Conversational AI empowers a variety of business tasks, offering enhanced client experiences and higher operational efficiency. This technology impacts client communication and has already changed data-heavy industries like healthcare, finance, and logistics. According to Precedence Research, the global conversational AI market is experiencing rapid growth. It's expected to expand from USD 10.08 billion in 2022 to USD 86.42 billion by 2032 as more companies adopt this technology into their workflows.
In this article, we'll explore conversational AI trends in 2024, with a focus on how they can be applied in healthcare, logistics, and financial services. We’ll also feature real-world use cases and provide examples of conversational AI in action.
Conversational AI Use Cases and Trends in Healthcare
Building and implementing healthcare solutions is challenging. The complexity of the technology and the responsibility of handling protected health information often becomes a roadblock and creates lots of concerns for conservative companies looking for tried-and-true ways of increasing operational efficiency rather than investing in emerging technology. However, in the health-tech sector, some solutions are already leveraging conversational AI trends to enhance scalability, save costs and improve the client experience.
Let's turn our attention to the latest conversational AI trends that are reshaping the healthcare field.
AI-powered mental health support and counseling
LLM-powered chatbots, enhanced with Natural Language Processing (NLP), are adept at understanding user inputs and can respond in a way that matches the user's conversational tone. However, in mental health applications, simply mirroring speech patterns is insufficient. When these chatbots are developed and refined with the input of psychology experts, they gain the ability to respond with empathy. Such conversational AI systems are tailored to recognize symptoms of distress and offer comfort and support, ensuring users feel heard and validated when discussing medical or psychological challenges. Additionally, these solutions can conduct preliminary screenings, ask critical questions, and alert healthcare specialists to any dangerous tendencies or urgent needs.
Example: PTSD chatbot
Akvelon has built a chatbot based on GPT-4 combined with Langchain Memory Summarization that assists medical professionals in diagnosing and treating patients suffering from PTSD. This tool immediately alerts specialists if users exhibit suicidal thoughts or other dangerous behaviors. PTSD chatbot also has an integrated smart search algorithm that scours reputable medical journals, research papers, and articles to provide users with accurate and up-to-date information related to PTSD.
AI-driven symptom-checking chatbot
Accurate diagnosis is crucial for understanding patient needs, whether it’s for scheduling appointments with the right specialists or for pre-test consultations. A symptom-checking chatbot can greatly assist in this process. It can aid healthcare professionals in initial screenings and help patients determine which doctor they should see and what additional tests may be necessary. This type of LLM-powered chatbot, when properly trained, is far more effective than simply searching for symptoms online. It can guide patients in understanding their next steps. Such solutions are particularly valuable in remote or rural areas, where accessing medical expertise in person can be challenging due to logistics.
This symptom-checking chatbot asks patients questions to determine their symptoms and directs them to further steps of care.
AI-powered appointment scheduling tools
In a high-demand environment, managing appointments – including scheduling, rescheduling, and cancellations – can be administratively burdensome. The lack of scalability and limited communicational capacity can disrupt organizational efficiency and negatively impact patient experience.
On the other hand, patients are frequently unaware of different policies for late cancellations and rules that apply to appointments. Furthermore, preparing for appointments with certain specialists can add to this complexity. Traditional automation tools and chatbots struggle with custom queries, exacerbating the administrative load.
Conversational AI tools, however, excel in these areas. They can provide detailed responses based on pre-set policies, guide patients through procedure preparation, offer available time slots according to healthcare providers' schedules, and assist in various other ways. This capability significantly streamlines the appointment process, enhancing patient satisfaction and operational efficiency.
Example: Notable Assistant
This concierge-level tool provides easy options for scheduling, navigation, and payment, enhancing patient experience with conversational AI.
