Using GenAI to Expand Understanding of Health Care Solutions
BCG and Zeiss developed an application to give prospective patients fast, accurate, validated answers about elective treatments.
The new wave of generative AI systems, such as ChatGPT, have the potential to transform entire industries. To be an industry leader in five years, you need a clear and compelling generative AI strategy today.
We are entering a period of generational change in artificial intelligence. Until now, machines have never been able to exhibit behavior indistinguishable from humans. But new generative AI models are not only capable of carrying on sophisticated conversations with users; they also generate seemingly original content.
To gain a competitive edge, business leaders first need to understand what generative AI is.
Generative AI is a set of algorithms, capable of generating seemingly new, realistic content—such as text, images, or audio—from the training data. The most powerful generative AI algorithms are built on top of foundation models that are trained on a vast quantity of unlabeled data in a self-supervised way to identify underlying patterns for a wide range of tasks.
For example, GPT-3.5, a foundation model trained on large volumes of text, can be adapted for answering questions, text summarization, or sentiment analysis. DALL-E, a multimodal (text-to-image) foundation model, can be adapted to create images, expand images beyond their original size, or create variations of existing paintings.
Vladimir Lukic
These new types of generative AI have the potential to significantly accelerate AI adoption, even in organizations lacking deep AI or data-science expertise. While significant customization still requires expertise, adopting a generative model for a specific task can be accomplished with relatively low quantities of data or examples through APIs or by prompt engineering. The capabilities that generative AI supports can be summarized into three categories:
Today, some generative AI models have been trained on large of amounts of data found on the internet, including copyrighted materials. For this reason, responsible AI practices have become an organizational imperative.
Generative AI systems are democratizing AI capabilities that were previously inaccessible due to the lack of training data and computing power required to make them work in each organization’s context. The wider adoption of AI is a good thing, but it can become problematic when organizations don’t have appropriate governance structures in place.
Generative AI text models can be used to generate texts based on natural language instructions, including but not limited to:
This is just the beginning. As companies, employees, and customers become more familiar with applications based on AI technology, and as generative AI models become more capable and versatile, we will see a whole new level of applications emerge.
Generative AI has massive implications for business leaders—and many companies have already gone live with generative AI initiatives. In some cases, companies are developing custom generative AI model applications by fine-tuning them with proprietary data.
The benefits businesses can realize utilizing generative AI include:
BCG and Zeiss developed an application to give prospective patients fast, accurate, validated answers about elective treatments.
The company’s leaders recognize that a GenAI transformation requires a transformation of business processes and people development.
BCG is collaborating with OpenAI to help our clients realize the power of OpenAI technologies and solve the most complex challenges using generative AI—responsibly.
BCG and Google Cloud are excited about generative AI’s transformative capabilities, devoting significant resources to jointly help customers apply this breakthrough technology.
The ability to scale AI applications continues to challenge businesses across industries. Our collaboration with Intel brings together BCG’s transformation expertise, BCG X’s engineering capabilities, and Intel’s AI hardware and software in order to rapidly create enterprise-grade generative AI solutions for our clients—securely and responsibly.
Generative AI technology will cause a profound disruption to industries and may ultimately aid in solving some of the most complex problems facing the world today. Three industries have the highest potential for growth in the near term: consumer, finance, and health care.
Given that the pace the technology is advancing, business leaders in every industry should consider generative AI ready to be built into production systems within the next year—meaning the time to start internal innovation is right now. Companies that don’t embrace the disruptive power of generative AI will find themselves at an enormous—and potentially insurmountable—cost and innovation disadvantage.
Salesforce’s Jonathan Phillips and BCG’s Bryan Gauch discuss the importance of taking GenAI from concept to reality, as well as the opportunities and challenges in the year ahead.
Generative AI can bring a host of ideas—and a critical “outside the box” perspective—to teams working through the innovation cycle.
BMW's Global Head of Brand and Product Management explains how the right organizational processes and platforms can help companies maximize the value of GenAI tools.
BCG’s survey of 1,400+ C-suite executives reveals that GenAI is quickly changing the way companies do business—and big gaps are emerging between the winners and the observers.
For many companies, data governance is already a pain point, the work too manual and tedious. Generative AI increases the burden but, smartly applied, can reduce it instead.
The opportunities presented by generative AI are significant, but leaders need to focus equally on the risks. What is a responsible C-suite member supposed to do?
BCG’s generative AI experts have deep experience in AI technology, neural networks, generative models, the benefits of generative AI, and more. Here are some of our experts in generative AI.