text,start,duration
good morning everybody David Shapiro,0.12,4.56
here with another video so today's video,2.34,4.2
is going to be a little bit less about,4.68,4.98
the narratives around Ai and that sort,6.54,4.139
of stuff and it's going to be a little,9.66,4.019
bit more uh down to Basics uh let's talk,10.679,5.641
let's talk business with artificial,13.679,5.041
intelligence uh particularly generative,16.32,3.48
AI,18.72,3.3
uh real quick plug before we get started,19.8,5.04
uh I am available for one-on-one,22.02,6.179
consultations on patreon and I'm also,24.84,6.3
available uh for for different kinds of,28.199,4.981
engagements uh reach out to me on,31.14,4.259
LinkedIn if you'd like to talk about any,33.18,3.18
of the things that I'm talking about,35.399,2.34
here,36.36,3.48
all right so getting right into the show,37.739,5.361
let's talk about generative AI for CEOs,39.84,5.28
and we're going to look at it at a very,43.1,3.88
high level so first we're going to look,45.12,3.18
at it through the lens of people,46.98,4.919
processes and tools uh all organizations,48.3,5.759
go through Transformations and one of,51.899,4.14
the ways to look at organizational,54.059,4.621
transitions is through people processes,56.039,5.281
and tools what kinds of people do you,58.68,4.44
need and how does that how does that,61.32,4.14
change what kind of expertise training,63.12,4.56
that sort of stuff how do your processes,65.46,4.38
change uh within the business and then,67.68,5.04
what tools do you use so this is just,69.84,4.92
kind of the the the background framing,72.72,4.02
we're not going to unpack these in any,74.76,3.719
particular order we're just going to,76.74,3.96
kind of talk about generative AI through,78.479,3.96
this particular lens,80.7,3.54
so one thing that you can think about,82.439,4.741
generative AI is that it's just more,84.24,3.96
software,87.18,3.6
at a fundamental level generative AI is,88.2,4.559
just a new kind of software but it is,90.78,3.9
still just software,92.759,4.921
one thing to keep in mind is that uh,94.68,5.52
technology you know computers uh,97.68,4.14
software that sort of stuff has,100.2,3.48
automated and accelerated business for,101.82,4.02
decades this is nothing new it's nothing,103.68,4.399
different this is just the next flavor,105.84,5.4
for those of you in the technology space,108.079,4.921
you might remember how virtualization,111.24,4.44
was a very disruptive technology for the,113.0,5.32
data center and that ultimately led to,115.68,4.52
uh the the,118.32,4.74
preeminence of cloud computing which is,120.2,4.959
now pretty much standard and so the,123.06,5.22
combination of virtualization and apis,125.159,6.001
and stuff that made cloud computing uh,128.28,4.98
you know the viable business model that,131.16,4.68
it is today this is no different from,133.26,5.119
how Oracle and SQL Technologies,135.84,4.74
transformed uh the way that businesses,138.379,4.481
handled data and then of course there's,140.58,4.32
everything that Microsoft did for for,142.86,3.66
business productivity from their office,144.9,4.02
suite to Microsoft Windows and,146.52,4.26
everything else team Foundation,148.92,3.959
everything,150.78,3.36
so,152.879,3.061
from that perspective from a software,154.14,4.98
perspective you can think of a,155.94,6.06
generative AI in two primary categories,159.12,5.399
the first category is that generative AI,162.0,4.62
is a new kind of automation,164.519,4.621
and so you know again business,166.62,6.3
automation nothing new uh and business,169.14,5.879
automation is also it doesn't really,172.92,4.74
change the idea is that you just do more,175.019,4.681
with less you do it faster and you do it,177.66,5.52
more reliably so looking at generative,179.7,6.179
AI through the lens of automation the,183.18,4.98
idea is that it can take some of the,185.879,4.621
workload off of humans and put it onto,188.16,4.98
machines and then it can allow you to,190.5,5.879
get more done faster with less and more,193.14,5.28
reliably that is the entire point of,196.379,3.72
automation,198.42,3.66
another thing that you can look at it is,200.099,3.661
and this is kind of the fundamentally,202.08,5.1
new aspect is it has to do with decision,203.76,5.88
enhancement and what I mean by that is,207.18,4.76
that the particularly language models,209.64,5.459
they can Aid with all kinds of things,211.94,6.04
whether it's judgment creativity,215.099,6.0
appraisal brainstorming drafting they,217.98,5.399
can also read a tremendous amount in,221.099,3.601
very short periods of time which can,223.379,3.78
allow you to make better decisions by,224.7,5.58
ingesting more data than ever before,227.159,5.22
so by thinking of generative Ai and,230.28,5.459
these two uh like I guess categories,232.379,5.94
Automation and decision enhancement that,235.739,4.741
can really help you target where in your,238.319,3.78
corporation where in your organization,240.48,5.52
to look at using generative AI again the,242.099,5.521
idea of automation is that you get more,246.0,4.04
done faster and of course time is money,247.62,4.56
another thing is that you can do it with,250.04,3.46
less you might be able to do it with,252.18,3.479
less head count or you can take the,253.5,3.72
ideally you take the head count that you,255.659,2.58
do have because we don't want to see,257.22,3.239
anyone get laid off if we can avoid it,258.239,5.46
and then you you Empower your existing,260.459,6.3
staff to do twice as much four times as,263.699,6.0
much 10 times as much so that is and,266.759,4.141
then of course you can also use,269.699,3.961
generative AI to perform checks and,270.9,5.22
interlocks which can raise the quality,273.66,5.4
of work and make it more consistent so,276.12,4.799
those are a few uh kind of off the cuff,279.06,3.12
ways to think about it like yes,280.919,3.901
generative AI is just more software but,282.18,4.68
there's it does give us a couple new,284.82,4.26
capabilities of this software,286.86,4.98
So speaking of new capabilities uh,289.08,5.28
generative AI mostly right now is text,291.84,4.38
and images but there's other modalities,294.36,5.22
coming soon namely video audio and a few,296.22,5.64
other things so what are the what are,299.58,4.38
the Baseline capabilities that this,301.86,4.5
technology has first of all as a,303.96,4.92
language model it is primarily based on,306.36,5.16
text which means it can read everything,308.88,4.94
it can ingest email chat papers,311.52,4.86
scientific papers articles laws,313.82,5.26
protocols reports logs tribal knowledge,316.38,5.759
in the form of KB articles documentation,319.08,4.5
that sort of stuff,322.139,3.241
so when you think when you have a,323.58,4.08
machine that can read at a thousand,325.38,5.22
times faster than any human think of the,327.66,4.8
text Heavy aspects of your business,330.6,4.5
whether that is combing through,332.46,5.76
financial reports or consolidating,335.1,6.18
Knowledge from from chat logs customer,338.22,5.46