Intelligent QA chatbots
Intelligent QA chatbots have already become a popular solution in healthcare, providing immediate, 24/7 answers to urgent patient inquiries. These chatbots, powered by Large Language Models (LLMs), enhance the traditional Q&A sections on apps or websites. They offer a conversational experience, reducing the need for patients to sift through extensive service descriptions and pricing details. Additionally, these solutions learn from patient queries, adapting to the language used by patients to describe their needs. This mimics a human consultant's adaptability, efficiently saving healthcare personnel time that would otherwise be spent in direct communication with patients.
On the other hand, such tools can be used by healthcare specialists to access specific information within a protected database.
Example: Secure LLM-based HIPAA-compliant search within legal documents and patient records
Akvelon built an LLM-powered documentation chatbot that provides quick searches and answers patients’ and clinicians' questions. The solution was tested using our LLM Security Testing framework, encompassing best OWASP practices along with HIPAA compliance criteria.
AI for medical triaging
Both undertriage (insufficiently prioritizing serious conditions) and overtraining (excessively prioritizing less severe conditions) can lead to negative outcomes for patients and healthcare providers. Conversational AI can play a significant role in this scenario. In some instances, AI within healthcare makes more accurate triaging decisions than trained professionals. This is largely due to its comprehensive analysis of patients' symptoms and medical histories. With adequate investment and development, this technology has immense potential to improve triaging processes.
Example: Chillwall AI
Tailored to the urgency of the circumstance, this personalized white-label virtual assistant seamlessly guides users to the optimal support service, minimizing needless trips to the emergency room.
AI for health & medication management
Conversational AI can be crucial in supporting physicians and patients with medication management. In healthcare, LLM-driven chatbots can be used for analyzing patients’ lifestyles, preferences, and medical histories to offer personalized daily reminders and advice. Such chatbots enable patients to:
- Access detailed information about their medications and treatment plans easily.
- Monitor their medication stock and receive notifications for when refills are necessary.
- Ensure adherence to their medication schedules through timely reminders.
- Enhance their commitment to following their medication routines.
For physicians, AI's data analysis offer a streamlined view via structured dashboards. These dashboards are capable of consolidating all patient-related data, providing insights into adherence rates, medication details, and treatment follow-ups, all accessible with a simple click for each patient.
AI for engaging patients and managing aftercare
The frequency of interactions between patients and medical professionals can vary greatly based on the stage of their medical journey. Post-treatment individuals, for instance, might have regular appointments for check-ups, while largely managing their post-treatment regimen independently.
Misunderstanding or neglecting certain aspects of aftercare instructions can adversely affect a patient's recovery. Implementing a conversational AI platform can bridge this communication gap, aiding patients throughout their recovery. Patients could report their aftercare activities and current status in their treatment trajectory to this system. Consequently, the AI could provide timely reminders for essential tasks and notify doctors when necessary.
Gathering patient insights through conversational AI
Conversational AI technologies are adept at continuously gathering and analyzing vast amounts of patient data. This data serves as a crucial resource for healthcare professionals, enabling them to make informed decisions that enhance patient experiences and care quality.
Take, for example, a scenario where a conversational AI system frequently logs attempts by patients to book appointments with podiatrists, but they are often unable to do so in a timely manner. Analyzing this data can highlight a recurring issue, prompting the healthcare facility to consider increasing their podiatrist staff to meet patient needs.
Moreover, monitoring patient interactions with the AI system allows healthcare providers to identify and address any shortcomings in care delivery promptly. The nature of patients' queries can reveal much about their medical understanding, difficulties they may face in accessing clinic services, and more. This insight can guide healthcare providers in tailoring the information presented to patients, aiming to create more user-friendly and informative experiences.
LLM-powered documentation automation
As more healthcare professionals struggle with documentation inconsistency and spend hours on writing documentation, there are already conversational AI solutions that provide secure voice-to-text transcripts and are capable of delivering insights from the conversation and writing them down in a predefined format.
Such solutions save time for medical experts and prove to be extremely helpful in routine work automation.
This tool delivers documentation in real time, converting natural clinician-patient conversations into medical notes.
