Enterprise
GenAI in Action: Use Cases for Every Industry
Sep 16, 2024
10 min read
THIRTY PERCENT!
That’s the proportion of new drugs and materials that will be discovered using Generative AI by next year, predicts Gartner. McKinsey is more enthusiastic in believing that GenAI has the potential to automate 60-70% of activities that take up an employee’s time today. This estimates that generative AI can add $4.4 trillion to the global economy.
Leaders across the globe are excited about trying Generative AI in their workplace. The buzz is definitely there. Yet, as BCG finds, “90% are either waiting for GenAI to move beyond the hype or experimenting in small ways.”
If you’re one of them, we’ve brought you the nudge you need to move to the next level. In this blog post, we discuss the various real, tangible, ROI-driven GenAI use cases for every industry or application.
Customer experience
Customer experience (CX) is one of the four areas that Gartner finds could derive most value from GenAI. We’re already seeing products integrate GenAI into their CX, like Mercedes adding ChatGPT to their cars, or OnePlus/Samsung adding Google Gemini to their phones.
Beyond the direct chat integration, GenAI can do a lot more for customer experience. Here are some use cases.
1. Self-service customer support
It is no news that Gen Z prefers to solve their problems on their own before calling customer service. For businesses too, this saves immense time and effort — modern tech businesses make it notoriously difficult to call for help or sometimes even charge for it.
GenAI can deliver the CX that today’s customers demand without the inefficiencies it brings. It can have immediate, personalized interactions with any number of customers in a language of their choice. It can resolve simple, repetitive complaints during first contact. Biggies like Best Buy have already begun this transformation.
Best Buy’s GenAI support assistant (Source: Best Buy)
In several situations, it can do the job better and faster than a human agent. For instance, if the customer has an obscure question about a privacy policy or fine print, a human agent might be hard-pressed to find that information. GenAI can do it instantly. And if needed, redirect to the subject matter expert for a deeper discussion.
2. Agent support
In an average customer care environment, data is spread across dozens of tools, such as email, live chat, social media, internal CRM, past interactions, known complaints, product knowledge base, etc. During any conversation, the agent jumps through these windows to get even the most basic information.
GenAI can become the agent’s personal assistant, bringing together information without the frazzle. They can access data by asking questions like, “Have we given this customer a discount before?” or “What should be the settings on a Mac?” or they can quickly resolve problems by giving commands like “extend this customer’s due date by 7 working days” or “arrange a call back with an expert at 2 pm tomorrow.”
In fact, Gartner estimates that GenAI can increase productivity “at a value ranging from 30-45% of current function costs.”
Sales and marketing
In the digital world, any tool that can generate text, images, video, etc. is a boon to the marketer. So, sales and marketing are among the biggest areas to create value with GenAI.
3. Conversion optimization
Salespeople often prioritize their leads based on instinct. For example, a salesperson might choose to spend time on nurturing a prospect based on how interested they seemed in a meeting or how strong their objections were.
Generative AI can make that more scientific by profiling customers based on internal and external data. For instance, it can take publicly available data from social media posts or company profile pages to understand client preferences and customize pitches.
4. Prospect nurturing
Imagine a GenAI chatbot putting together a docket of information and attaching it to an email draft, intricately customized to your interaction with the prospect, ready for the salesperson to hit send!
GenAI tools can understand conversations and context to craft impactful responses on your behalf. It can not only identify what the customer wants (for example, all terms around your product’s compliance) but also find the necessary resources instantly, saving your sales team’s time and dramatically improving accuracy.
What’s more? GenAI can automatically follow up with the prospect at the right time, through the right channel, in the right tone, improving closing rates.
5. Discovery and customer journey
With GenAI, everyone can have a personal shopper—or at least an attentive sales representative—irrespective of the industry or product. Mercedes Benz recently added a GenAI-powered “sales assistant” to their e-commerce platform, with a goal of “making the digital storefront a seamless extension of the physical showroom.”
Mercedes’ customer interaction bots (Source: Mercedes)
Providing product information, creating comparison tables, making contextual recommendations, organizing appointments, collecting (and analyzing) qualitative feedback are just a few ways in which GenAI can transform sales operations. GenAI can do all this in a hyper-personalized manner.
6. Content creation at scale
With GenAI, resource is no longer a constraint for content creation. Here’s how.
Ideation: Don’t know what to write about? Spin up some thoughts into a chat interface and get a number of ideas instantly. Tune them for your needs.
Content creation: Avoid the dread of the blank slate with a content draft from GenAI. Use it as an outline to structure your article.
Multimedia generation: Save time and money in creating artistic images or animated videos with GenAI. Learn to prompt right and get visual, audio and video content at the same speed as text.
Content repurposing: Convert a blog post into a social media update, a webinar into an ebook, an interview into a press release and so on — all this while staying on brand!
Translations: Reach out to a multitude of audiences across geographies by translating your messages into their vernacular. Customize your message and visuals for the audience you’re targeting.
With GenAI, you can also enable real-time translated captioning in video meetings for distributed teams.
SEO: Automate the creation of SEO aspects like meta titles, descriptions, image tags, etc.
If you’re willing to be imaginative, you can also create a GenAI influencer, like the Brazilian retailer Magalu did with Lu, who has millions of followers on Instagram and TikTok.
Lu, the non-human influencer (Source: The Observer)
Software engineering
Generative AI can create not just text and images but fully functional code as well. Here are ways in which you can accelerate your software development with GenAI.
