۷ Real Examples of Companies Using Chatbots for Business

Figure out if you need a chatbot to handle FAQs, offer personalized support or manage complex interactions. Getting clear on your goals will help you choose a service that fits your business needs. They use predefined scripts for simple queries and AI for more complex interactions, offering a balanced and flexible solution. When I saw that ChatGPT was the fastest-growing application in history, I initially thought that organizations would also benefit from a faster change culture. The significant impact of trust on attitude and BI is in accordance with mainstream reports.

Legacy systems may not easily integrate with modern AI technologies, creating compatibility issues. Let’s delve deeper to understand the role and use of AI in insurance, its benefits, use cases, impact, and current trends. “We have to understand when and where and why these models are acting a certain way and do some prompt engineering so that the models err on the side of fact, [not] err on the side of creativity,” says Ferranti. [It] can’t be put back in the bottle, and so, all we can do is try to use it in a way that’s responsible and thoughtful, and that’s what we’re trying to do,” says Ferranti.

Using chatbots and its AI assistant Maya, the company creates policies and handles user claims for both desktop and mobile. Plus, customers can choose which nonprofit organizations receive underwriting profits as part of the company’s annual “Giveback” initiative. Snapsheet digitizes the claims process with its AI tools and cloud-based claims management software. Snapsheet Cloud is an insurance platform that automates various parts of the claims process, reducing the time it takes to calculate appraisals and receive online payments. The company’s AI features also snuff out false claims, allowing insurance teams to operate with a higher degree of efficiency. CCC Intelligent Solutions digitizes and automates the entire claims process with artificial intelligence.

Artificial intelligence: Digital humanities, business, & society

IoT sensors and smart devices collect and transmit large volumes of information, creating a data explosion. This presents both challenges and opportunities for managing, analyzing, and making decisions based on this data. It is crucial for businesses to effectively handle this influx of data to stay competitive in today’s digital landscape. The massive insurance industry collects approximately $1 trillion in premiums every year. The total cost of non-health insurance fraud is estimated to be more than $40 billion per year, increasing the premium cost from $400 to $700 per year per family. Companies have been adopting emerging technologies like AI, RPA, and the Internet of Things (IoT) to increase operational efficiency.

• The future of the insurance industry may well see a blending of both approaches, leveraging the strengths of each to meet the evolving needs of consumers.
• This configuration specifies that the OpenAI’s text-davinci-003 model should be used as the main LLM.
• By using neural networks plugged into sources coming from internal and external data providers (including reinsurers and product manufacturers), insurers can present instant quotes.
• In addition, trust in these tools is driven by providing meaningful services that are considered a value-add.

This is especially true for one’s personal and financial information, which fraudsters are constantly finding new methods of breaching accounts to find. This need for security has also risen in insurance, and numerous AI firms are selling claims fraud detection solutions to the insurance sector. Datamation is the leading industry resource for B2B data professionals and technology buyers. Datamation’s focus is on providing insight into the latest trends and innovation in AI, data security, big data, and more, along with in-depth product recommendations and comparisons. Learn the latest news and best practices about data science, big data analytics, artificial intelligence, data security, and more.

AI Insurance Applications

The application of I4.0 technologies to the insurance industry creates value for the insurance company, and heterogeneous transformational capabilities are sources of competitive advantage (Stoeckli et al., 2018). They may enhance internal processes (e.g., exploiting data to handle claims), create new products, and develop new channels to provide professional advisory services. Cao et al. (2020) outline artificial intelligence (AI), machine learning, robotic process automatization, augmented reality/virtual reality, and blockchain as principal impacting technologies. These data could be transferred to the insurance company by using blockchain technology and then processed to fit policy prices by using AI algorithms such as those obtained from machine learning. This information may simplify underwriting because insured risk declaration is no longer needed (Ostrowska, 2021).

While the concept isn’t new, technological advances are priming parametric insurance to become a game changer in 2024, per EMARKETER’s Fintech Trends to Watch in 2024 report. While these make building use cases and workflows easy, solutions still must adhere to emerging ChatGPT AI regulation. Therefore, it’s important that these tools are rolled out hand-in-hand with training and upskilling on responsible AI practices. We don’t limit ourselves in use-case ideation, and we are doing our assessments as part of the solution design.