Trends of Conversational AI in Financial Services and Banking
Picture a world where automated intelligence not only understands but anticipates your client's needs, offering real-time solutions and insights. This is exactly how conversational AI transforms financial services from a task-oriented process to an experience-driven journey. It's not just about responding to queries; it's about engaging in meaningful dialogue and fostering deeper client relationships. This innovative technology streamlines workflows, reduces response times and elevates customer service to new heights.
Let’s explore conversational AI use cases in financial services and banking in detail.
Automated customer support
Conversational AI operates around the clock, ensuring that your customers receive prompt and accurate responses anytime, anywhere. Conversational AI-enhanced support chatbot doesn’t just solve problems; it builds relationships, fostering trust and loyalty through consistent, empathetic, and personalized interactions. By seamlessly blending human-like empathy with the efficiency of AI, conversational AI elevates customer experiences, driving satisfaction and transforming support into a strategic asset for your business. It's not just support; it's a game-changer in creating lasting customer relationships.
Conversational AI-driven chatbots that are tailored for finance and banking are capable of handling most client queries, such as:
- Personalized updates. Conversational AI can provide real-time updates on account balances, including recent transactions, helping users keep track of their finances effortlessly.
- Simplified transactions. Users can execute fund transfers between accounts with simple voice or text instructions, making the process faster and more convenient.
- Secure Authentication. Conversational AI can incorporate secure authentication processes, such as voice recognition or one-time passwords, ensuring safe and authorized transactions.
- Transaction Support. Chatbots can assist in selecting the right accounts for transfers, provide information on transfer limits, and even confirm transaction completion, offering a full-service experience.
Example: Customer support chatbot by Akvelon
This AI-powered chatbot enables automated query resolution and reduces the burden on live agents. It also offers scalability for high-volume user interactions, especially during peak traffic periods.
By analyzing intricate details such as spending habits, credit history, personal income, savings patterns, and even life goals, this intelligent technology is adept at crafting highly personalized financial advice. For instance, it can sift through a myriad of credit card options to recommend one that aligns perfectly with a user's spending trends and reward preferences, ensuring they reap maximum benefits.
Moreover, in the realm of loans and mortgages, conversational AI can navigate through complex product offerings, interest rates, and eligibility criteria to propose options that best fit the user's repayment capacity and financial goals. This level of customization extends to retirement planning and insurance products, where conversational AI assesses life stages, dependents, and future financial needs to provide well-rounded, holistic financial advice.
The platform is capable of offering advanced wealth management solutions, guides users to goal-based savings, and provides personalized insights and advice.
Conversational AI for financial documentation
Conversational AI for banking and finance can guide clients through the documentation process, asking relevant questions and prompting for necessary details, ensuring completeness and compliance. This technology can adeptly handle complex tasks such as verifying client identities, extracting key information from documents, and even updating client profiles in real time based on ongoing interactions. Furthermore, it can streamline compliance checks by cross-referencing data against regulatory requirements, and flagging any discrepancies for immediate attention.
Example: ConvAI-Powered Documentation Chat Services by Akvelon
This solution helps clients interact with documents naturally, asking questions and receiving instant responses for an engaging and informative experience, empowering scalable data-based conversations.
Automated ESG reporting
LLMs are capable of generating comprehensive Environmental, Social, and Governance (ESG) reports. Such solutions streamline the reporting process, crucial for sustainable investing, and integrate diverse data sources to create holistic ESG profiles. As a result, companies save time they would otherwise spend on creating reports.
Datamaran's AI platform arms business leaders with the confidence to expertly navigate the intricate ESG terrain. The tool has the ability to convert extensive data into actionable insights, providing a clear path to informed decision-making.
Other Conversational AI Use Cases
Conversational AI is progressively becoming the new norm for numerous businesses, amplifying workforce capabilities, streamlining processes, and curbing operational expenses. According to conversational ai market trends data from Precedence Research, industries beyond healthcare and finance that currently reap the benefits of ConvAI chatbots include real estate (28%), travel (16%), and education (14%). Furthermore, integrating conversational AI into processes proves to be notably easier and cost-effective for industries that lean towards innovation, unencumbered by legacy infrastructure requiring extensive updates for AI enhancement.