7. Code drafts
At the most basic level, your engineers can ask the GenAI tool for code drafts. They can think and solve problems in natural language. For instance, one can say, “write Python code to create a scheduling app for a business coaching service. Restrict coach availability to sessions a day” and get a draft to work on top of. This immediately improves speed by eliminating productivity blockers.
8. Coding assistance
GenAI can be your team’s pair programmer. It can help developers with coding suggestions that help improve programming speed and quality. When you integrate a secure GenAI tool into your private codebase, it can exponentially increase performance by making the suggestions highly contextual and offering them in real-time!
35-45% improvement in code generation efficiency with GenAI (Source: McKinsey)
For instance, with the help of Google’s Code Assist, Turing saw a 33% increase in productivity in PR merges per developer. This creates a compounding increase in time to production, efficiency, quality and innovation.
9. Developer experience
Software developers using GitHub CoPilot completed tasks 55% faster than those not using any tool, found a study. GenAI certainly improves productivity, but are developers happy about it? Apparently they are, based on a large-scale survey of users of GitHub CoPilot.
60% users feel more fulfilled with their job
74% believe they can focus on more satisfying work
73% say GenAI helped them stay in the flow
77% spend less time ‘searching’
87% admitted that it helps them conserve mental energy while performing repetitive tasks
Healthcare and pharma
The healthcare industry is under extreme pressure across the globe, unable to serve the needs of everyone. Especially after the pandemic, the need for stronger public health systems is also more pressing. Perhaps, GenAI can help a little.
10. Analysis and reporting
GenAI is growing popular among radiologists in data analysis and reporting, given that nearly 90% of healthcare data is imaging. A good radiology support bot can help doctors with initial findings, ensure they don’t miss out on key details, dramatically reducing medical errors. Once done, GenAI can create reports that meet regulatory standards and healthcare requirements, freeing up the doctor’s time from documentation.
However, several pilots in using all forms of clinical documentation have shown initial success.
11. Caregiver experience
A gargantuan amount of information is passed on from one caregiver shift to the next in every hospital. Even the smaller item falling through the cracks might become a matter of life and death for the patient.
HCA Healthcare is solving this problem with a virtual AI assistant, which reads the charts and creates hand-offs for the nurses from one shift to another. They’re making this experience mobile, through smartphones and tablets, to ensure that the information is available on the go and in context.
Automating such repetitive, yet critical processes can save a lot of time and energy for clinicians, paving way for better healthcare delivery overall.
12. Drug discovery
The pharmaceutical industry is especially excited by the research and development possibilities opened up by Generative AI. “Once GenAI is optimized, it's going to reduce timelines by 50%,” says a former Clinical Development Director, Medical & Scientific Affairs at Biotech.
Across the drug development process, GenAI can help with:
Preclinical testing: Predicting the properties and toxicity of drug compounds based on available data
Decision-making: Supporting several decisions throughout the process, such as identifying relevant patients, dosage, monitoring, etc.
Risk mitigation: Predicting trial outcomes across various potential scenarios to identify risks and design mitigative measures
Resource allocation: Intelligently allocating the right resources—human or otherwise—to optimize study outcomes
Automation: Accelerating documentation, compliance checks, administrative tasks and regulatory submissions
Retail
While speaking of customer experience, we explore retail scenarios a little. Let’s get a little big deeper here.
13. Product descriptions
If you’ve ever shopped on any e-commerce platform, you know that product descriptions leave a lot wanting. Depending on what you sell, describing the benefits, ingredients, specifications, configurations, dimensions, usage instructions, etc. for every product can be a Himalayan endeavor in itself.
Retailers are leveraging GenAI to handle this with little training from across various sources. A good GenAI tool can scan/capture data from the physical product’s packaging, pull together information from internal systems, understand regulatory requirements and create descriptions automatically.
14. Personalized shopping
Everyone is acquainted with GenAI in its capacity to generate text. What if it can create what you have in mind—visually? That’s what fashion subscription service Stitch Fix did with DALL-E. It accepts a user’s text-based input of their needs and helps stylists visualize an article of clothing accordingly. The Outfit Creation Model (OCM) generates 13 million new outfit combinations every day!
Amazon’s AI shopping assistant Rufus! (Source: Amazon)
15. Innovation
Generative AI tools can serve as the digital playground for real-world ideas. It can help marketing teams quickly create campaigns and test them directly with customers. It can create innumerable design options and help teams iterate until they’re happy.
Nutella created individual label designs for 7 million jars. Yep, 7 million different labels generated by AI. Going with the theme of celebrating individuality, Nutella Unica sold out the entire lot in one month.
Nutella Unica jar designs (Source: Ogilvy Italia)
16. Market research
Retailers and CPG players regularly conduct market research for product development, marketing, sales, distribution and more. GenAI can significantly optimize this across processes.
Analysis: GenAI can read, process and summarize large volumes of data quickly. You can put all those expensive market reports to good use by synthesizing information across sources to power your decisions.
Simulation: GenAI can help imagine and test potential across various scenarios without the costs of actually going to market with it. Is this brand campaign bold or likely to create a backlash? GenAI can tell (somewhat!)
Synthetic data: It can help address data gaps by creating realistic synthetic data large enough to reality in order to run simulations and predictions. Startup without customer information, no sweat.
Segmentation: It can analyze customer data to identify market segments hitherto unnoticed. GenAI can help identify and understand niches to serve their needs best.
