patient to take their medication or schedule an appointment with their healthcare provider. While this capability offers benefits, such as improved patient outcomes and reduced healthcare costs, there are also potential drawbacks, such as privacy concerns and misinterpretation of patient queries. As mentioned previously, AI-based chatbots are trained using closed datasets that are not able to continuously update themselves to incorporate the most up-to-date information. This is particularly important in relation to health care, an area where clinical practice guidelines, best practices, and safety data are continuously changing. The lack of real-time updates to the content of chatbots could result in people receiving out-of-date information in response to their queries. The same can be true for human-to-human interactions; however, a health care provider does have the ability to access up-to-date information in real time, whereas an AI chatbot does not.

As a healthcare IT company, with over 10 years of experience, we provide a full cycle of AI solutions for a wide variety of healthcare needs. The AI-powered assistants have revolutionized patient care by providing plenty of benefits. Medical app investors and producers should prioritize developing effective, responsive, tailored assistants that can be trusted not to leak sensitive patient data. Health crises can occur unexpectedly, and patients may require urgent medical attention at any time, from identifying symptoms to scheduling surgeries. World-renowned healthcare companies like Pfizer, the UK NHS, Mayo Clinic, and others are all using Healthcare Chatbots to meet the demands of their patients more easily.

They can help to improve access to healthcare, reduce wait times, and improve patient outcomes. As technology continues to advance, we can expect to see even more innovative and sophisticated medical chatbots in the future. Artificial Intelligence in healthcare is changing many of the administrative aspects of medical care. Furthermore, artificial intelligence also has the potential to reduce human error by providing a faster way to review health records, medical imaging, claims processing and test results. With artificial intelligence giving medical professionals more autonomy over their workflow process, they are able to provide better quality patient care while maintaining budget efficiency.

H2O.ai’s AI analyzes data throughout a healthcare system to mine, automate and predict processes. It has been used to predict ICU transfers, improve clinical workflows and pinpoint a patient’s risk of hospital-acquired infections. Using the company’s AI to mine health data, hospitals can predict and detect sepsis, which ultimately reduces death rates. Proscia is a digital pathology platform that uses AI to detect patterns in cancer cells. The company’s software helps pathology labs eliminate bottlenecks in data management and uses AI-powered image analysis to connect data points that support cancer discovery and treatment. The Cleveland Clinic teamed up with IBM on the Discovery Accelerator, an AI-infused initiative focused on faster healthcare breakthroughs.

• Such an unobtrusive feedback channel allows patients to evaluate the quality of the clinic’s service, assess medical services, or leave a detailed review of services.
• In the context of patient engagement, chatbots have emerged as valuable tools for remote monitoring and chronic disease management (7).
• Skilled in mHealth app building, our engineers can utilize pre-designed building blocks or create custom medical chatbots from the ground up.
• Having 18 years of experience in healthcare IT, ScienceSoft can start your AI chatbot project within a week, plan the chatbot and develop its first version within 2-4 months.
• The body of evidence will continue to grow as AI is used more often to support the provision of health care.

For those who cannot read or who have reading levels lower than that of the chatbot, they will also face barriers to using them. Coghlan and colleagues (2023)7 outlined some important considerations when choosing to use chatbots in health care. Developers and professionals seeking to implement chatbots should weigh the risks and benefits by clearly defining the aim of the chatbot and the problem to be solved in their circumstances. There should be careful assessment of the problem to be solved to determine whether the use of AI or chatbots is an appropriate solution.