Blog: Generative AI in action: real-world applications and examples

Notably, the potential value of using generative AI for several functions that were prominent in our previous sizing of AI use cases, including manufacturing and supply chain functions, is now much lower.5Pitchbook. This is largely explained by the nature of generative AI use cases, which exclude most of the numerical and optimization applications that were the main value drivers for previous applications of AI. In this section, we highlight the value potential of generative AI across business functions.

In response, workers will need to become content editors, which requires a different set of skills than content creation. Foremost are AI foundation models, which are trained on a broad set of unlabeled data Yakov Livshits that can be used for different tasks, with additional fine-tuning. Complex math and enormous computing power are required to create these trained models, but they are, in essence, prediction algorithms.

> Supply Chain & Procurement Applications

In February 2023, they launched their first “Infinity Quizzes,” which create personalized quizzes for users based on a few inputs. AdCreative.ai is a generative AI app that quickly generates conversion-focused ad creatives and social media posts. With the ability to specify the target audience and platform, it selects the ideal message aligned with specific business goals. With the help of generative AI, we are witnessing exciting communication possibilities, including new and improved ways to present information, highly useful real-time AI assistants, and streamlined content optimization processes.

By providing a simple prompt, users can instantly generate captivating slides for product presentations, sales pitches, training sessions, client proposals, and more. To demonstrate the real impact of AI, we have also integrated real-world generative AI examples that are already leaving a profound imprint on people’s work processes. In addition to generating visual content, generative AI can also be used to create music and audio. This can range from original songs and compositions to human-like voice audio for use in voiceovers or assistive technologies.

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With a simple chat interface, Cleo assists users in saving money, budgeting effectively, and gaining financial knowledge. RAD AI merges data-driven insights and authentic content to assist marketing teams in crafting impactful campaigns. By analyzing past performance and formulating effective strategies, it aims to establish genuine and emotional connections with the target Yakov Livshits audience across various marketing channels. Users can paste their travel inspiration from text messages, social media, or blogs, and the app automatically saves and researches each mentioned place leveraging generative AI. There’s no doubt that education today faces many challenges, including unequal access, outdated methods, and the need for personalized learning.

However, by harnessing advanced technologies, including the integration of generative AI, farmers can overcome these hurdles and achieve optimized crop production, efficient resource management, and sustainable practices. It enables designers and architects to swiftly create and render designs with a multitude of options, including color, Yakov Livshits material, finish, and part-specific modifications. The result is faster and more versatile design iterations than ever before and thus better user experience for clients. Today, the manufacturing industry is a vibrant and rapidly evolving landscape, where technological advancements and streamlined processes are revolutionizing production.

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

Some 40 percent of the activities that workers perform in the economy require at least a median level of human understanding of natural language. Generative AI could have a significant impact on the banking industry, generating value from increased productivity of 2.8 to 4.7 percent of the industry’s annual revenues, or an additional $200 billion to $340 billion. On top of that impact, the use of generative AI tools could also enhance customer satisfaction, improve decision making and employee experience, and decrease risks through better monitoring of fraud and risk. In the life sciences industry, generative AI is poised to make significant contributions to drug discovery and development. For example, our analysis estimates generative AI could contribute roughly $310 billion in additional value for the retail industry (including auto dealerships) by boosting performance in functions such as marketing and customer interactions.

An image generator, for example, can help a graphic designer create whatever image they need (See the figure below). With generative AI, users can transform text into images and generate realistic images based on a setting, subject, style, or location that they specify. Therefore, it is possible to generate the needed visual material in a quick and simple manner. In this article, we have gathered the top 100+ generative AI applications that can be used in general or for industry-specific purposes.

These are the types of innovations that can produce step changes not only in the performance of individual companies but in economic growth overall. In 2012, the McKinsey Global Institute (MGI) estimated that knowledge workers spent about a fifth of their time, or one day each work week, searching for and gathering information. If generative AI could take on such tasks, increasing the efficiency and effectiveness of the workers doing them, the benefits would be huge. Our second lens complements the first by analyzing generative AI’s potential impact on the work activities required in some 850 occupations.

• Assuming that such issues are addressed, however, LLMs could rekindle the field of knowledge management and allow it to scale much more effectively.
• Based on data about the customer, such as age, health history, location, and more, the AI system can generate a policy that fits those individual attributes, rather than providing a one-size-fits-all policy.
• When a customer sends a message with a complaint, the tool can analyze the message and provide a response that addresses the customer’s concerns and offers potential solutions.
• Possible indications for a given drug are based on a patient group’s clinical history and medical records, and they are then prioritized based on their similarities to established and evidence-backed indications.
• It can also be used to generate text that is specifically designed to have a certain sentiment.
• Automating repetitive tasks allows human agents to devote more time to handling complicated customer problems and obtaining contextual information.

Generative AI tools can help generate policy documents based on user-specific details. It can automatically fill in the information where necessary, speeding up the process of creating these documents. By leveraging generative AI to create a variety of fashion models, fashion companies can better serve their diverse customer base and accurately display their products in a more authentic manner.

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For example, a classic machine learning problem is to start with an image or several images of, say, adorable cats. The program would then identify patterns among the images, and then scrutinize random images for ones that would match the adorable cat pattern. Rather than simply perceive and classify a photo of a cat, machine learning is now able to create an image or text description of a cat on demand. Farmer.CHAT is an AI-based farmer advisory service that connects governments and farmers for real-time communication.

Needless to say, these technologies will provide substantial work for intellectual property attorneys in the coming years. We have already seen that these generative AI systems lead rapidly to a number of legal and ethical issues. “Deepfakes,” or images and videos that are created by AI and purport to be realistic but are not, have already arisen in media, entertainment, and politics.

Similarly, a tool developed by Synthesized can help researchers expand existing drugs beyond their initial use to treat other diseases, which could make medicines more accessible. Generative AI has quickly become a major factor in a number of industries, including health care. It has the potential to transform the sector, but executives must understand how to use the technology in order to capitalize on its potential while avoiding the risks inherent in applying it to patient care. We analyzed numerous use cases across health segments, looking at both solutions already on the market and those likely to arrive soon. Our goal was to demystify generative AI and help leadership teams make sense of the options.