Forecasting: GenAI can increase the accuracy of demand forecasts, helping the entire supply chain optimize performance.
Banking and finance
Wouldn’t it be great if AI could generate money? Alas. But we’ve got the next best thing. Generative AI enables dozens of valuable use cases for the banking, finance and insurance industry. Let’s explore the top few.
17. Navigating legalese
Financial legalese is a special kind of maze that needs miraculous superpowers to navigate. GenAI now offers that superpower. A good Generative AI companion can help agents synthesize complex financial information with ease. It can allow them to search for exactly what they need dynamically.
If you’re thinking your teams can already search, GenAI can do a lot more. It can help agents search contextually. Instead of refining search teams every single time, they can have a conversation with the chatbot within the context of the relationship with the prospect/customer they’re serving. What’s more, like Morgan Stanley’s Debrief, it can also generate notes and action items on behalf of the financial advisor.
Screenshot from Mongan Stanley’s AI program (Source: Morgan Stanley)
18. Real-time risk management
Cybersecurity risks are some of the costliest in the banking industry. Banks and financial institutions spend millions of dollars mitigating risks. GenAI can improve outcomes.
Monitoring: GenAI can help monitor and verify banking activity to identify risks
Evaluation: It can enable banks to assess risks based on a wide range of data from the customer, industry, government agencies and other authorities
Credit assessment: It can help synthesize private and publicly available data about the customer to build a strong risk profile
Predictions: GenAI can improve the accuracy of predicting patterns of fraudulent transactions based on real-world or synthetic data
Claims processing: GenAI can help visualize damage based on customer conversations and photographic evidence to process claims faster
19. Wealth management
Traditionally wealth and portfolio management has been the responsibility of a financial advisor. So, investment firms set the bar high for who can become a client. GenAI can lower that.
By automating the entire process of onboarding, asset evaluation, strategy recommendations, and servicing, GenAI can help middle income investors move up the ladder.
Miscellany
20. Astronomy
If you’re convinced that GenAI is an earthly endeavor, think again. The Asteroid Institute is using LLMs on existing astronomical data to discover hidden asteroids. So far, they’ve identified “27,500 new, high-confidence, asteroid discovery candidates.”
With the above 20 use cases, we’re barely scratching the surface. Across content creation, data synthesis, conversation, automation, indexation, and more, Generative AI is your oyster.
However, just a good Generative AI strategy goes beyond signing your entire team up for ChatGPT. While embracing GenAI in your organization, you need to consider a lot more.
Considerations while designing GenAI Strategy
Key aspects to think about if you’re looking to operationalize Generative AI in your organization.
Model suitability: Is the LLM right for your use case? For instance, Google’s Med-PaLM might be right if you’re in healthcare.
Customization: Is your model intelligent for your organization? No model, however industry specific, will have the intelligence of someone who has been in your organization, understand your customers and your markets. Model fine-tuning is necessary for that.
Data privacy and security: Is your data secure? All your proprietary data needs to be protected against security threats. More so if you’re using customer data or personally identifiable information.
LLM stack: How flexible do you need your GenAI apps? Open source models will give you the flexibility to customize/adapt, while closed source tools like ChatGPT will be easier to deploy.
Infra: Cloud? On-prem? Hybrid? The choice of where and how your deploy your LLMs can have significant bearing on its performance and costs.
Prompt engineering: Do your employees know how to use the GenAI tool? Create a library of specific, high-quality outputs for your teams to use. Offer training and workshops to improve prompting outcomes.
The good news is that you don’t need to invest the time, money and resources into building GenAI capabilities in-house. Speak to our experts and see how you can springboard your GenAI use cases today.
THIRTY PERCENT!
That’s the proportion of new drugs and materials that will be discovered using Generative AI by next year, predicts Gartner. McKinsey is more enthusiastic in believing that GenAI has the potential to automate 60-70% of activities that take up an employee’s time today. This estimates that generative AI can add $4.4 trillion to the global economy.
Leaders across the globe are excited about trying Generative AI in their workplace. The buzz is definitely there. Yet, as BCG finds, “90% are either waiting for GenAI to move beyond the hype or experimenting in small ways.”
If you’re one of them, we’ve brought you the nudge you need to move to the next level. In this blog post, we discuss the various real, tangible, ROI-driven GenAI use cases for every industry or application.
Customer experience
Customer experience (CX) is one of the four areas that Gartner finds could derive most value from GenAI. We’re already seeing products integrate GenAI into their CX, like Mercedes adding ChatGPT to their cars, or OnePlus/Samsung adding Google Gemini to their phones.
Beyond the direct chat integration, GenAI can do a lot more for customer experience. Here are some use cases.
1. Self-service customer support
It is no news that Gen Z prefers to solve their problems on their own before calling customer service. For businesses too, this saves immense time and effort — modern tech businesses make it notoriously difficult to call for help or sometimes even charge for it.
GenAI can deliver the CX that today’s customers demand without the inefficiencies it brings. It can have immediate, personalized interactions with any number of customers in a language of their choice. It can resolve simple, repetitive complaints during first contact. Biggies like Best Buy have already begun this transformation.
Best Buy’s GenAI support assistant (Source: Best Buy)
In several situations, it can do the job better and faster than a human agent. For instance, if the customer has an obscure question about a privacy policy or fine print, a human agent might be hard-pressed to find that information. GenAI can do it instantly. And if needed, redirect to the subject matter expert for a deeper discussion.