feedback there's all kinds of stuff that,341.28,3.96
is text based or could easily be,343.68,3.78
rendered as text that you can then just,345.24,4.5
read and get a tremendous amount of,347.46,5.16
information from now the problem there,349.74,4.32
of course is you have to be asking the,352.62,3.72
right questions and there are also still,354.06,4.62
technical limits namely the window size,356.34,3.72
of some of these things,358.68,4.019
you can summarize and transform text and,360.06,4.02
information and so what I mean by that,362.699,3.121
is you can take a large block of text,364.08,4.86
and you can either make it smaller or,365.82,4.68
change the formatting or that sort of,368.94,4.02
thing which again this is one of the two,370.5,4.8
one of the new tools in the toolbox,372.96,4.92
that allows you to engage with the data,375.3,4.679
that you do have in a different manner,377.88,4.62
uh brainstorming and planning so this is,379.979,5.16
one of the most powerful aspects of,382.5,5.16
tools such as chat gbt it's like hey I'm,385.139,4.201
addressing this problem help me,387.66,4.2
brainstorm how to approach it uh I've,389.34,4.979
used brainstorming everything for uh,391.86,4.32
writing fiction you know it's like hey,394.319,4.201
I'm working on this scene uh help me,396.18,4.079
brainstorm a few ways to approach the,398.52,3.959
scene so that it you know ticks these,400.259,4.321
boxes right you give it you give it some,402.479,4.5
constraints and Technologies like chat,404.58,4.679
GPT will absolutely surprise you in,406.979,4.141
terms of what they're capable of helping,409.259,5.041
you brainstorm because they it has a lot,411.12,4.859
more information than than you will ever,414.3,3.3
have and so if you give it the right,415.979,3.181
constraints and the right problem space,417.6,3.78
it will surprise you and it'll add,419.16,4.56
information to uh what you're trying to,421.38,4.5
do planning one of the things that's,423.72,3.96
really good at is helping you think,425.88,4.08
through every step of a plan,427.68,4.859
brainstorming and planning are among the,429.96,4.679
most cognitively demanding tasks and,432.539,4.44
we'll talk about cognitive demands and,434.639,4.921
cognitive offload in just a moment but,436.979,4.62
basically you know there are some things,439.56,3.9
that chat GPT and similar Technologies,441.599,4.621
can do that can save you a tremendous,443.46,4.92
amount of mental energy which then you,446.22,4.379
can allocate to other things other,448.38,4.5
problems that AI is not yet capable of,450.599,4.021
doing and then finally Drafting and,452.88,4.379
revising uh you know whether you're,454.62,4.44
writing a legal document or an agreement,457.259,4.621
or a contract or even just drafting an,459.06,5.28
email I mean I use chat GPD it's like,461.88,4.74
hey I need to respond to this email I,464.34,3.9
want to do it diplomatically and explain,466.62,4.32
it clearly and you know like yes I am,468.24,4.799
good at writing but it's just easier to,470.94,4.199
have the machine write the first draft,473.039,5.1
for me and then I can clean it up and,475.139,4.921
then revisions as well,478.139,3.661
in some of my previous videos you might,480.06,4.44
have seen where I use uh the chat GPT,481.8,4.98
API to provide feedback on my fiction,484.5,4.8
and and plenty of other things I often,486.78,5.16
use chat GPT for uh helping actually,489.3,5.22
even make these slide decks although I'm,491.94,3.84
getting better at making these slide,494.52,3.239
decks so I actually need it less which,495.78,3.539
is a really interesting phenomenon it's,497.759,3.66
like okay I've actually gained new,499.319,4.201
skills by using this tool and I am,501.419,3.601
better at communicating now and I need,503.52,3.66
this tool less really fascinating I,505.02,3.299
don't know if that's going to keep up,507.18,4.079
but anyway so here these are four basic,508.319,6.001
categories of new capabilities that you,511.259,5.041
can think of in terms of okay what is it,514.32,3.899
that generative AI is actually capable,516.3,4.44
of right now and then from there these,518.219,3.721
are kind of the low level building,520.74,4.02
blocks that you can slot into other,521.94,5.22
products other services whether it's,524.76,4.139
internal or external right because you,527.16,4.02
might have internal facing tools you,528.899,4.44
might have external facing tools and,531.18,3.42
these are things that you can just kind,533.339,3.241
of pipe into existing Frameworks,534.6,4.56
existing processes to make them better,536.58,4.5
you can also think about these when,539.16,4.56
creating new products and services,541.08,5.66
okay so as I promised cognitive offload,543.72,6.72
most humans are capable of two to maybe,546.74,5.86
four hours of high performance cognitive,550.44,5.16
labor per day many people less so an,552.6,4.56
average a rule of thumb is about two,555.6,2.76
hours,557.16,4.2
so the idea of cognitive offload is that,558.36,4.56
it's like okay whatever it is that's,561.36,4.8
difficult you uh delegate that to,562.92,5.34
someone else you delegate it to a,566.16,3.66
machine,568.26,3.68
excuse me you delegate it to a machine,569.82,5.22
you uh you do something to make it,571.94,6.399
easier you create a process or you,575.04,5.4
offshore it or whatever,578.339,3.661
so what are some things that are,580.44,3.74
cognitively demanding decision making,582.0,4.38
there's a phenomenon called decision,584.18,5.44
fatigue if you follow hbr uh and or,586.38,5.579
scitec daily or whatever there's plenty,589.62,3.899
of research that goes into decision,591.959,3.421
fatigue and basically what this means is,593.519,4.921
that the cognitive demand of making,595.38,5.7
decisions all day is very very taxing,598.44,4.68
it's very draining and so what happens,601.08,4.379
is that after making too many decisions,603.12,5.1
once decision fatigue takes over people,605.459,4.32
will just kind of go with the default,608.22,3.299
answer or whatever they're most,609.779,3.961
comfortable with or they'll use simpler,611.519,4.5
and simpler heuristics and objectively,613.74,4.98
speaking decisions get worse with with,616.019,5.701
time and fatigue so any place that you,618.72,6.66
can use generative AI to offload some of,621.72,5.46
the decision-making process from humans,625.38,4.019
or to augment it right because it,627.18,3.719
doesn't necessarily mean taking it from,629.399,4.201
Human but instead instead of having to,630.899,4.981
have a human synthesize all the things,633.6,4.14
and think through it you can have the AI,635.88,3.959
generator report like okay based on the,637.74,3.3
problem space that you're addressing,639.839,3.721
here's the top three choices you know,641.04,4.14
think through this and again this is,643.56,3.24
something that I use chat GPT for all,645.18,3.36
the time it's like okay help me think,646.8,3.06
through what you know what are the,648.54,2.82
questions that I'm forgetting to ask,649.86,4.38