The National Association of Insurance Commissioners (NAIC) notes that many insurers have already invested in virtual assistants like chatbots. These chatbots offer digital services and can hold natural sounding conversations with human beings. Over the decades, they have accumulated mountains of data about families, homes, and businesses. However, it is often sitting in silos and not accessible to those on the front lines. It can piece together this abundance of unstructured data and leverage it to increase customer engagement, improve service personalization, and make marketing messages more meaningful. Natural language processing, (NLP) is one AI technique that’s finding its way into a variety of verticals, but the finance industry is among the most interested in the business applications of NLP.

Juniper Research projects that operational cost savings from for the banking industry will reach US$7.3 billion by next year, 30 times higher than projected savings in 2019. Users are no longer restricted to the limited opening hours of their local bank and use of technology in the financial services industry can save up to four minutes of time per enquiry — saving banks US$0.50 to US$0.70 per interaction. They must iteratively improvise and enhance the capability of their chatbots so that they are more in sync with the progress in conversational technologies. Failing to do so could potentially drive the feature-restricted, older-generation bots toward customer disuse. A simple rule-based chatbot could have completed the above transaction sooner with fewer questions and answers.

We will begin with State Farm, the #1 ranking insurance company based on the 2016 National Insurance Commissioners ranking. The greatest opportunities seem to lie, perhaps unsurprisingly, in claims and underwriting. According to our AI Opportunity Landscape in insurance, approximately 46% of AI vendors in insurance offer solutions for claims and 43% for underwriting. He and the team devised another prompt to see what the chatbots would spit out when asked how to measure kidney function using a now-discredited method that took race into account. ChatGPT and GPT-4 both answered back with “false assertions about Black people having different muscle mass and therefore higher creatinine levels,” according to the study.

AI algorithms can automatically verify and validate policy applications, identify discrepancies, and ensure compliance with regulatory requirements. This streamlines the policy issuance process, reducing the time required to issue new policies and renew existing ones. Personalised insurance products are more likely to meet customers’ specific needs, reducing the likelihood of policy cancellations and increasing retention rates. According to a report by Accenture, insurers that implement hyper-personalisation strategies can achieve a 15% increase in customer retention and a 10% increase in premium growth. For insurers, it represents a valuable opportunity to reach new customers and diversify distribution channels. By partnering with retailers, automakers, and other businesses, insurers can tap into a broader customer base and offer tailored insurance solutions that meet specific needs.

Marketers can easily generate high-quality copy, images, and videos based on a single brief, which enables them to quickly produce consistent and engaging content for entire campaigns, enhancing brand messaging and audience engagement. You can foun additiona information about ai customer service and artificial intelligence and NLP. Its analytics tools measure campaign performance and give insights that help refine and optimize future chatbot insurance examples marketing strategies. Midjourney stands out for its capacity to transform brief textual prompts into vivid, imaginative visuals, making it an invaluable tool for advertisers and marketers. The video app’s generative capabilities push the boundaries of creative expression, enabling brands to stand out in a saturated digital landscape.

Data using Woebot, she says, has been published in peer-reviewed scientific journals. And some of its applications, including for post-partum depression and substance use disorder, are part of ongoing clinical research studies. The company continues to test its products’ effectiveness in addressing mental health conditions for things like post-partum depression, or substance use disorder. Woebot, a text-based mental health service, warns users up front about the limitations of its service, and warnings that it should not be used for crisis intervention or management. If a user’s text indicates a severe problem, the service will refer patients to other therapeutic or emergency resources.

Nauto is a driverless car company focused on preventing collisions within commercial fleets by mitigating distracted driving. Their AI-driven driver safety system makes use of a dual-facing camera, computer vision (CV), and sophisticated algorithms to identify unsafe behaviors in real-time and take appropriate action in an effort to improve safety and lower accident rates. ZestFinance displays one of the best examples of AI applications in insurance by harnessing the power of AI to evaluate both traditional and non-traditional data. By automating the underwriting process, they enhance profitability and minimize risk. AI-powered chatbots can cross-sell and upsell products based on the customer’s profile and history. Automating the repetitive process allows operations to be scaled up easily while utilizing human resources in more strategic roles.

Machine Learning in Human Resources – Applications and Trends

There are some innovative solutions out there and we’ve had engagement with parties offering plug in solutions that may benefit our Magenta system. We’re excited to get this into our roadmap this year if these solutions are embraced by the industry and are cost effective enough to drive some real benefit. In an increasingly digitalized landscape, chatbots have become an indispensable component for customer engagement and self-service in the insurance industry. Cheung believes that RAG-based conversational solutions will greatly improve companies’ ability to retrieve and present targeted information to their customers or employees. “With domain-specific Q&A use cases, this technology can greatly improve productivity. RAG frameworks can be used in scientific research to help researchers accelerate new discoveries,” he added. Massive Bio, a biotechnology company, has introduced the use of ChatGPT in the process of recruitment for clinical trials.