2. Agent support
In an average customer care environment, data is spread across dozens of tools, such as email, live chat, social media, internal CRM, past interactions, known complaints, product knowledge base, etc. During any conversation, the agent jumps through these windows to get even the most basic information.
GenAI can become the agent’s personal assistant, bringing together information without the frazzle. They can access data by asking questions like, “Have we given this customer a discount before?” or “What should be the settings on a Mac?” or they can quickly resolve problems by giving commands like “extend this customer’s due date by 7 working days” or “arrange a call back with an expert at 2 pm tomorrow.”
In fact, Gartner estimates that GenAI can increase productivity “at a value ranging from 30-45% of current function costs.”
Sales and marketing
In the digital world, any tool that can generate text, images, video, etc. is a boon to the marketer. So, sales and marketing are among the biggest areas to create value with GenAI.
3. Conversion optimization
Salespeople often prioritize their leads based on instinct. For example, a salesperson might choose to spend time on nurturing a prospect based on how interested they seemed in a meeting or how strong their objections were.
Generative AI can make that more scientific by profiling customers based on internal and external data. For instance, it can take publicly available data from social media posts or company profile pages to understand client preferences and customize pitches.
4. Prospect nurturing
Imagine a GenAI chatbot putting together a docket of information and attaching it to an email draft, intricately customized to your interaction with the prospect, ready for the salesperson to hit send!
GenAI tools can understand conversations and context to craft impactful responses on your behalf. It can not only identify what the customer wants (for example, all terms around your product’s compliance) but also find the necessary resources instantly, saving your sales team’s time and dramatically improving accuracy.
What’s more? GenAI can automatically follow up with the prospect at the right time, through the right channel, in the right tone, improving closing rates.
5. Discovery and customer journey
With GenAI, everyone can have a personal shopper—or at least an attentive sales representative—irrespective of the industry or product. Mercedes Benz recently added a GenAI-powered “sales assistant” to their e-commerce platform, with a goal of “making the digital storefront a seamless extension of the physical showroom.”
Mercedes’ customer interaction bots (Source: Mercedes)
Providing product information, creating comparison tables, making contextual recommendations, organizing appointments, collecting (and analyzing) qualitative feedback are just a few ways in which GenAI can transform sales operations. GenAI can do all this in a hyper-personalized manner.
6. Content creation at scale
With GenAI, resource is no longer a constraint for content creation. Here’s how.
Ideation: Don’t know what to write about? Spin up some thoughts into a chat interface and get a number of ideas instantly. Tune them for your needs.
Content creation: Avoid the dread of the blank slate with a content draft from GenAI. Use it as an outline to structure your article.
Multimedia generation: Save time and money in creating artistic images or animated videos with GenAI. Learn to prompt right and get visual, audio and video content at the same speed as text.
Content repurposing: Convert a blog post into a social media update, a webinar into an ebook, an interview into a press release and so on — all this while staying on brand!
Translations: Reach out to a multitude of audiences across geographies by translating your messages into their vernacular. Customize your message and visuals for the audience you’re targeting.
With GenAI, you can also enable real-time translated captioning in video meetings for distributed teams.
SEO: Automate the creation of SEO aspects like meta titles, descriptions, image tags, etc.
If you’re willing to be imaginative, you can also create a GenAI influencer, like the Brazilian retailer Magalu did with Lu, who has millions of followers on Instagram and TikTok.
Lu, the non-human influencer (Source: The Observer)
Software engineering
Generative AI can create not just text and images but fully functional code as well. Here are ways in which you can accelerate your software development with GenAI.
7. Code drafts
At the most basic level, your engineers can ask the GenAI tool for code drafts. They can think and solve problems in natural language. For instance, one can say, “write Python code to create a scheduling app for a business coaching service. Restrict coach availability to sessions a day” and get a draft to work on top of. This immediately improves speed by eliminating productivity blockers.
8. Coding assistance
GenAI can be your team’s pair programmer. It can help developers with coding suggestions that help improve programming speed and quality. When you integrate a secure GenAI tool into your private codebase, it can exponentially increase performance by making the suggestions highly contextual and offering them in real-time!
35-45% improvement in code generation efficiency with GenAI (Source: McKinsey)
For instance, with the help of Google’s Code Assist, Turing saw a 33% increase in productivity in PR merges per developer. This creates a compounding increase in time to production, efficiency, quality and innovation.
9. Developer experience
Software developers using GitHub CoPilot completed tasks 55% faster than those not using any tool, found a study. GenAI certainly improves productivity, but are developers happy about it? Apparently they are, based on a large-scale survey of users of GitHub CoPilot.
60% users feel more fulfilled with their job
74% believe they can focus on more satisfying work
73% say GenAI helped them stay in the flow
77% spend less time ‘searching’
87% admitted that it helps them conserve mental energy while performing repetitive tasks
Healthcare and pharma
The healthcare industry is under extreme pressure across the globe, unable to serve the needs of everyone. Especially after the pandemic, the need for stronger public health systems is also more pressing. Perhaps, GenAI can help a little.
10. Analysis and reporting
GenAI is growing popular among radiologists in data analysis and reporting, given that nearly 90% of healthcare data is imaging. A good radiology support bot can help doctors with initial findings, ensure they don’t miss out on key details, dramatically reducing medical errors. Once done, GenAI can create reports that meet regulatory standards and healthcare requirements, freeing up the doctor’s time from documentation.
However, several pilots in using all forms of clinical documentation have shown initial success.