myself that sort of thing and by by,651.36,4.32
having the machine do some of the,654.24,3.659
thinking for me it preserves my,655.68,4.2
cognitive energy for other problems,657.899,4.56
speaking of problem solving,659.88,5.28
problem solving is also very very,662.459,5.461
cognitively demanding whether you're,665.16,4.44
trying to solve a financial problem a,667.92,3.2
legal problem a technology problem,669.6,4.02
having something that you can bounce,671.12,5.5
ideas off of or ideally actually just,673.62,5.58
pipe it into your existing products and,676.62,5.219
services and platforms where either it,679.2,4.8
can solve the problem for you or it can,681.839,4.68
help you solve problems again this is,684.0,6.12
going to be a high value ad where the,686.519,4.981
overall intelligence of your,690.12,3.6
organization will go up if you use,691.5,4.2
generative AI to help your organization,693.72,4.619
solve problems better but it also save,695.7,4.74
your employees brain power for the,698.339,3.901
problems that AI is not yet capable of,700.44,2.7
solving,702.24,3.779
learning learning is something that uh,703.14,4.62
All Humans Do it's natural it's,706.019,3.841
instinctive it's reflective sorry,707.76,3.9
reflexive you don't even need to think,709.86,3.9
about doing it but when you put yourself,711.66,3.9
in a position where you're deliberately,713.76,3.84
learning and stretching your mind that,715.56,4.56
is very exhausting it's very taxing uh,717.6,4.62
and so what you can do is you can use,720.12,5.459
these tools to help streamline your,722.22,5.16
training your learning,725.579,4.741
and what that does is that you uh can,727.38,4.68
meet everyone where they are for your,730.32,4.38
training programs and you can also often,732.06,4.5
learn faster because then you have an,734.7,3.66
interactive modality and you can,736.56,3.899
basically create an internal uh,738.36,4.68
customized tutor that says okay here's,740.459,4.44
the company's training material let's,743.04,3.539
get through it and then instead of just,744.899,3.781
like watching a brain dead boring video,746.579,3.961
that nobody actually cares about anyways,748.68,4.62
you can have an interactive experience,750.54,4.799
which one will make the training more,753.3,4.8
engaging uh and that that level of,755.339,4.921
Engagement means that people will enjoy,758.1,4.739
it more and they'll retain it better,760.26,4.44
and then of course that's you know,762.839,3.3
corporate training is one thing but,764.7,3.42
there's also there's also the uh,766.139,4.921
acquisition of new skills so let's say,768.12,4.56
you're bringing you're onboarding a new,771.06,3.839
product or a new service or you're,772.68,3.719
shipping a new product and service and,774.899,3.481
you need to teach people about it so,776.399,3.541
remember that learning is very,778.38,3.899
cognitively demanding and AI chat Bots,779.94,4.62
are already good at tutoring and,782.279,4.441
teaching and so this again is a way,784.56,4.079
where you can use the AI not to replace,786.72,4.32
humans but to augment humans and bring,788.639,3.781
them to the next level,791.04,4.56
creativity synthesizing new ideas is,792.42,5.099
also very very difficult it's very,795.6,4.979
cognitively demanding and while,797.519,5.461
Technologies like chat GPT and others,800.579,4.26
are not technically creating anything,802.98,3.78
new most humans don't create anything,804.839,3.901
new anyways we just remix stuff that,806.76,3.72
we've experienced which is not any,808.74,3.42
different from what generative AI does,810.48,4.14
and also within the context of business,812.16,4.2
you don't necessarily need to create,814.62,5.04
anything entirely 100 new what you do,816.36,5.34
need to do is take the things that you,819.66,5.46
know and then deploy them with with good,821.7,6.12
application you need to find the right,825.12,4.32
solution for the problem that you're,827.82,2.639
facing,829.44,3.36
whether it's a marketing problem legal,830.459,4.201
Finance HR right if you need to come up,832.8,4.86
with a creative solution for an HR issue,834.66,6.119
again chat GPT knows enough about the,837.66,5.28
human condition and emotions and all,840.779,3.3
this other stuff to help you think,842.94,2.82
through and come up with Creative,844.079,4.26
Solutions uh whatever it is that you're,845.76,4.68
doing and then finally planning as I,848.339,4.201
mentioned planning is very cognitively,850.44,3.959
demanding and this is this includes,852.54,4.32
forecasting anticipation or even,854.399,4.801
predicting the future and so basically,856.86,3.84
one thing that you can do is you can ask,859.2,5.16
chat gbt say like hey uh you know the,860.7,5.22
these are the business trends that I'm,864.36,3.479
seeing this is what the Market's doing,865.92,3.96
help me think through this and it it's,867.839,3.901
not necessarily going to be 100 right,869.88,4.199
but that's not the point what I'm saying,871.74,3.96
is you're not using it to replace your,874.079,3.06
ability to plan you're using it to,875.7,3.66
augment your ability to plan,877.139,4.38
so the golden rule for all of this one,879.36,4.14
of the best ways you can use generative,881.519,4.26
AI this Golden Rule is preserve human,883.5,4.68
cognition for when you really need it so,885.779,5.641
this design principle goes uh it one,888.18,5.88
it's it's relatively old this is one of,891.42,4.56
the chief design principles in the Unix,894.06,4.2
operating system which treats human,895.98,5.34
cognition as a scarce resource but also,898.26,5.28
this is how jet fighters work so the,901.32,5.1
avionics research industry uh for,903.54,5.58
particularly for military realized that,906.42,4.919
you needed to treat a pilot's cognitive,909.12,4.86
attention as the scare as a very scarce,911.339,5.401
resource and so the avionics in jet,913.98,5.76
fighters only gets their attention when,916.74,4.86
they absolutely need it,919.74,4.08
and so if you watch the top gun Maverick,921.6,3.479
movie,923.82,2.879
um one of the scenes where the plane is,925.079,3.661
like spiraling towards the ground and it,926.699,3.721
the alarm starts where it's like you,928.74,4.14
know pull up pull up pull you know and,930.42,4.68
then as the uh as the level of danger,932.88,5.759
Rises the alarm changes right and so,935.1,6.419
that change in tone uh what that does is,938.639,4.5
it calls the Pilot's attention to,941.519,3.721
something that is at that they need to,943.139,4.56
pay attention to immediately uh and so,945.24,5.159
that is an example of how uh attention,947.699,5.221
engineering can be used for good rather,950.399,3.781
than the way that it's used in social,952.92,4.08
media and this is just an example but if,954.18,5.94
you the the whole point here is that the,957.0,5.579
the point of cognitive offload is to,960.12,5.1
treat your employees brain power those,962.579,4.38
those two hours of high performance,965.22,3.66
cognitive labor as a very scarce,966.959,4.62
