Businesses are revolutionized through technology, as Generative AI helps automate processes, promote innovation, and boost operational efficiency.
The use of generative AI across multiple sectors (Content Creation, Healthcare, Customer Service) has generated an immense return on investment (ROI) for all users. We will look at examples of how businesses applied the technology and benefited from it in a real-world application.
What is Generative AI?
Generative AI creates new and innovative content (e.g., text or images) by using an algorithm and training it on a dataset.
A lot of businesses now use gen AI development services to create, train, and add these models to their apps. Generative AI could be implemented with different model architectures, such as GANs or transformers, to generate text, images, videos, etc., that look similar to human-produced output results.
Generative AI ROI
There are several types of ROI from using Generative AI:
- Cost Savings: There may be cost savings related to developing products (fewer manual processes).
- Revenue Generation: Creating new products or services can lead to revenue growth.
- Time Savings: There will be quicker time to complete a process.
- Better Decision Making: Using insights gained from AI can optimize strategic planning processes.
- New Innovative Solutions: AI helps to develop new and creative solutions that may not have existed prior to application of AI.
Real-World Use Cases of Generative AI
Here are some examples from the real world of how businesses are getting a return on investment from generative AI.
1. Content Generation in Marketing & Media
Content generation is one of the most recognised areas where Generative Artificial Intelligence has been put to use by organisations.
Generative AI tools such as GPT are being used by businesses across the spectrum to create written content for blogs, articles, social media updates and advertisements.
Example of Heliograf (The Washington Post)
The Washington Post has begun using an AI tool called Heliograf to compose brief articles about specific news events. By giving Heliograf the ability to produce these basic, repetitive types of news coverage about things like sports scores and political updates, The Washington Post can allow human reporters to work on stories that require a higher level of complexity.
Implementing Generative AI has made it possible for The Washington Post to create content much faster than before, at an increased volume, and at the same overall quality as was produced previously.
Return on Investment (ROI) Benefits:
- Cost Savings: Utilizing Generative AI allows newspapers to avoid relying on large teams of content writers for repetitive written tasks.
- Time Savings: Generative AI allows news organisations to produce news articles at near to real-time, which greatly diminishes the time between when an article is produced and when it is published.
- Scalability: With the Generative AI capabilities, newspapers can create more content, using fewer resources than ever before.
2. Design and Prototyping in Fashion
In the area of fashion design/prototyping, generative AI is changing the landscape of fashion design. Fashion organizations are using AI tools to analyse data from prior years, consumer preferences, and current trends to quickly and effectively design new clothing collections.
Example: Tommy Hilfiger and IBM
A great example of this is the partnership between Tommy Hilfiger and IBM to create an AI platform that allows Tommy Hilfiger to generate clothing designs based upon real-time analysis of consumer trends.
Additionally, this AI platform will allow Tommy Hilfiger to identify potential styles, patterns, and materials that will likely gain popularity for the upcoming seasons, therefore decreasing the amount of time and labour needed to design clothing collections.
AI in Fashion Design ROI:
- Cost Savings (Faster, less expensive prototypes): Using AI generated prototypes is helping Tommy Hilfiger to shorten their design timelines, thus resulting in cost reducing the overall design process.
- Innovative Fashion Designs (Unique/fresh designs based on up and coming trends): With AI providing fashion designers with real-time analysis of consumer preferences and other data sources, Tommy Hilfiger can remain innovative by creating new and unique designs based on up-and-coming consumer preferences and current industry trends.
- Sustainability (Optimisation of designs/reduction of overproduction): By optimising the designs of clothing collections and significantly reducing the ability to produce excess inventory, Tommy Hilfiger is reducing the amount of waste associated with clothing production processes.
3. Healthcare: Drug Discovery
Generative AI is expediting drug discovery, a key area of healthcare. AI can generate molecular structures that could become new treatments for particular diseases.
By simulating how various molecules will interact, AI eliminates the need for laborious, traditional laboratory experiments.
Example: Insilico Medicine
Insilico Medicine utilizes generative AI to help design drug molecules to target multiple diseases. Their generative AI platform enables researchers to design possible drug molecules and then simulate the potential effects of those drug molecules to help researchers narrow their focus to the most likely drug molecules.
As an illustration, the use of generative AI enabled researchers at Insilico Medicine to identify a potential drug for fibrosis, which is a disease for which there are no currently approved therapies, and would otherwise be extremely difficult to find with traditional drug discovery techniques.
ROI Impact:
- Cost Savings: Generative AI reduces the costs associated with traditional drug discovery by enabling the simulation of molecular interactions.
- Revenue Generation: Accelerated time to market for new drugs results from a decrease in drug development time due to generative AI, which has the potential to provide incremental revenue from the introduction of new drugs to the marketplace.
- Improved Decision-Making: Early identification of the best drug candidates by utilizing generative AI improves the likelihood of successful clinical trial results for those drug candidates.
4. Customer Service – AI Driven Chatbots
AI chatbots are changing the way we do Customer Service because they can answer common questions, troubleshoot problems, and help you with your transactions.
This means there’s less reliance on real people (Customer Service representatives), which provides you with faster, anytime support.
Example: Sephora Virtual Artist
Sephora is a worldwide retailer of cosmetics and has an AI driven chat called Sephora Virtual Artist that provides customers with personalized makeup suggestions.
This AI powered chat uses images of customers’ skin tones combined with artificial intelligence to suggest products for each customer based on their own preferences and previous purchases.
Impact on Return on Investment:
- Cost Reduction: The use of AI reduces the amount of Customer Service representatives needed to process routine inquiries, therefore reducing the overall cost of your Customer Service.
- Time Saving: Shoppers receive immediate, personalized responses to their inquiries, making their shopping experience an excellent one.
- Increased Sales: Personalized recommendations on products to purchase lead to higher conversion rates for Sephora.
Final Thoughts on Maximizing the Value of Generative AI
Generative AI clearly has the potential to offer return on investment throughout all sectors of commerce. There are already numerous examples of organizations, including The Washington Post, Tommy Hilfiger, and Insilico Medicine, among others, benefitting greatly from these technologies.
These organizations have improved their profit margins in operating costs, streamlined operations at higher levels, and created new lines of revenue by utilizing automation (with the help of artificial intelligence) for repetitive tasks that help enhance creative workflow and improve the quality of decision-making.
Author Bio
Yuliya Melnik is a technical marketing writer with a strong focus on AI, software development, and innovative digital solutions. She enjoys breaking down complex technical concepts into clear, practical insights for businesses and tech enthusiasts.