11. Caregiver experience
A gargantuan amount of information is passed on from one caregiver shift to the next in every hospital. Even the smaller item falling through the cracks might become a matter of life and death for the patient.
HCA Healthcare is solving this problem with a virtual AI assistant, which reads the charts and creates hand-offs for the nurses from one shift to another. They’re making this experience mobile, through smartphones and tablets, to ensure that the information is available on the go and in context.
Automating such repetitive, yet critical processes can save a lot of time and energy for clinicians, paving way for better healthcare delivery overall.
12. Drug discovery
The pharmaceutical industry is especially excited by the research and development possibilities opened up by Generative AI. “Once GenAI is optimized, it's going to reduce timelines by 50%,” says a former Clinical Development Director, Medical & Scientific Affairs at Biotech.
Across the drug development process, GenAI can help with:
Preclinical testing: Predicting the properties and toxicity of drug compounds based on available data
Decision-making: Supporting several decisions throughout the process, such as identifying relevant patients, dosage, monitoring, etc.
Risk mitigation: Predicting trial outcomes across various potential scenarios to identify risks and design mitigative measures
Resource allocation: Intelligently allocating the right resources—human or otherwise—to optimize study outcomes
Automation: Accelerating documentation, compliance checks, administrative tasks and regulatory submissions
Retail
While speaking of customer experience, we explore retail scenarios a little. Let’s get a little big deeper here.
13. Product descriptions
If you’ve ever shopped on any e-commerce platform, you know that product descriptions leave a lot wanting. Depending on what you sell, describing the benefits, ingredients, specifications, configurations, dimensions, usage instructions, etc. for every product can be a Himalayan endeavor in itself.
Retailers are leveraging GenAI to handle this with little training from across various sources. A good GenAI tool can scan/capture data from the physical product’s packaging, pull together information from internal systems, understand regulatory requirements and create descriptions automatically.
14. Personalized shopping
Everyone is acquainted with GenAI in its capacity to generate text. What if it can create what you have in mind—visually? That’s what fashion subscription service Stitch Fix did with DALL-E. It accepts a user’s text-based input of their needs and helps stylists visualize an article of clothing accordingly. The Outfit Creation Model (OCM) generates 13 million new outfit combinations every day!
Amazon’s AI shopping assistant Rufus! (Source: Amazon)
15. Innovation
Generative AI tools can serve as the digital playground for real-world ideas. It can help marketing teams quickly create campaigns and test them directly with customers. It can create innumerable design options and help teams iterate until they’re happy.
Nutella created individual label designs for 7 million jars. Yep, 7 million different labels generated by AI. Going with the theme of celebrating individuality, Nutella Unica sold out the entire lot in one month.
Nutella Unica jar designs (Source: Ogilvy Italia)
16. Market research
Retailers and CPG players regularly conduct market research for product development, marketing, sales, distribution and more. GenAI can significantly optimize this across processes.
Analysis: GenAI can read, process and summarize large volumes of data quickly. You can put all those expensive market reports to good use by synthesizing information across sources to power your decisions.
Simulation: GenAI can help imagine and test potential across various scenarios without the costs of actually going to market with it. Is this brand campaign bold or likely to create a backlash? GenAI can tell (somewhat!)
Synthetic data: It can help address data gaps by creating realistic synthetic data large enough to reality in order to run simulations and predictions. Startup without customer information, no sweat.
Segmentation: It can analyze customer data to identify market segments hitherto unnoticed. GenAI can help identify and understand niches to serve their needs best.
Forecasting: GenAI can increase the accuracy of demand forecasts, helping the entire supply chain optimize performance.
Banking and finance
Wouldn’t it be great if AI could generate money? Alas. But we’ve got the next best thing. Generative AI enables dozens of valuable use cases for the banking, finance and insurance industry. Let’s explore the top few.
17. Navigating legalese
Financial legalese is a special kind of maze that needs miraculous superpowers to navigate. GenAI now offers that superpower. A good Generative AI companion can help agents synthesize complex financial information with ease. It can allow them to search for exactly what they need dynamically.
If you’re thinking your teams can already search, GenAI can do a lot more. It can help agents search contextually. Instead of refining search teams every single time, they can have a conversation with the chatbot within the context of the relationship with the prospect/customer they’re serving. What’s more, like Morgan Stanley’s Debrief, it can also generate notes and action items on behalf of the financial advisor.
Screenshot from Mongan Stanley’s AI program (Source: Morgan Stanley)
18. Real-time risk management
Cybersecurity risks are some of the costliest in the banking industry. Banks and financial institutions spend millions of dollars mitigating risks. GenAI can improve outcomes.
Monitoring: GenAI can help monitor and verify banking activity to identify risks
Evaluation: It can enable banks to assess risks based on a wide range of data from the customer, industry, government agencies and other authorities
Credit assessment: It can help synthesize private and publicly available data about the customer to build a strong risk profile
Predictions: GenAI can improve the accuracy of predicting patterns of fraudulent transactions based on real-world or synthetic data
Claims processing: GenAI can help visualize damage based on customer conversations and photographic evidence to process claims faster
19. Wealth management
Traditionally wealth and portfolio management has been the responsibility of a financial advisor. So, investment firms set the bar high for who can become a client. GenAI can lower that.
By automating the entire process of onboarding, asset evaluation, strategy recommendations, and servicing, GenAI can help middle income investors move up the ladder.
