What is the future of generative AI?

The advanced machine learning that uses gen AI -activated products has been manufacturing for decades. But since Chatgpt came from the starting block in the end of 2022, new iterations of Gen AI technology have been released several times a month. In March 2023 alone, there were six important steps ahead, including new solutions to customer relationships and support for the financial services industry.

Source: What every CEO of Generative AI should know

For most technical abilities shown in this graph, Gen AI will perform at a median level of human performance by the end of this decade. And its performance will compete with the top 25 percent of people who have completed all these tasks before 2040. In some cases, it is 40 years faster than experts have thought before.

Source: The economic potential of generative AI: The following productivity limit

Previous waves of automation technology have mostly affected physical work activities, but gen AI is likely to have the greatest impact on knowledge work – especially activities that involve decision making and collaboration. Professionals in fields such as education, law, technology and the arts are likely to see earlier that parts of their work are automatic than previously expected. This is due to generative AI’s ability to predict patterns in natural language and use them dynamically.

Source: The economic potential of generative AI: The following productivity limit

Gen AI tools can already create the most types of written, image, video, audio and coded content. And businesses develop applications to address use cases across all these areas. In the near future, we expect applications that target specific industries and functions to offer more value than those that are more common.

Source: Investigate opportunities in the generative AI value chain

Gen AI’s exact impact will depend on a variety of factors, such as the mix and importance of different business functions, as well as the extent of the income of an industry. Almost all industries will see the most important profits from the deployment of the technology in their marketing and sales functions. But high -tech and banking will have even more impact through Gen AI’s potential to accelerate software development.

Source: The economic potential of generative AI: The following productivity limit

When we asked marketing and sales leaders how much they thought their organization should use Gen AI or machine learning for commercial activities, 90 percent thought it should at least be ‘regular’. This is hardly surprising, as marketing and sales are the area with the most potential for impact, as we saw earlier. But 60 percent said their organizations rarely or never do it.

Source: AI-powered marketing and sales reach new heights with generative AI

When we had 40 of McKinsey’s own developer test -generative AI -based tools, we found impressive velocity profit for many common developer tasks. The documentation of code functionality for maintenance (which considers how easily code can be improved) can be completed within half the time, in almost half the time, writing a new code and optimizing the existing code (called CodeRefactoring) in nearly two-thirds.

Source: Unleash the productivity of developers with generative AI

Our research has found that the appropriate developers with the tools they need to be their most productive have also significantly improved their experience, which in turn can help retain their best talent. Developers using generative AI -based instruments were more than twice as likely to report overall happiness, fulfillment and a state of flow. They attributed this to the tool’s ability to automate gruntwork that hindered them from more satisfying tasks and to put information on their fingers faster than seek solutions on different online platforms.

Source: Unleash the productivity of developers with generative AI

A new McKinsey recording shows that the vast majority of workers – in a variety of industries and geographical locations – have tried generative instruments at least once, either in or out of work. This is a fairly quick adoption less than one year. One surprising result is that Baby Boomers report with Gen AI instruments for more than millennials.

Source: The State of AI in 2023: Generative AI’s getaway year

As organizations begin to set Genal goals, they also develop the need for more Gen AI -Literate Workers. As generative and other applied AI instruments begin to deliver value to early employees, the gap between demand and demand for skilled workers remains wide. To keep abreast of the talent market, organizations need to develop excellent talent management capabilities and provide rewarding work experiences to the Gen AI -Literate Workers they rent and hope to retain.

Source: McKinsey Technology Trends Outlook 2023

The possibilities of Gen AI are for very exciting. But like any new technology, Gen AI does not come without potential risks. In the first place, it is known that Gen AI produces content that is biased, virtually wrong or is illegally scrapped from a copyright source. Before adopting Gen AI tools wholesale, organizations must count on the reputation and legal risks they can be exposed to. One way to reduce the risk? Keep one in the loop; That is, make sure that a real person checks any gen AI output before it is published or used.

Source: The State of AI in 2023: Generative AI’s getaway year

McKinsey found that genuine labor productivity in the economy could significantly increase. However, in order to utilize the benefits of this productivity increase, workers whose work is influenced will have to move to other work activities that can at least match their productivity levels of 2022. If workers are supported in learning new skills and in some cases changing professions, stronger global GDP growth can lead to a more sustainable, inclusive world.

Source: The economic potential of generative AI: The following productivity limit