What’s the future of generative AI? Read on…

Since the release of ChatGPT in November 2022, it’s been all over the headlines, and businesses are racing to capture its value. Within the technology’s first few months, McKinsey research found that generative AI (gen AI) features stand to add up to $4.4 trillion to the global economy—annually. In this report, McKinsey has compiled all the answers they have so far — in 15 McKinsey charts.

Generative AI is a type of artificial intelligence that can create new content, such as text, images, and music. It is still in its early stages of development, but it has the potential to revolutionize many industries.

One of the most promising applications of generative AI is in the field of business. Generative AI can be used to create personalized marketing campaigns, generate leads, and develop new products and services. For example, a company could use generative AI to create personalized email campaigns for its customers, based on their past purchase history and interests. Or, a company could use generative AI to design and test new product prototypes, without having to invest in expensive physical prototypes.

Generative AI is also having a major impact on the creative industries. Generative AI can be used to create new forms of art, music, and literature. For example, generative AI can be used to create new musical compositions or to generate new text formats of text content, like poems, code, scripts, musical pieces, email, and letters.

Generative AI is also being used in a variety of other industries, such as healthcare, finance, and education. For example, generative AI is being used to develop new drugs and treatments, design new financial products and services, and create personalised learning materials for students.

The potential economic impact of generative AI is enormous. McKinsey estimates that generative AI could create trillions of dollars in new economic value by 2030.

However, there are also some concerns about the potential negative impacts of generative AI. One concern is that generative AI could lead to job displacement, as machines become capable of performing tasks that are currently done by humans. Another concern is that generative AI could be used to create deepfakes, which are realistic but fake videos or audio recordings that can be used to deceive people.

Overall, the future of generative AI is very promising. Generative AI has the potential to revolutionise many industries and create trillions of dollars in new economic value. However, it is important to be aware of the potential negative impacts of generative AI and to take steps to mitigate them.

What the data says

Market demand: 90% of marketing and sales leaders believe that their organizations should be using generative AI.

Adoption rates: 60% of marketing and sales leaders say that their organizations rarely or never use generative AI.

Economic impact: McKinsey estimates that generative AI could create trillions of dollars in new economic value by 2030.

Job displacement: 80% of workers in the United States are concerned that their jobs could be automated by AI in the next 50 years.

Deepfakes: 60% of Americans believe that deepfakes are a major threat to democracy.

These percentages suggest that there is a strong demand for generative AI, but that many organizations are not yet using it. This isbecauseact that generative AI is still a relatively new technology and that many organizations are not yet familiar with its benefits.

How generative AI is being used today

Marketing: Generative AI is being used to create personalized marketing campaigns and content. For example, AI can be used to generate personalised email campaigns or social media posts.

Sales: Generative AI is being used to generate leads and qualify prospects. For example, AI can be used to generate a list of potential customers who are likely to be interested in a company’s products or services.

Product development: Generative AI is being used to design new products and services. For example, AI can be used to design a new car or a new piece of furniture.

Healthcare: Generative AI is being used to develop new drugs and treatments. For example, AI can be used to design new drugs that are more effective and have fewer side effects.

Finance: Generative AI is being used to develop new financial products and services. For example, AI can be used to develop new trading algorithms or to design new risk management tools.

Education: Generative AI is being used to create personalized learning materials for students. For example, AI can be used to generate tailored practice problems or to create interactive learning simulations.

These are just a few examples of the many ways that generative AI is being used today. As generative AI technology continues to develop, we can expect to see even more innovative and groundbreaking applications of generative AI in the future.

Generative AI is a powerful new technology with the potential to revolutionise many industries. However, it is important to be aware of the potential negative impacts of generative AI and to take steps to mitigate