Miscellany
20. Astronomy
If you’re convinced that GenAI is an earthly endeavor, think again. The Asteroid Institute is using LLMs on existing astronomical data to discover hidden asteroids. So far, they’ve identified “27,500 new, high-confidence, asteroid discovery candidates.”
With the above 20 use cases, we’re barely scratching the surface. Across content creation, data synthesis, conversation, automation, indexation, and more, Generative AI is your oyster.
However, just a good Generative AI strategy goes beyond signing your entire team up for ChatGPT. While embracing GenAI in your organization, you need to consider a lot more.
Considerations while designing GenAI Strategy
Key aspects to think about if you’re looking to operationalize Generative AI in your organization.
Model suitability: Is the LLM right for your use case? For instance, Google’s Med-PaLM might be right if you’re in healthcare.
Customization: Is your model intelligent for your organization? No model, however industry specific, will have the intelligence of someone who has been in your organization, understand your customers and your markets. Model fine-tuning is necessary for that.
Data privacy and security: Is your data secure? All your proprietary data needs to be protected against security threats. More so if you’re using customer data or personally identifiable information.
LLM stack: How flexible do you need your GenAI apps? Open source models will give you the flexibility to customize/adapt, while closed source tools like ChatGPT will be easier to deploy.
Infra: Cloud? On-prem? Hybrid? The choice of where and how your deploy your LLMs can have significant bearing on its performance and costs.
Prompt engineering: Do your employees know how to use the GenAI tool? Create a library of specific, high-quality outputs for your teams to use. Offer training and workshops to improve prompting outcomes.
The good news is that you don’t need to invest the time, money and resources into building GenAI capabilities in-house. Speak to our experts and see how you can springboard your GenAI use cases today.
THIRTY PERCENT!
That’s the proportion of new drugs and materials that will be discovered using Generative AI by next year, predicts Gartner. McKinsey is more enthusiastic in believing that GenAI has the potential to automate 60-70% of activities that take up an employee’s time today. This estimates that generative AI can add $4.4 trillion to the global economy.
Leaders across the globe are excited about trying Generative AI in their workplace. The buzz is definitely there. Yet, as BCG finds, “90% are either waiting for GenAI to move beyond the hype or experimenting in small ways.”
If you’re one of them, we’ve brought you the nudge you need to move to the next level. In this blog post, we discuss the various real, tangible, ROI-driven GenAI use cases for every industry or application.
Customer experience
Customer experience (CX) is one of the four areas that Gartner finds could derive most value from GenAI. We’re already seeing products integrate GenAI into their CX, like Mercedes adding ChatGPT to their cars, or OnePlus/Samsung adding Google Gemini to their phones.
Beyond the direct chat integration, GenAI can do a lot more for customer experience. Here are some use cases.
1. Self-service customer support
It is no news that Gen Z prefers to solve their problems on their own before calling customer service. For businesses too, this saves immense time and effort — modern tech businesses make it notoriously difficult to call for help or sometimes even charge for it.
GenAI can deliver the CX that today’s customers demand without the inefficiencies it brings. It can have immediate, personalized interactions with any number of customers in a language of their choice. It can resolve simple, repetitive complaints during first contact. Biggies like Best Buy have already begun this transformation.
Best Buy’s GenAI support assistant (Source: Best Buy)
In several situations, it can do the job better and faster than a human agent. For instance, if the customer has an obscure question about a privacy policy or fine print, a human agent might be hard-pressed to find that information. GenAI can do it instantly. And if needed, redirect to the subject matter expert for a deeper discussion.
2. Agent support
In an average customer care environment, data is spread across dozens of tools, such as email, live chat, social media, internal CRM, past interactions, known complaints, product knowledge base, etc. During any conversation, the agent jumps through these windows to get even the most basic information.
GenAI can become the agent’s personal assistant, bringing together information without the frazzle. They can access data by asking questions like, “Have we given this customer a discount before?” or “What should be the settings on a Mac?” or they can quickly resolve problems by giving commands like “extend this customer’s due date by 7 working days” or “arrange a call back with an expert at 2 pm tomorrow.”
In fact, Gartner estimates that GenAI can increase productivity “at a value ranging from 30-45% of current function costs.”
Sales and marketing
In the digital world, any tool that can generate text, images, video, etc. is a boon to the marketer. So, sales and marketing are among the biggest areas to create value with GenAI.
3. Conversion optimization
Salespeople often prioritize their leads based on instinct. For example, a salesperson might choose to spend time on nurturing a prospect based on how interested they seemed in a meeting or how strong their objections were.
Generative AI can make that more scientific by profiling customers based on internal and external data. For instance, it can take publicly available data from social media posts or company profile pages to understand client preferences and customize pitches.
4. Prospect nurturing
Imagine a GenAI chatbot putting together a docket of information and attaching it to an email draft, intricately customized to your interaction with the prospect, ready for the salesperson to hit send!
GenAI tools can understand conversations and context to craft impactful responses on your behalf. It can not only identify what the customer wants (for example, all terms around your product’s compliance) but also find the necessary resources instantly, saving your sales team’s time and dramatically improving accuracy.
What’s more? GenAI can automatically follow up with the prospect at the right time, through the right channel, in the right tone, improving closing rates.
5. Discovery and customer journey
With GenAI, everyone can have a personal shopper—or at least an attentive sales representative—irrespective of the industry or product. Mercedes Benz recently added a GenAI-powered “sales assistant” to their e-commerce platform, with a goal of “making the digital storefront a seamless extension of the physical showroom.”
