0:03 we've looked at how gen of AI may be
0:06 useful to your work and also talked
0:09 about analyzing its impact on a business
0:11 let's now zoom out and take a look at
0:14 its impact on job rades across different
0:16 companies as well as its impact on
0:19 different industry sectors the results
0:21 from this video may be less directly
0:23 actionable for a particular business but
0:25 maybe this will help you to think
0:27 through and try to forecast some of the
0:30 large macro changes that may take place
0:34 over time let's dive in a study by alund
0:36 and others at openi and the University
0:38 of Pennsylvania examined how much
0:41 different job occupations are exposed to
0:45 AI augmentation or automation that study
0:48 resulted in this graph showing that
0:51 higher wage jobs tend to be more exposed
0:54 to AI augmentation or automation than
0:57 lower wage jobs in this draft which is a
0:59 slightly funny horizontal axis because
1:02 it's on the log scale we plot salaries
1:06 ranging from about 30k up to about 163k
1:09 like this and the vertical axis measures
1:12 the degree to which these jobs are
1:15 exposed to automation earlier waves of
1:18 automation tended to have lower wage
1:20 jobs more exposed because AI could do
1:23 more of the routine repetitive work so
1:25 supervised learning for example tended
1:29 to automate more of the lower wage jobs
1:32 but large language models and G AI more
1:35 broadly are exposing in this wave the
1:38 higher wage occupations so Automation
1:39 and we'll say more later this week as
1:43 well about the impact of G of AI on jobs
1:46 let's look at a second study uh due to
1:48 McKenzie which carries out an analysis
1:51 by functional role so this graph plots
1:52 different functions that tries to
1:54 estimate how much will sales be impacted
1:56 how much will marketing be impacted how
1:58 much will customer operations including
2:01 customer service be impacted the
2:03 vertical axis here shows the total
2:06 impact in terms of billions of dollars
2:08 and so the points in the upper portion
2:10 of this graph correspond to the
2:13 functional roles where the total value
2:16 of the impact will be large in terms of
2:18 total number of dollars the horizontal
2:21 axis measures the impact as a percentage
2:24 of the functional spin so customer
2:26 operations according to this study will
2:28 have a very large absolute dollar value
2:31 impact maybe around $400 billion I would
2:33 take the exact numbers not too sery
2:36 since it's are frankly loose estimates
2:38 but the total dollar value seems like it
2:41 will be larged because gen of AI is
2:43 automating or augmenting a lot of
2:46 customer service moreover as a
2:47 percentage of all the spending on
2:50 customer operations gent VI's impact
2:52 will be pretty large as well maybe
2:54 approaching 40% of the total spend on
2:57 customer operations in contrast it will
2:58 also have hundreds of billions of
3:01 dollars impact on sales but as a
3:04 percentage of the total spend on sales
3:06 it is much smaller and the McKenzie
3:10 study also estimates that these yellow
3:12 dots shown on top together might
3:16 represent 75% of the total annual impact
3:19 of G Ai and it will be a significant
3:22 impact now this isn't to say that if you
3:24 work in some of these other functions
3:26 you shouldn't pay attention to gen of AI
3:28 for example if you work in the legal
3:31 function and gender VII will impact 15
3:34 to 20% of the functional spend on legal
3:36 that's still a significant shift for the
3:38 industry even if the total spend on
3:41 lawyers on Legal Services is not nearly
3:44 as big as a total spend on sales or
3:45 marketing or software engineering and so
3:48 on but if the McKenzie study is correct
3:50 then these are some of the functional
3:52 roles across many different companies
3:54 that'll have a huge impact through
3:57 generative AI lastly let's take a look
4:01 at its estimated impact by industry
4:04 sector so McKenzie had carried a study
4:08 on the potential of AI automation with
4:11 and without gent of AI and we repotted
4:14 the McKenzie data to show the impact of
4:18 gent of AI only on automation leaving
4:20 out other forms of AI such as supervised
4:23 learning some of the sectors impacted
4:26 include educator and Workforce training
4:28 business and legal professions s
4:30 professionals and so on
4:34 and one remarkable thing about this data
4:37 is that there are sectors that were not
4:39 highly exposed to automation before
4:41 generative AI but with the rise of
4:44 generative AI is now seeing a much
4:46 greater potential of automation or
4:49 augmentation and so depending on what
4:51 sector or sectors you either work in or
4:53 work with perhaps this type of analysis
4:55 may give you a sense of what may happen
4:57 in industries that you touch as well if
4:59 you look at the top few lines on the
5:02 this graph one theme that pervades both
5:04 this as well as other studies is that it
5:05 looks like a lot of the impact of
5:08 generative AI will be on knowledge
5:11 workers meaning workers who generate
5:13 value primarily through their knowledge
5:16 including the expertise their critical
5:18 thinking and their interpersonal skills
5:21 this is in contrast to say workers that
5:23 create value mainly from performing
5:26 physical TOS rather than knowledge TOS
5:28 this wraps up our section on gent of AI
5:30 and business
5:32 there are lots of opportunities for
5:35 individuals businesses and for
5:38 society the huge impact of gender AI is
5:40 also raising questions about how gent of
5:43 AI will affect society and it's also
5:46 made some people anxious about what the
5:48 future will be like for them in the
5:51 world with these amazing AI capabilities
5:54 let's go on to the next video to examine
5:57 how AI is impacting society as well as
6:00 how we can mitigate risk and how we can
6:04 build beneficial responsible AI I'll see