resource so that instead of you know,968.88,5.1
using their raw brain power to do the,971.579,4.981
work manually instead they use a machine,973.98,4.38
to offload as much of that as possible,976.56,4.2
so that then they can protect their,978.36,4.919
productivity for or elsewhere,980.76,4.92
so here's some questions to ask so these,983.279,4.201
are based on questions that I often ask,985.68,5.219
when I'm Consulting uh and this is these,987.48,5.099
are the questions that I ask to zoom,990.899,4.62
into and find okay where is it that you,992.579,5.161
need to use generative Ai and how do you,995.519,4.44
employ it so the first question what,997.74,3.959
activities are the most menial tedious,999.959,4.201
and time consuming what do you avoid,1001.699,5.161
doing because it's just too painful,1004.16,5.7
so this is a really good question I,1006.86,4.38
usually start with something like this,1009.86,3.539
especially if if uh you know my client,1011.24,4.08
or whatever doesn't really know what,1013.399,3.36
they need or know how to deploy,1015.32,3.0
generative AI it's like okay what are,1016.759,3.481
your pain points and of course this is a,1018.32,3.66
business practice that is as old as,1020.24,3.719
business itself what are your pain,1021.98,3.66
points let's see if we can address those,1023.959,4.62
pain points with generative AI,1025.64,4.98
and you know the the way that it can,1028.579,3.6
address it is you know look at cognitive,1030.62,3.36
offload and new capabilities,1032.179,3.841
the second question is what activities,1033.98,4.62
actually add value what is the,1036.02,4.559
objectively uh beneficial business,1038.6,3.78
output of a given activity or in other,1040.579,4.141
words what is the value proposition what,1042.38,3.959
is what is the activity that you're,1044.72,3.66
doing that is actually giving something,1046.339,4.321
to your customers what are you getting,1048.38,4.14
paid to do what is the outcome that,1050.66,3.84
they're looking for because if you apply,1052.52,4.26
generative AI directly to your outputs,1054.5,4.22
to the things that bring in Revenue,1056.78,4.68
obviously that's good for business what,1058.72,4.3
a lot of startups are doing right now is,1061.46,3.48
trying to invent new products and new,1063.02,4.38
services to create entirely new revenue,1064.94,4.08
streams but there's plenty of existing,1067.4,4.2
businesses out there that could probably,1069.02,5.159
help their Top Line you know get the get,1071.6,5.66
the net uh income up by,1074.179,6.24
providing more goods and services either,1077.26,5.919
at a cheaper price or adding some novel,1080.419,4.341
features to their products and services,1083.179,4.5
but by by actually paying attention to,1084.76,6.159
the objective business value of any,1087.679,4.981
activity and this it doesn't necessarily,1090.919,3.541
have to be the business outputs it could,1092.66,3.78
be the outputs of a given Department the,1094.46,3.839
HR department your legal department your,1096.44,3.42
it Department your marketing department,1098.299,3.601
right because one of the what is the,1099.86,3.78
output of the marketing department you,1101.9,3.899
generate you generate leads which can,1103.64,3.419
lead to revenue,1105.799,3.12
so that's what I mean by outputs what is,1107.059,4.681
the objective value added number three,1108.919,5.161
how do you know that an activity is,1111.74,3.42
successful,1114.08,4.68
whether it's a kpi intuition experience,1115.16,5.7
what is it that you actually pay,1118.76,4.5
attention to to know that you have been,1120.86,5.22
successful the reason that this is a,1123.26,5.159
good question for generative AI is,1126.08,4.44
because sometimes it's not obvious how,1128.419,3.961
generative AI can help you be more,1130.52,4.56
successful so if they're like you know,1132.38,4.26
if you're looking for an intangible,1135.08,3.42
right like maybe you need to build,1136.64,4.56
customer trust or build rapport that is,1138.5,5.7
something that uh that might surprise,1141.2,4.56
you but chat GPT and other similar,1144.2,3.0
Technologies can actually help you with,1145.76,5.159
you say like uh hey I you know I'm gonna,1147.2,6.78
I've got a customer that I'm cultivating,1150.919,4.801
um let me feed you in the profile for,1153.98,3.54
this customer let's talk about this,1155.72,3.18
customer and let's connect with what,1157.52,3.36
they actually need right how can I how,1158.9,3.659
can I make this customer trust me how,1160.88,4.08
can I earn their trust right and so,1162.559,4.98
that's just one example of where if it's,1164.96,5.7
a marketing a sales sales team,1167.539,5.661
it can generative AI can help them,1170.66,5.519
increase their level of success if you,1173.2,4.599
pay attention to what it is that,1176.179,3.481
actually makes them successful and it,1177.799,3.12
does not necessarily have to be,1179.66,2.639
something that you can put a number on,1180.919,3.961
in fact a lot of business is something,1182.299,4.141
that is very difficult to measure,1184.88,5.1
objectively now that being said chat GPT,1186.44,6.0
doesn't necessarily need metrics this is,1189.98,3.9
one of the biggest differences between,1192.44,2.94
conventional machine learning and,1193.88,3.36
artificial intelligence and generative,1195.38,4.86
AI it operates in qualitative space not,1197.24,5.16
quantitative space this is the biggest,1200.24,4.679
fundamental difference between data,1202.4,4.019
science in the past and data science,1204.919,4.441
today is that pivot from quantitative,1206.419,5.76
data numbers forecast linear regression,1209.36,5.04
that sort of thing to qualitative,1212.179,4.201
information what is it that this person,1214.4,4.019
likes and why and how do you earn their,1216.38,4.5
trust and finally question number four,1218.419,4.861
what activities are the highest priority,1220.88,5.34
or highest stakes in other words where,1223.28,4.8
would having an extra brain or an extra,1226.22,4.26
set of eyes make the most difference,1228.08,5.64
so this is something where uh often if,1230.48,4.439
something is high priority or high,1233.72,3.42
stakes that is where that's like the,1234.919,4.201
sweet spot right that is that is the,1237.14,3.18
meat and potatoes of your business,1239.12,3.66
because that is the that is the set of,1240.32,5.099
tasks that only humans can do right now,1242.78,5.1
and they are they're going to be the,1245.419,4.62
bottleneck right so what I mean by that,1247.88,4.38
is uh I used to work at managed service,1250.039,5.401
providers and so you know one of the,1252.26,6.18
biggest things was uptime if the if the,1255.44,5.099
data center goes down or a service goes,1258.44,4.619
down that's money out the door so that,1260.539,4.26
means that's a very high priority task,1263.059,4.021
and so if I were Consulting for a,1264.799,3.601
managed service provider and they said,1267.08,3.54
Dave how can we use generative AI to,1268.4,3.84
help our bottom line I said what are the,1270.62,3.72