Mercedes’ customer interaction bots (Source: Mercedes)
Providing product information, creating comparison tables, making contextual recommendations, organizing appointments, collecting (and analyzing) qualitative feedback are just a few ways in which GenAI can transform sales operations. GenAI can do all this in a hyper-personalized manner.
6. Content creation at scale
With GenAI, resource is no longer a constraint for content creation. Here’s how.
Ideation: Don’t know what to write about? Spin up some thoughts into a chat interface and get a number of ideas instantly. Tune them for your needs.
Content creation: Avoid the dread of the blank slate with a content draft from GenAI. Use it as an outline to structure your article.
Multimedia generation: Save time and money in creating artistic images or animated videos with GenAI. Learn to prompt right and get visual, audio and video content at the same speed as text.
Content repurposing: Convert a blog post into a social media update, a webinar into an ebook, an interview into a press release and so on — all this while staying on brand!
Translations: Reach out to a multitude of audiences across geographies by translating your messages into their vernacular. Customize your message and visuals for the audience you’re targeting.
With GenAI, you can also enable real-time translated captioning in video meetings for distributed teams.
SEO: Automate the creation of SEO aspects like meta titles, descriptions, image tags, etc.
If you’re willing to be imaginative, you can also create a GenAI influencer, like the Brazilian retailer Magalu did with Lu, who has millions of followers on Instagram and TikTok.
Lu, the non-human influencer (Source: The Observer)
Software engineering
Generative AI can create not just text and images but fully functional code as well. Here are ways in which you can accelerate your software development with GenAI.
7. Code drafts
At the most basic level, your engineers can ask the GenAI tool for code drafts. They can think and solve problems in natural language. For instance, one can say, “write Python code to create a scheduling app for a business coaching service. Restrict coach availability to sessions a day” and get a draft to work on top of. This immediately improves speed by eliminating productivity blockers.
8. Coding assistance
GenAI can be your team’s pair programmer. It can help developers with coding suggestions that help improve programming speed and quality. When you integrate a secure GenAI tool into your private codebase, it can exponentially increase performance by making the suggestions highly contextual and offering them in real-time!
35-45% improvement in code generation efficiency with GenAI (Source: McKinsey)
For instance, with the help of Google’s Code Assist, Turing saw a 33% increase in productivity in PR merges per developer. This creates a compounding increase in time to production, efficiency, quality and innovation.
9. Developer experience
Software developers using GitHub CoPilot completed tasks 55% faster than those not using any tool, found a study. GenAI certainly improves productivity, but are developers happy about it? Apparently they are, based on a large-scale survey of users of GitHub CoPilot.
60% users feel more fulfilled with their job
74% believe they can focus on more satisfying work
73% say GenAI helped them stay in the flow
77% spend less time ‘searching’
87% admitted that it helps them conserve mental energy while performing repetitive tasks
Healthcare and pharma
The healthcare industry is under extreme pressure across the globe, unable to serve the needs of everyone. Especially after the pandemic, the need for stronger public health systems is also more pressing. Perhaps, GenAI can help a little.
10. Analysis and reporting
GenAI is growing popular among radiologists in data analysis and reporting, given that nearly 90% of healthcare data is imaging. A good radiology support bot can help doctors with initial findings, ensure they don’t miss out on key details, dramatically reducing medical errors. Once done, GenAI can create reports that meet regulatory standards and healthcare requirements, freeing up the doctor’s time from documentation.
However, several pilots in using all forms of clinical documentation have shown initial success.
11. Caregiver experience
A gargantuan amount of information is passed on from one caregiver shift to the next in every hospital. Even the smaller item falling through the cracks might become a matter of life and death for the patient.
HCA Healthcare is solving this problem with a virtual AI assistant, which reads the charts and creates hand-offs for the nurses from one shift to another. They’re making this experience mobile, through smartphones and tablets, to ensure that the information is available on the go and in context.
Automating such repetitive, yet critical processes can save a lot of time and energy for clinicians, paving way for better healthcare delivery overall.
12. Drug discovery
The pharmaceutical industry is especially excited by the research and development possibilities opened up by Generative AI. “Once GenAI is optimized, it's going to reduce timelines by 50%,” says a former Clinical Development Director, Medical & Scientific Affairs at Biotech.
Across the drug development process, GenAI can help with:
Preclinical testing: Predicting the properties and toxicity of drug compounds based on available data
Decision-making: Supporting several decisions throughout the process, such as identifying relevant patients, dosage, monitoring, etc.
Risk mitigation: Predicting trial outcomes across various potential scenarios to identify risks and design mitigative measures
Resource allocation: Intelligently allocating the right resources—human or otherwise—to optimize study outcomes
Automation: Accelerating documentation, compliance checks, administrative tasks and regulatory submissions
Retail
While speaking of customer experience, we explore retail scenarios a little. Let’s get a little big deeper here.
13. Product descriptions
If you’ve ever shopped on any e-commerce platform, you know that product descriptions leave a lot wanting. Depending on what you sell, describing the benefits, ingredients, specifications, configurations, dimensions, usage instructions, etc. for every product can be a Himalayan endeavor in itself.
Retailers are leveraging GenAI to handle this with little training from across various sources. A good GenAI tool can scan/capture data from the physical product’s packaging, pull together information from internal systems, understand regulatory requirements and create descriptions automatically.
