It's hard to miss the stream of noise around generative artificial intelligence.

Many companies are investing in generative AI — to the tune of $150 billion, according to a Sequoia Capital Valuation — because they are afraid of being left behind. At the same time, many are paralyzed by the fear that AI-generating hallucinations could damage their reputation. So what do founders, business leaders and investors need to know and do about this AI boom in order to capitalize and ensure their investments in the space are worthwhile?

There are two major industries—retail and healthcare—that are rolling out generative AI applications that appear to create significant value with interesting potential that can provide insights for others to implement.

As an associate professor of management practice at Babson College and with a background that includes working at an AI startup during my time at MIT and the author of three books on the dot-com boom, I have a deep understanding of technology waves and their economic impacts. I was inspired to explore this latest wave of technology and significant change in the AI ​​landscape in my latest book, Brain Rush: How to Invest and Compete in the Real World of Online Business.

Clearly, everyone should try using an AI chatbot like ChatGPT so they can put their fears to rest and learn how it can help them and where it doesn't work well. But will the benefits of AI-infused generating services make customers eager to buy them at a premium? It's too early to tell, of course.

Based on the investments that retail and healthcare companies are making in generative AI applications, here are early insights emerging for founders, business leaders and investors across other industries to begin capitalizing on the AI ​​boom.

Related: How a $10,000 investment in AI transformed my career and business strategy

Create new growth curves

Retailers are aiming to use generative AI to attract consumers and keep them shopping. A 2024 Google Cloud Report found that 50% of retailers surveyed were starting initiatives for it automate customer service “With 25% of respondents currently piloting such programs and 22% already deploying them.”

While retailers are trying out other generative AI applications, here are two with the highest potential to attract and retain consumers:

• Hyper-personalization. AI can enable retailers to create digital flyers that inform consumers of the best weekly deals based on their past purchases. A test of these digital flyers for a retailer found evidence of greater customer engagement – ​​specifically a 14% higher loyalty program sign-up rate, a 100% increase in click-through rates and “increased total sales in shop with 2% to 5% ” according to Oliver Wyman Forum.
• Improving customer service. Consumers prefer an AI-generated customer service agent because it's available around the clock and reduces call wait times, noted Oliver Wyman. Generative AI could boost productivity in the retail and consumer packaged goods industry by “up to 2% of annual revenue—an additional $400 billion to $660 billion,” according to Brain Rush.

The hyper-personalized digital flyer offers hope for generating a return on investment because it can drive faster growth. However, it remains to be seen whether retailers will significantly accelerate their revenues ahead of the cost of providing these digital flyers.

Related: 3 Big Mistakes Companies Are Making With AI That's Limiting Their ROI

Increases productivity

Healthcare providers are under pressure to achieve more with fewer resources while improving the quality of patient care. Providers are using generative AI for it simplify administrative taskssuch as answering patient questions and scheduling appointments, automating the transcription of patient conversations with healthcare providers, streamlining patient consent forms, and helping doctors diagnose patients.

Two such applications stand out for their value creation potential:

• Better information faster and less expensive. During the pandemic, patients were scrambling to get information about Covid-19. Health care providers struggled to hire and attract enough staff to handle patients' demand for such information. To solve the problem, healthcare providers tried to shift work from call center staff to patient self-service. Contra Costa Health Care, a California-based healthcare provider, used an AI-powered healthcare assistant to divert 80% of customer calls to its AI, saving $20 per call that Contra Costa would have to pay an outside contractor. That freed up Contra Costa staff time to answer other calls more quickly, improving the patient experience, he noted Brain Rush.
• More attentive, personalized service. When doctors meet with patients, they often record the conversation on a computer. For the patient and the doctor, typing is somewhat distracting. There is a risk that during transcribing, the physician may miss emotional cues from patients' facial expressions that may lead to important follow-up questions from the physician. Additionally, while asking questions and listening to patients' answers, doctors may not write down everything they hear on the computer. To solve these problems, the University of Kansas Health System made an AI-based generative tool available to doctors. Artificial intelligence reduced the time more than 2,000 doctors and other medical personnel spent on notes. AI created summaries of medical conversations from audio recorded during patient visits, reducing the more than two hours doctors typically spend on notes each day, according to Brain Rush.

While there is much more to discover about early AI investments, these two industries are setting a good example by trying to find uses for generative AI that create value for customers and may prove promising to generate a return .