what are the biggest uh priorities that,1272.24,4.2
you have and it's like well if we have a,1274.34,4.44
severity one let's you know we need to,1276.44,5.04
all hands on deck and one thing this is,1278.78,4.139
just from my experience in technology,1281.48,3.24
one thing is that a lot of people are,1282.919,3.241
very reactive,1284.72,3.42
I actually had to leave a job because my,1286.16,4.259
boss did not understand the value of,1288.14,4.5
eliminating technical debt and so he's,1290.419,4.441
just like oh well we have fire alarms on,1292.64,4.019
a daily basis and that's just the way,1294.86,3.179
things are and I said no the hell it,1296.659,3.661
isn't like prevention is what we should,1298.039,4.441
be doing right if if your fire,1300.32,3.66
department is over taxed because,1302.48,3.48
everything is burning down maybe you,1303.98,4.199
need new fire code he didn't get that so,1305.96,4.98
I left that job but my point is is that,1308.179,5.041
there there are going to be key risks,1310.94,4.8
and key business activities that are,1313.22,4.86
responsible for a good chunk of the,1315.74,4.26
money coming in and the money going out,1318.08,3.599
so that's what I mean by high priority,1320.0,3.84
and high stakes you pay attention to,1321.679,3.961
those things first and you fix them as,1323.84,4.98
much as you can by adding generative AI,1325.64,6.0
uh to make you know to to change those,1328.82,4.44
ratios so they got more coming in and,1331.64,4.68
less going out uh you know you can ask,1333.26,5.88
and as a CEO you can ask these questions,1336.32,5.46
of every department head you can also,1339.14,4.32
look at it from an internal perspective,1341.78,3.66
or an external perspective how do you,1343.46,3.719
engage with your customer your vendors,1345.44,3.96
your clients how do you engage with your,1347.179,3.901
internal stakeholders how do you engage,1349.4,3.659
with your uh your financial stakeholders,1351.08,3.3
your shareholders,1353.059,4.681
these are you can generative AI can,1354.38,4.799
apply to literally every level of,1357.74,2.88
business,1359.179,4.38
okay so on the tool side so we talked,1360.62,4.679
about the people in the processes let's,1363.559,3.24
talk about the tools,1365.299,4.86
uh first one thing that you can do the,1366.799,5.041
best one of the approaches is that you,1370.159,4.741
can create drop-in tools so one thing is,1371.84,4.8
that a lot of people get wrong is,1374.9,3.24
they're trying is they try and build,1376.64,3.6
tools that require a fundamentally,1378.14,3.779
different workflow and it's a,1380.24,2.88
fundamentally different approach to,1381.919,3.841
business and I this is something that I,1383.12,4.799
often talk about with uh for startups,1385.76,3.84
where they're like oh we've got this,1387.919,3.301
great new tool that we're building it's,1389.6,3.48
you know based on generative Ai and I'm,1391.22,4.02
like okay great but how are businesses,1393.08,4.92
going to use it is this gonna is is this,1395.24,5.4
gonna require them to adopt an entirely,1398.0,4.86
new workflow is it going to replace,1400.64,5.94
existing tools or ideally it's a drop-in,1402.86,5.76
tool that just goes in alongside every,1406.58,4.26
other tool in their toolbox so for,1408.62,3.419
instance in the marketing department,1410.84,3.54
they already use file servers they,1412.039,5.161
already use Photoshop they use Adobe and,1414.38,5.159
and image services,1417.2,4.92
stock image services so in that case,1419.539,4.5
image generators like stable diffusion,1422.12,3.98
and mid-journey and adobe's Firefly,1424.039,5.221
these are all drop-in tools where they,1426.1,4.959
fit into the existing workflows,1429.26,4.44
perfectly and so when you're whether,1431.059,4.62
you're looking at adopting a generative,1433.7,4.859
AI tool or service make sure that it,1435.679,5.701
will fit into your existing workflows,1438.559,4.081
because that's where you're going to get,1441.38,3.179
the most value out of it if it's a tool,1442.64,3.419
that requires a fundamentally different,1444.559,4.5
approach the the path to adoption is,1446.059,5.641
just that much harder and I you know I,1449.059,4.801
saw this on the back in my it,1451.7,4.38
infrastructure days all the time where,1453.86,3.42
it's like yeah there's a great new,1456.08,3.42
powerful tool but like we can't really,1457.28,3.84
use it because it doesn't integrate with,1459.5,3.419
anything else that we do and it's going,1461.12,3.36
to fundamentally change the way we do,1462.919,3.601
business which just means it's not a,1464.48,4.199
good fit and this is this is something,1466.52,4.92
for startup CEOs to keep in mind it's,1468.679,5.521
also something for CEOs that are not,1471.44,6.119
Tech Centric or AI Centric when adopting,1474.2,4.8
AI tools,1477.559,3.181
make sure that you make sure that you,1479.0,4.32
get those drop-in tools one another,1480.74,3.9
thing to keep in mind is that general,1483.32,3.3
purpose tools like chat GPT are often,1484.64,4.26
the hardest to use because you have to,1486.62,4.02
know a lot about the tool you have to,1488.9,3.36
know a lot about what it is that you're,1490.64,3.06
trying to do and you have to interact,1492.26,2.94
with it in a very fundamentally,1493.7,2.64
different way than you've ever,1495.2,4.14
interacted with any uh technology tool,1496.34,4.199
in the past,1499.34,4.199
so because of that part of what makes a,1500.539,5.041
a drop-in tool is going to be the,1503.539,4.02
affordances and user experience design,1505.58,4.56
that says oh this is just like this,1507.559,4.62
other piece of software that I use this,1510.14,4.14
other app that I use all the time it,1512.179,4.5
just has some AI baked into it and it's,1514.28,4.2
really easy to use this is one of the,1516.679,4.201
things that I consulted with in the,1518.48,3.48
early days,1520.88,2.52
was there was a lot of people just,1521.96,4.14
putting together generic dashboards of,1523.4,4.62
AI tools and I'm like you have no,1526.1,4.86
coherent strategy there's nothing about,1528.02,5.399
this that just stands out and says Ah I,1530.96,5.099
know exactly what this tool is for and,1533.419,5.221
you know so basically what you're trying,1536.059,4.441
to optimize for is make your generative,1538.64,4.32
AI tool as intuitive as possible where,1540.5,3.9
you can just pick someone off the street,1542.96,3.42
put them in front of the app and they,1544.4,5.159
say oh I know I one I know exactly what,1546.38,4.74
this does and I know exactly how to use,1549.559,4.5
it just by guessing if you can if you,1551.12,4.86
can do that then you uh almost certainly,1554.059,3.901
have a drop in tool,1555.98,3.9
now the other thing that you can do is,1557.96,4.56
you can improve existing systems so this,1559.88,4.679
could be you know if you've got teams if,1562.52,3.72
you've got slack if you've got exchange,1564.559,4.561
you know or or even log services or,1566.24,4.439
whatever and of course that's just all,1569.12,4.2