Let's delve into how conversational AI can be strategically employed across diverse industries, providing companies with a competitive edge in 2024.
Voice-powered shopping assistants
The evolution of conversational AI in e-commerce is anticipated to advance, particularly with the integration of voice-powered shopping assistants. These assistants are designed to enable consumers to make purchases directly through voice commands, providing personalized recommendations and ensuring a smooth, hassle-free shopping experience.
Example: Alexa AI (Amazon)
Alexa empowers everyone to create natural voice experiences, providing customers with an intuitive way to interact seamlessly with their everyday technology. The solution comprises a suite of tools, APIs, reference solutions, and comprehensive documentation, simplifying the process of building for Alexa and ensuring a user-friendly development experience.
Interactive learning companions based on ConvAI
Within the realm of education, AI-powered conversational agents function as personalized tutors. These agents adeptly adapt to individual learning styles, offering tailor-made educational content, insights, and assessments to enhance the learning experience.
Example: AI Study Assistant by Akvelon
This solution was created to increase learning efficiency while providing answers tailored to specific subjects based on a chatbot’s real-time searching, indexing, and crawling capabilities. While using it, students get personalized recommendations, find scholarships and internships, and use the chatbot to create a study plan.
AI travel advisors
Travel bots are poised to deliver increasingly personalized and interactive travel planning experiences. From suggesting destinations to crafting complete itineraries, these bots leverage individual preferences and past behavior to create tailored travel plans for a more engaging and customized journey.
Example: AI Trip Planner
Travelers can engage with the AI Trip Planner by asking general travel-related questions or seeking more specific information to support any stage of their trip planning process. This includes exploring potential destinations and accommodation options, receiving personalized travel inspiration based on individual needs and requirements, and generating detailed itineraries for a specific city, country, or region.
Fleet management AI-driven chatbots
Conversational AI proves valuable in optimizing fleet management and enhancing overall efficiency. Language models can play a pivotal role in streamlining fleet operations by accurately predicting maintenance requirements, optimizing routes, and efficiently managing logistics. This strategic approach not only reduces operational costs but also significantly improves efficiency, ultimately elevating the overall delivery experience for customers.
UPS has innovatively introduced a chatbot driven by AI to assist customers in tracking packages, locating UPS facilities, and obtaining shipping rates. Customers can engage in conversations with the bot using natural language through various platforms, including Facebook Messenger, Amazon Alexa, Skype, and UPS's mobile app. The outcome is a significantly enhanced customer experience across both chat and voice channels, aligning with the everyday communication preferences of consumers. Reportedly, the company has saved over $200 Million this year by integrating AI solutions into its workflows.
AI-powered lead generation
Conversational AI can be used to generate leads and qualify potential customers. Such solutions often help companies cut costs on finding new clients and retaining existing ones, combining conversational solutions with a tailored lead generation strategy.
Drift chatbots excel in tailoring the experience for each potential lead by considering factors such as their identity, source of arrival, engaged content, and current stage in the buying journey. This customization ensures a highly personalized interaction, optimizing engagement and aligning seamlessly with the individual needs and the stage of conversion.
Conversational AI is a rapidly evolving technology with a wide range of potential applications. More companies are looking to adopt AI-powered chatbots and augment their current workflows using new technology regardless of any concerns. In this article, we have outlined the most promising conversational AI trends and focused on conversational AI use cases that can be incorporated into one’s business, bringing both strategic and tactical benefits. Any of these solutions can be created and tailored to match the industry-specific privacy and security regulations. Moreover, Akvelon team has vast experience in creating solutions for healthcare and finance, e-commerce, and tech industries. We help other companies embrace innovation while diligently ensuring our solutions’ viability and alignment with specific business needs.