14. Personalized shopping
Everyone is acquainted with GenAI in its capacity to generate text. What if it can create what you have in mind—visually? That’s what fashion subscription service Stitch Fix did with DALL-E. It accepts a user’s text-based input of their needs and helps stylists visualize an article of clothing accordingly. The Outfit Creation Model (OCM) generates 13 million new outfit combinations every day!
Amazon’s AI shopping assistant Rufus! (Source: Amazon)
15. Innovation
Generative AI tools can serve as the digital playground for real-world ideas. It can help marketing teams quickly create campaigns and test them directly with customers. It can create innumerable design options and help teams iterate until they’re happy.
Nutella created individual label designs for 7 million jars. Yep, 7 million different labels generated by AI. Going with the theme of celebrating individuality, Nutella Unica sold out the entire lot in one month.
Nutella Unica jar designs (Source: Ogilvy Italia)
16. Market research
Retailers and CPG players regularly conduct market research for product development, marketing, sales, distribution and more. GenAI can significantly optimize this across processes.
Analysis: GenAI can read, process and summarize large volumes of data quickly. You can put all those expensive market reports to good use by synthesizing information across sources to power your decisions.
Simulation: GenAI can help imagine and test potential across various scenarios without the costs of actually going to market with it. Is this brand campaign bold or likely to create a backlash? GenAI can tell (somewhat!)
Synthetic data: It can help address data gaps by creating realistic synthetic data large enough to reality in order to run simulations and predictions. Startup without customer information, no sweat.
Segmentation: It can analyze customer data to identify market segments hitherto unnoticed. GenAI can help identify and understand niches to serve their needs best.
Forecasting: GenAI can increase the accuracy of demand forecasts, helping the entire supply chain optimize performance.
Banking and finance
Wouldn’t it be great if AI could generate money? Alas. But we’ve got the next best thing. Generative AI enables dozens of valuable use cases for the banking, finance and insurance industry. Let’s explore the top few.
17. Navigating legalese
Financial legalese is a special kind of maze that needs miraculous superpowers to navigate. GenAI now offers that superpower. A good Generative AI companion can help agents synthesize complex financial information with ease. It can allow them to search for exactly what they need dynamically.
If you’re thinking your teams can already search, GenAI can do a lot more. It can help agents search contextually. Instead of refining search teams every single time, they can have a conversation with the chatbot within the context of the relationship with the prospect/customer they’re serving. What’s more, like Morgan Stanley’s Debrief, it can also generate notes and action items on behalf of the financial advisor.
Screenshot from Mongan Stanley’s AI program (Source: Morgan Stanley)
18. Real-time risk management
Cybersecurity risks are some of the costliest in the banking industry. Banks and financial institutions spend millions of dollars mitigating risks. GenAI can improve outcomes.
Monitoring: GenAI can help monitor and verify banking activity to identify risks
Evaluation: It can enable banks to assess risks based on a wide range of data from the customer, industry, government agencies and other authorities
Credit assessment: It can help synthesize private and publicly available data about the customer to build a strong risk profile
Predictions: GenAI can improve the accuracy of predicting patterns of fraudulent transactions based on real-world or synthetic data
Claims processing: GenAI can help visualize damage based on customer conversations and photographic evidence to process claims faster
19. Wealth management
Traditionally wealth and portfolio management has been the responsibility of a financial advisor. So, investment firms set the bar high for who can become a client. GenAI can lower that.
By automating the entire process of onboarding, asset evaluation, strategy recommendations, and servicing, GenAI can help middle income investors move up the ladder.
Miscellany
20. Astronomy
If you’re convinced that GenAI is an earthly endeavor, think again. The Asteroid Institute is using LLMs on existing astronomical data to discover hidden asteroids. So far, they’ve identified “27,500 new, high-confidence, asteroid discovery candidates.”
With the above 20 use cases, we’re barely scratching the surface. Across content creation, data synthesis, conversation, automation, indexation, and more, Generative AI is your oyster.
However, just a good Generative AI strategy goes beyond signing your entire team up for ChatGPT. While embracing GenAI in your organization, you need to consider a lot more.
Considerations while designing GenAI Strategy
Key aspects to think about if you’re looking to operationalize Generative AI in your organization.
Model suitability: Is the LLM right for your use case? For instance, Google’s Med-PaLM might be right if you’re in healthcare.
Customization: Is your model intelligent for your organization? No model, however industry specific, will have the intelligence of someone who has been in your organization, understand your customers and your markets. Model fine-tuning is necessary for that.
Data privacy and security: Is your data secure? All your proprietary data needs to be protected against security threats. More so if you’re using customer data or personally identifiable information.
LLM stack: How flexible do you need your GenAI apps? Open source models will give you the flexibility to customize/adapt, while closed source tools like ChatGPT will be easier to deploy.
Infra: Cloud? On-prem? Hybrid? The choice of where and how your deploy your LLMs can have significant bearing on its performance and costs.
Prompt engineering: Do your employees know how to use the GenAI tool? Create a library of specific, high-quality outputs for your teams to use. Offer training and workshops to improve prompting outcomes.
The good news is that you don’t need to invest the time, money and resources into building GenAI capabilities in-house. Speak to our experts and see how you can springboard your GenAI use cases today.
Written by
Anshuman Pandey
Co-founder and CEO
Enterprise GenAI Stack.
LLMs on your cloud & data.
© 2024 NimbleBox, Inc.
Enterprise GenAI Stack.
LLMs on your cloud & data.
© 2024 NimbleBox, Inc.
Enterprise GenAI Stack.
LLMs on your cloud & data.
© 2024 NimbleBox, Inc.