looking at it from the I.T side there's,1570.679,4.521
plenty of other business platforms,1573.32,4.38
whether it's your financial workflows,1575.2,4.5
your marketing workflows,1577.7,5.16
whether if you if you if you're not,1579.7,5.32
trying to add a new tool what you can do,1582.86,5.28
is if you have access to the code base,1585.02,4.98
uh for you know your internally,1588.14,4.8
developed tools you can add generative,1590.0,6.419
AI uh for at some of these uh decision,1592.94,5.94
points in order to make it just a little,1596.419,4.74
bit better a little bit faster so the,1598.88,3.779
primary example I have in my head is,1601.159,3.481
servicenow and other,1602.659,3.781
um internal management things like that,1604.64,4.5
so let's say you have ticket routing,1606.44,5.16
you've got uh follow-ups you've got,1609.14,4.86
emails so basically like you know,1611.6,5.4
instead of having uh humans do a lot of,1614.0,5.159
the work you can have the machine do a,1617.0,3.539
lot of the work for the humans and to,1619.159,3.421
say hey which one of these emails do you,1620.539,4.26
want to send to this customer as a,1622.58,5.28
follow-up uh or if there's a if there's,1624.799,4.98
a ticketing system you can have the,1627.86,4.26
ticketing system ask a few obvious,1629.779,4.26
questions before a human even looks at,1632.12,4.2
it so that there's by the time your,1634.039,3.901
ticket gets escalated to an actual,1636.32,4.5
engineer or whoever it gets to a few,1637.94,4.2
questions have already been asked,1640.82,3.42
immediately and so there's more context,1642.14,5.279
which can reduce your mttx,1644.24,5.34
another place that you can look at it is,1647.419,5.76
human intervention where in uh and it,1649.58,5.04
can either be routing to the correct,1653.179,2.821
human so I was actually just talking to,1654.62,3.48
a friend about this on the medical side,1656.0,4.2
uh who's at a startup trying to use,1658.1,4.559
generative AI which is uh if there's a,1660.2,4.32
if there's a patient need how do you,1662.659,3.661
write it to the route it to the correct,1664.52,4.38
medical provider that is a that is a,1666.32,4.2
great use case because you can feed a,1668.9,4.62
whole patient chart into the llm and say,1670.52,5.039
what what exactly competency what,1673.52,3.84
competencies does this person need right,1675.559,2.761
now,1677.36,2.34
um and then you get the you get the,1678.32,2.82
exact right thing and then you make sure,1679.7,4.14
that uh that that uh you know nurse or,1681.14,5.519
or specialist also gets the exact notes,1683.84,5.219
that they need uh without having to go,1686.659,4.14
talk to a you know a bunch of other,1689.059,4.321
people because I mean heck one of my one,1690.799,4.321
of my patreons several of my patreon,1693.38,3.6
supporters are in the medical field and,1695.12,3.48
they talk about just how annoying it is,1696.98,3.72
when charts aren't updated correctly and,1698.6,4.559
when uh Physicians and nurses don't talk,1700.7,4.2
to each other or they you know forget to,1703.159,4.26
pass something on so again you can,1704.9,5.58
reduce human interaction uh or sorry you,1707.419,4.14
can reduce the need for human,1710.48,3.12
intervention by having some of these,1711.559,3.901
interactions automated,1713.6,4.38
and then finally cognitive offload if,1715.46,4.079
you if you go hunting across your,1717.98,2.939
organization for the things that are,1719.539,3.781
really demanding those are ways that you,1720.919,4.38
can improve existing systems because you,1723.32,4.02
know you reduce the frustration that,1725.299,3.661
will increase productivity increase,1727.34,3.9
satisfaction and that also just all,1728.96,4.26
speaks to the bottom line,1731.24,4.5
okay so that was people processes and,1733.22,4.74
tools let's talk about better faster and,1735.74,4.919
cheaper otherwise uh how do you get the,1737.96,4.319
best return on investment from any,1740.659,3.361
generative AI initiative whether it's a,1742.279,2.941
product or service that you're thinking,1744.02,2.759
about adopting or one that you're,1745.22,3.54
building uh internally,1746.779,4.801
so the the primary three questions here,1748.76,5.34
that you should ask yourself is uh what,1751.58,4.44
can generative AI do better than humans,1754.1,4.14
what can it do faster than humans and,1756.02,4.32
what can it do cheaper than humans and,1758.24,3.419
so this is what I mean where it's like,1760.34,3.719
okay if you can offset some of the labor,1761.659,5.821
costs uh you can ideally hopefully you,1764.059,5.401
preserve your existing head count but,1767.48,3.6
you take your organization to the next,1769.46,3.48
level and you can double triple,1771.08,4.62
quadruple productivity while also doing,1772.94,4.859
cognitive offload so your your human,1775.7,4.74
employees are happier,1777.799,4.98
so this is a universal truth of,1780.44,4.8
technology technology has always been a,1782.779,5.4
force multiplier so you know the the,1785.24,5.22
Industrial Revolution example that I,1788.179,3.961
always love to give is the tractor,1790.46,3.54
tractors are very complicated they're,1792.14,4.019
expensive heavy pieces of equipment but,1794.0,4.32
we still use them because they have the,1796.159,4.62
physical power output of literally,1798.32,5.459
hundreds of horses uh and so you get rid,1800.779,4.681
of the you instead of feeding and,1803.779,3.78
providing veterinary care for hundreds,1805.46,4.14
of horses you have a tractor that all it,1807.559,4.201
does is drink gasoline need some oil and,1809.6,3.54
some replacement parts every now and,1811.76,2.22
then,1813.14,3.96
generative AI is a cognitive Force,1813.98,5.52
multiplier so let me say that again the,1817.1,4.26
the first industrial or the first three,1819.5,4.399
industrial revolutions were more about,1821.36,5.28
uh communication Force multiplication,1823.899,5.461
and physical Force multiplication,1826.64,6.24
generative AI is the first example of a,1829.36,5.679
cognitive Force multiplier it doesn't,1832.88,4.14
just send email faster right because you,1835.039,3.721
know email came around in the 80s or,1837.02,3.48
whatever which is like okay cool,1838.76,3.899
communication now happens faster that's,1840.5,5.34
not really cognitive labor or crunching,1842.659,5.281
numbers right math definitely very,1845.84,4.38
cognitively demanding but this is a new,1847.94,4.56
era of of cognitive labor force,1850.22,5.699
multiplication so that's why this video,1852.5,5.88
has cognitive offload as a central,1855.919,4.86
lesson as something to look for when,1858.38,4.26
you're trying to integrate generative AI,1860.779,3.841
into your business,1862.64,2.94
better,1864.62,4.88
so uh keep your ear to the ground but,1865.58,7.02
you know basically chat GPT has already,1869.5,5.5
demonstrated Superior uh clinical,1872.6,4.38
judgment than many doctors and this is,1875.0,4.5
according to Harvard research it also,1876.98,4.559
has better uh executive judgment,1879.5,4.98
