The chatbot economy: 4 verticals where bots are soaring

If money talks, these days it's shouting from the rooftops about generative AI.

Enterprise spending on consumer-facing generative AI tools will grow from $40 billion in 2023 to a cool $1.3 trillion by 2032, according to a Bloomberg Intelligence analysis.

Where will companies pour those hundreds of billions? More than 80% of business leaders believe that the best bang for their gen AI buck is in chatbots for automating customer service and improving knowledge management, according to a Capgemini survey of 1,000 companies in 13 countries.

The chatter of bots has been a staple of daily life since Siri debuted on the iPhone 4 in 2011, but consumer interactions have often been plagued by fumbling responses and stilted syntax, leading to customer dissatisfaction.

Despite steady advances in natural language processing and sentiment analysis, 3 in 5 consumers still suffered frequent disappointment in their chatbot interactions as recently as 2022, according to a Zendesk CX Trends report.

But generative AI has the potential to flip the script. As 100 million users discovered in the two months after ChatGPT’s explosive November 2022 debut, chatbots trained on large language models are capable of analyzing and synthesizing mounds of data in real time, generating contextually intelligent responses and maintaining human-like natural language flow.

Read also: How machines learned to chat

For industries across the board, a chatbot that is actually good at chatting will be a customer- and employee-experience game-changer. Here are four verticals where companies are betting the payoff will be sky-high.

Healthcare

The market for healthcare chatbots globally was valued at $212 million in 2022. That’s projected to more than triple to $647 million by 2030, according to Vantage Market Research.

Credit that growth to both front-of-practice patient interactions and back-office operations, where administrative staff could turn to AI-powered digital assistants to automate up to 73% of tasks, Insider Intelligence reports.

In direct patient interactions, expect the next generation of AI-powered chatbots to improve care for both caregivers and patients. For doctors and nurses, chatbots are already providing real-time answers to patient queries; advising on diagnoses, treatment, and medications based on the latest medical research; and speeding the logging of health records, freeing up time to devote to patient care.

For patients, experts envision a generative-AI-powered chatbot, with its potential for fluid conversation, functioning as a personal medical assistant. A chatbot app on a phone linked to a wearable device could monitor a patient’s chronic conditions or post-surgery recovery and talk with them about any symptoms they might be experiencing. In a life-or-death emergency, the bot could reach out to a caregiver or even 911 for immediate support.

The key to adoption is buy-in among healthcare professionals, and data suggests that the medical establishment is warming to the tech. Nearly half of doctors believe that ChatGPT is a valuable tool now, and 77% believe that chatbots will be able to treat patients safely within five to 10 years, according to a March 2023 survey by Software Advice.

Banking

Like healthcare, the banking sector is poised to nearly triple its chatbot investment by 2030, from $2.45 billion in 2022 to $6.9 billion, according to Verified Market Research.

Already banking customers are increasingly using chatbots in their everyday transactions. From 2021 to 2022 alone, the number of U.S. banking customers using chatbots for checking and savings account interactions doubled, Bain & Company research found.

With generative AI, banking bots will not only converse more fluidly, they will also be able to tap data and analytic insights more quickly. McKinsey projects that the greatest value of next-gen chatbots for banking will be in customer emergency response by partially automating, accelerating, and enhancing resolution of customer emergencies such as lost cards and stolen identities.

Other promising use cases for generative AI banking chatbots include guiding customers through loan applications, suggesting new financial products, advising on mortgage and debt repayment, and helping credit analysts by offering suggestions on loan underwriting.

Deloitte predicts that by 2026, generative AI bots will allow the top 14 global investment banks to boost their frontline customer support workers’ productivity 27%-35% by escalating issues requiring human intervention to agents and arming those workers with easy-to-understand summaries of ticket histories and actionable data.

Already chatbot companies like Kasisto (spun off from SRI International, the developer of Siri) are launching banking-specific generative AI chatbots to help bankers not only access and interpret customer data but also bank policies, regulatory filings, news content, and complex financial products.

And financial giant Morgan Stanley is testing a generative AI bot designed to help its thousands of wealth managers quickly find and synthesize data to offer investment advice for any client in real time.

Retail

At $12 billion, consumers’ global retail spending using chatbots is big in 2023. But Juniper Research projects that customers will be spending a whopping $72 billion using retail chatbots by 2028, a 5x increase.

The downside: When a problem arises with a purchase, only 25% of shoppers feel understood by traditional retail chatbots, according to a recent Capterra survey. But when it comes to interacting with ChatGPT, 67% of consumers feel understood, the same survey found.

Connect the dots, and the potential for generative AI to revolutionize the retail chatbot experience is enormous. McKinsey analysis pegs the value of curated shopping interactions and personalized marketing outreach at $400 billion to $660 billion annually.

For retailers, generative AI chatbots can leverage greater customer engagement through human-like conversations. Informed with customer and market insights, retail bots can make personalized recommendations to cross-sell and upsell.

And retailers are already experimenting with how to use generative AI for better customer engagement. Online retailer Stitch Fix, for one, is using Dall-E 2’s text-to-image capability to visualize a customer’s desired piece of clothing, translating text to match a similar article in Stitch Fix’s inventory and customizing its color, fabric, and style.

Insurance

In 2022, the global insurance sector spent $467 million on chatbot technology. That is projected to reach $4.5 billion by 2032, according to Allied Market Research.

No wonder, considering the eye-popping annual value that generative AI is predicted to add to the industry: $1.1 trillion, according to McKinsey. Of that staggering sum, the research firm sees insurers gaining $300 billion from customer service chatbots and personalized product offerings.

To reap those rewards, however, insurance firms will have to overcome the hurdle of customers’ reticence to solve issues with bots. As recently as May 2023, 44% of policyholders preferred talking with a human when discussing a claim, according to a Duck Creek Technologies survey. More troubling, that’s nearly a 10% increase from 2022.

Insurers are looking to generative AI to provide the human touch in customer service, with 23% piloting new chatbot technologies and 20% already deploying them since ChatGPT came on the scene, an Aite Novarica survey found.

Beyond direct customer interactions—from guiding new policyholders through applications and basic policy claims and providing them with 24/7 answers to basic queries—generative AI chatbots can assist human agents with personalized recommendations on insurance products and fielding complex claims issues.

Amid the blue-sky forecast of $1 trillion-plus value, industries embracing generative AI chatbots should proceed with caution. Case in point: a class-action lawsuit recently filed against insurance giant Cigna. Policyholders allege that the company relied on a proprietary algorithm to deny more than 300,000 medical claims over two months in 2022. The suit comes on the heels of a ProPublica report that the claims were rejected in batches, the time spent reviewing each one a mere 1.2 seconds.

It’s a sobering reminder as companies rush to unleash the potential of generative AI that with AI, it is always wise to tap the brakes first.

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