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 - The metaverse
 - The trillion-dollar question: What to do with the workforce in the age of gen AI
 - Think like an AI-native business
 
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                            Navigating tomorrow:
                            gen AI's impact on your job
                        
                        Understanding how generative AI will affect your profession is crucial in career planning. Our interactive tool helps you prepare by quantifying how the fast-moving technology will impact you.
To get started, enter your job role.
Understanding your exposure score
Your exposure score reflects the degree to which your occupation could be affected by generative AI. It takes into account how many of your job's tasks could be fully automated by gen AI; how many could be assisted; and the relative importance of these tasks. A lower exposure score means a lower percent of your job's tasks will be automated, so your profession will be relatively unaffected. The chart shows your exposure score in both 2023 and 2032.
| Job title | 2023 | 2032 | 
|---|
Theoretical maximum Exposure score*
Understanding your friction score
Now that you know your exposure score, let's move on to your friction score. What does this mean? The friction score measures how difficult it will be for workers displaced by gen AI to find new employment with their existing skills. A high friction score means it could be more challenging for you to find new work. This chart shows your friction score in 2027, which forms the midpoint of our analysis.
Find out more about your occupational group
Looking ahead: your job in five years
Now let's put your exposure score and friction score to work to see what your job will look like five years from now. The four quadrants on this chart illustrate the impact gen AI will have on both the tasks that make up your job and the ease with which you will find work in your field.
Data in this chart represents predicted exposure scores versus theoretical maximum exposure scores. See methodology for how these scores are calculated. Bubble size represents the relative number of workers in the job category.
                                        Color coding of bubbles corresponds to wage quintile in 2022, with darkest blue representing the fifth quintile and lightest representing the first.
                                        
                                        Source: Oxford Economics and Cognizant
                                        Figure 4
                                    
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