executive reasoning uh than many people,1881.539,5.301
and this includes managers and some CEOs,1884.48,5.22
and so in this case look for the,1886.84,4.66
activities where generative AI is,1889.7,5.28
demonstrably superior to humans this,1891.5,4.919
will give you obviously a competitive,1894.98,3.12
Advantage but if it is better than you,1896.419,4.86
use the machine right humans can go use,1898.1,5.28
a rake and a hoe and and and and and,1901.279,4.921
plow uh the field but we don't have,1903.38,4.5
humans doing it by hand anymore because,1906.2,3.599
the machine is better so just because,1907.88,3.6
you can do something doesn't mean that,1909.799,3.781
you should especially if the machine is,1911.48,4.02
better than you at it now again this,1913.58,4.56
doesn't necessarily mean get handed over,1915.5,4.98
to the machine entirely but you should,1918.14,4.38
be using the machine to augment your,1920.48,5.1
abilities so in the case of doctors if,1922.52,6.18
there is any room for doubt maybe,1925.58,5.219
doctors should be required or maybe not,1928.7,5.099
required but you know as part of the the,1930.799,4.801
medical resourcing system like you know,1933.799,3.541
epic and Cerner and stuff,1935.6,3.72
you integrate some uh some language,1937.34,3.66
model technology into that where it's,1939.32,3.78
like okay cool uh based on this,1941.0,4.08
patient's chart and test results have,1943.1,4.38
you thought of X Y and Z uh just enough,1945.08,4.14
just enough to clue in that the,1947.48,3.54
physician on the direction that maybe,1949.22,4.199
they need to go in order to augment,1951.02,4.379
human judgment and augment human,1953.419,4.62
executive reasoning now one thing about,1955.399,6.481
this is that unless you have a you know,1958.039,5.701
a product or service where they've done,1961.88,4.5
the work and they can say look this this,1963.74,4.62
AI service that we've built is,1966.38,4.26
demonstrably better than humans you're,1968.36,3.48
going to need to figure that out for,1970.64,2.639
yourself through experimentation and,1971.84,3.3
consultation,1973.279,2.581
um,1975.14,3.0
and also as I mentioned earlier you will,1975.86,3.6
need to start measuring some things,1978.14,3.539
qualitatively rather than quantitatively,1979.46,5.76
so if if the objective is patient,1981.679,6.061
satisfaction or customer satisfaction or,1985.22,4.559
trust or any number of those other,1987.74,4.08
intangible things they can be a lot,1989.779,4.14
harder to measure but fortunately,1991.82,4.5
language models can help you measure,1993.919,5.461
those things through approximations,1996.32,4.8
and so what I mean by that is just ask,1999.38,3.24
chat GPT,2001.12,2.939
um you know how can I measure customer,2002.62,3.779
satisfaction or trust or whatever and,2004.059,3.901
it'll give you some cool ideas about how,2006.399,3.481
you can measure that and then you say,2007.96,2.939
well what's the difference between,2009.88,3.179
quantitative and qualitative trust me if,2010.899,3.481
you do that experiment you'll see what,2013.059,2.401
I'm talking about,2014.38,3.539
uh but again this is no different from,2015.46,4.559
using machines to do things that humans,2017.919,5.1
either couldn't or shouldn't do uh you,2020.019,5.64
know a forklift right yes a human could,2023.019,4.681
you know unpack a pallet and put,2025.659,3.601
everything in the you know on a new,2027.7,2.88
palette in the truck but it's easier to,2029.26,3.12
just use the forklift to pick up the,2030.58,3.54
pallet as a whole and put it in the,2032.38,4.08
truck for you likewise there's going to,2034.12,4.439
be some things that generative AI it can,2036.46,4.079
just do that a human can't,2038.559,3.661
um or that would take a human way too,2040.539,4.14
long to do so just offload those things,2042.22,4.14
and let the machine do it because it's,2044.679,3.66
already better than the human,2046.36,6.72
faster so generative AI is super super,2048.339,8.701
fast it can read literally like 20 pages,2053.08,6.779
of text in a few seconds no human is,2057.04,5.52
capable of that and then it can use that,2059.859,4.081
text it can either summarize it,2062.56,4.02
brainstorm extend it it can draft a new,2063.94,4.919
version all of this happens really,2066.58,3.839
really fast and of course time is money,2068.859,4.32
right velocity is speed plus Direction,2070.419,4.2
so you got to make sure you're going in,2073.179,4.2
the right direction but basically so,2074.619,4.141
this is another thing that I do when I'm,2077.379,4.081
Consulting is I say what takes the,2078.76,5.28
longest you know so when I consult with,2081.46,4.679
scientists and academics it's like oh,2084.04,5.16
well you know writing grants is takes,2086.139,4.5
forever,2089.2,3.179
um you know Grant proposals Grant,2090.639,4.921
reviews that takes forever or writing,2092.379,4.98
research papers and revising research,2095.56,3.84
papers takes a long time,2097.359,4.98
whatever business activities take the,2099.4,6.06
longest those might be good targets uh,2102.339,5.641
for generative AI uh not related to,2105.46,4.639
generative AI but many many years ago,2107.98,5.52
earlier in my it infrastructure days I,2110.099,5.201
was working at a small uh medical,2113.5,5.28
startup medical software startup and I I,2115.3,5.34
we got a couple new servers and I added,2118.78,3.42
these new servers to their build Network,2120.64,4.5
and so then their software builds took,2122.2,5.639
went from 26 hours to two and they said,2125.14,4.5
well Dave you threw off our entire,2127.839,4.141
workflow because instead of kicking off,2129.64,3.9
a build and then just coming back the,2131.98,3.48
next day we just go to lunch and come,2133.54,4.039
back and now we have to keep working,2135.46,5.22
but again if you can I mean and,2137.579,4.721
Technology can do this you can shorten,2140.68,4.439
things by a factor of 10x or 100x I,2142.3,4.319
usually look at the things that can,2145.119,4.201
happen that we can shorten by 100x say,2146.619,4.861
okay what takes the longest here,2149.32,4.56
we've got some lawyer friends right the,2151.48,3.72
you know there's there's a bunch of,2153.88,2.699
active lawsuits out there and I said,2155.2,4.5
okay given that we have generative AI,2156.579,5.161
that can read and summarize you know,2159.7,4.56
hundreds of pages of legal documents,2161.74,5.339
really fast how can I build a tool that,2164.26,4.92
is going to really help you get to the,2167.079,4.561
bottom of these things really quick uh,2169.18,5.22
so again looking looking at ways that,2171.64,5.34
generative AI can speed up really basic,2174.4,5.04
stuff just reading right don't,2176.98,4.619
underestimate the power of speeding up,2179.44,4.08
really basic tasks,2181.599,5.281
uh so another example is that I have I,2183.52,6.12
I've built my own tools that I use for,2186.88,5.58
uh for helping revise my writing,2189.64,4.92
um Chad GPT still sucks at writing by,2192.46,3.24
the way,2194.56,2.94