In fact, healthcare chatbot’s market size was valued at $194.85 million in 2021 and is forecasted to reach $943.64 million by 2030, according to Verified Market Research study. The user experience kicks off with a quiz where customers pick photos to define their style. The bot then lets users save, share, search for outfits and redirect to the H&M site for purchases. Our most recent Index report also found that the vast majority of consumers (69%) expect a response from brands on social within the same day. This research shows that audiences are all in on social media customer service, and they expect the same from brands.

• High inbound message volumes and rising customer care standards have left support teams hustling to keep resolution times low.
• IBM claims to have helped a leading insurance provider organize their data from large storage systems and multiple sources.
• Customer service is crucial in the banking industry, and good customer service can often differentiate one institution from another and retain valuable customers, including high-net-worth individuals.
• This entails the search for and evaluation of information about potential insurers capable of providing suitable protection.
• It allows businesses to construct chatbots by using its drag-and-drop feature, which can respond to client inquiries, give support, and even drive transactions.
• If you’ve contacted your bank recently, there’s a good chance you’ve engaged with an AI chatbot or a voice recognition system.

With the rise of connectivity, insurers can now utilize a wide range of IoT devices, such as smart home assistants, fitness trackers, telematics, and healthcare wearables, to gather extensive data effortlessly. This allows adjusters and claims managers to proactively manage claims, focusing their efforts where needed. Everyone benefits from this approach; workers get the specific treatment they need sooner and recover from injuries more quickly, claims costs are reduced and management efficiencies are improved. The DocsGPT site includes an expanding library of medical prompts in which the AI-based writing assistant has been trained on health care-specific prose. Koko, a nonprofit online mental health support platform, stirred up consent controversy earlier this year. In January, the company’s co-founder Rob Morris, PhD, took to X (then Twitter) to share the results of an experiment.

Asking standard questions

About half of states are using chatbots to support their unemployment insurance websites. Nearly three-quarters of states have employed chatbots to assist government employees providing services related to the COVID-19 pandemic, according to a report published Wednesday by the National Association of State Chief Information Officers. The evidence for stochastic parroting is fundamentally incontrovertible, rooted in the very nature of the technology. The tool applied to solve many natural language ChatGPT App processing problems is called a transformer, which uses techniques called positioning and self-attention to achieve linguistic miracles. Every token (a term for a quantum of language, think of it as a “word,” or “letters,” if you’re old-fashioned) is affixed a value, which establishes its position in a sequence. The positioning allows for “self-attention”—the machine learns not just what a token is and where and when it is but how it relates to all the other tokens in a sequence.

Banks can deploy chatbots to assist users in applying for loans and to guide them through the application procedure. In a global market that makes room for more competitors by the day, some companies are turning to AI and machine learning to try to gain an edge. Supply chain and inventory management is a domain that has missed some of the media limelight, but one where industry leaders have been hard at work developing new AI and machine learning technologies over the past decade. In Allstate’s 2017 annual report, the company discussed a multi-year effort to hone the expertise of its agents with a goal of positioning them as “trusted advisors” for their customers. In the full article below, we’ll explore the AI applications of each insurance company individually.

But that’s no reason to doubt the underlying AI technology behind this business, as AI and machine-learning algorithms are designed to make inferences and judgments using large amounts of data. Figure 14 gives the second level of the WhatsApp data flow diagram decomposition of the above business operations. Given the increased usage and advancement of AI over the past few years, it’s likely the technology is here to stay. This opens up the possibility of launching assistants in narrower areas where data is cleaner, without having to overhaul the master data across the entire enterprise to achieve an AI result. As we started exploring what we could do together, it felt like we could figure out a way to use our own Help Center [documentation] to answer customers through the bot. So if you are just looking for an answer, it’s a great resource for our customers.

The lack of a human touch can make these systems appear less reliable than someone who can give personalized advice and answer queries in real-time. For example, insurance claims processing can be done via the online portal instead of in-person, reducing the number of resources required for communication and follow up procedures. 1-800-Flowers, the biggest gifting retailer in the US, uses AI to make shopping a breeze. Their virtual assistant, GWYN (gifts when you need them), helps users find the perfect gift with smart, contextual suggestions. GWYN is also great at meeting new customers where they already are—on Facebook Messenger. According to Digiday, GWYN has brought in many new customers, especially younger ones.