um but so I don't use it for writing I,2195.7,3.84
use it for revisions and providing,2197.5,3.3
feedback because that's something that,2199.54,2.88
is really good at it says Hey I just,2200.8,3.24
read this whole chapter let me give you,2202.42,3.419
some feedback on it and it gives really,2204.04,3.36
good feedback,2205.839,3.121
I know because I've paid a professional,2207.4,4.38
editor and it gives me uh feedback at a,2208.96,4.8
very similar level as a professional,2211.78,4.319
editor now that being said it does miss,2213.76,4.92
a lot of stuff but instead of a two,2216.099,4.921
month turnaround I get a 30 minute,2218.68,4.62
turnaround so that's what I mean by look,2221.02,3.96
for things that you can accelerate by a,2223.3,4.68
factor of 10x or 100x so let's see going,2224.98,5.54
from two months or 60 days to 30 minutes,2227.98,6.599
that's you know 60x and then instead of,2230.52,6.4
hours it's minutes like so I mean you're,2234.579,6.121
looking at a 200x speed up by using chat,2236.92,7.86
GPT API for getting uh feedback rather,2240.7,7.32
than using a human so again like you,2244.78,5.819
know those that level of speed up is,2248.02,4.5
absolutely possible with generative AI,2250.599,3.541
look for those and you're going to,2252.52,3.78
really make a a very good difference in,2254.14,3.78
some departments,2256.3,4.5
and then finally cheaper uh here's the,2257.92,6.3
thing is that a lot of stuff costs a lot,2260.8,5.4
and human labor is one of the most,2264.22,5.46
expensive parts of of uh many businesses,2266.2,6.06
and the best expense is no expense so,2269.68,5.399
what I mean by that is unfortunately we,2272.26,4.62
are seeing where like many many,2275.079,4.141
companies are doing huge huge layoffs as,2276.88,4.199
they pivot and I don't know if those,2279.22,3.48
jobs are ever coming back but that kind,2281.079,3.181
of goes outside of the scope of this,2282.7,3.419
video but,2284.26,4.02
what I mean by that is that if there is,2286.119,4.561
something that you can do cheaper with,2288.28,6.12
AI than paying a human or you can,2290.68,5.82
Empower a human to do some to do the,2294.4,4.5
same task faster and therefore cheaper,2296.5,4.68
that is kind of the direction to look at,2298.9,4.62
so where can you lower costs with,2301.18,4.38
generative AI this one is actually a lot,2303.52,3.42
harder to do,2305.56,4.86
because uh again it's it's better at,2306.94,5.1
some things and it's certainly faster at,2310.42,3.54
some things uh but you still need human,2312.04,4.02
oversight you still need human uh you,2313.96,4.26
know guess and check or whatever uh you,2316.06,5.039
need experts supervising these systems,2318.22,5.04
um but with that being said there are,2321.099,3.961
ways that you can probably lower costs,2323.26,4.68
because again chat gbt has a 20 a month,2325.06,4.92
assistant it can do the work of,2327.94,3.78
literally like thousands of dollars,2329.98,3.84
worth of cognitive labor for you per,2331.72,3.06
month,2333.82,2.34
um so that you don't need to hire like a,2334.78,2.94
research assistant or that sort of thing,2336.16,3.54
which then frees up the you know,2337.72,4.92
cognitive labor of other humans but,2339.7,5.399
again look at where it's cheaper uh,2342.64,4.439
generative AI in the form of image,2345.099,3.841
generators much much cheaper than,2347.079,3.361
graphic artists which is really really,2348.94,3.419
unfortunate for the graphics artists out,2350.44,3.72
there and I don't have a solution but,2352.359,3.961
from a business perspective this says,2354.16,4.56
like okay hey we can get a lot more art,2356.32,5.759
done uh much faster and much cheaper uh,2358.72,5.34
than than with the humans you still,2362.079,3.661
often need humans to do touch-ups and,2364.06,3.36
and that sort of thing and to even Drive,2365.74,4.379
the machines but again much cheaper,2367.42,4.199
because it is faster,2370.119,4.74
you can also use it to do a SWOT,2371.619,4.98
analyzes and that sort of thing again,2374.859,2.961
that goes back to the cognitive,2376.599,3.841
reasoning where you can use generative,2377.82,5.08
AI to help look at and control those,2380.44,4.44
outflows,2382.9,4.92
and then so this is uh we're closing in,2384.88,5.28
on the end of the video one thing that I,2387.82,3.66
really want to point out particularly,2390.16,3.6
for the for the managers middle managers,2391.48,5.28
and the executives watching is that you,2393.76,4.98
need to be using generative AI to,2396.76,3.839
augment yourself,2398.74,3.839
um whether this is using tools like chat,2400.599,4.321
GPT to develop your sense of empathy and,2402.579,6.0
to be more diplomatic uh to even be more,2404.92,5.699
vulnerable to learn to be more,2408.579,4.861
vulnerable with your customers your,2410.619,5.521
employees uh your star players that sort,2413.44,5.58
of thing you use that and you will,2416.14,5.219
develop better relationships and and,2419.02,4.86
you'll develop more trust and have a lot,2421.359,5.041
more of that intangible benefit of,2423.88,5.76
working with your employees and but,2426.4,5.219
employees inside the company and then,2429.64,3.38
customers outside the company,2431.619,4.98
introspection so this is one of the most,2433.02,6.52
unsung things that all leaders need to,2436.599,6.781
do is using these tools whether it's,2439.54,5.88
chat GPT or the reflective journaling,2443.38,4.52
tool that I built or anything else,2445.42,5.04
understanding how your own mind works,2447.9,5.14
and What Makes You tick is absolutely,2450.46,4.92
critical to being a good leader because,2453.04,3.78
if you're doing things for the wrong,2455.38,3.479
reason you need to be aware of that so,2456.82,3.36
that you can fix that and make sure that,2458.859,2.901
you're doing things for the right reason,2460.18,3.6
introspection and the way that,2461.76,4.359
generative AI can help with that is,2463.78,4.799
really really good and then finally,2466.119,4.5
smarter if you're not using generative,2468.579,4.861
AI to learn more faster to make sure,2470.619,4.801
that you have good understanding you,2473.44,4.98
will be left behind and so this is,2475.42,4.86
something like I know I'm saying that,2478.42,3.9
like really bluntly but the fact of the,2480.28,3.78
matter is if you're not using generative,2482.32,3.539
AI to make yourself smarter to make,2484.06,4.86
smarter decisions your competition is so,2485.859,5.041
it's that simple,2488.92,4.8
and then lastly ethics and courage,2490.9,4.679
I've mentioned a few times during this,2493.72,3.66
video that in some cases I think,2495.579,4.201
generative AI will inevitably lead to,2497.38,5.3
layoffs job loss and that sort of thing,2499.78,5.16
uh there's going to be really tough,2502.68,5.62
decisions ahead for a lot of people and,2504.94,6.899
the competition May undercut you and you,2508.3,5.0
might feel like you have to compromise,2511.839,4.081
your principles and your values in order,2513.3,5.74
to stay competitive the thing is it's a,2515.92,5.159
foregone conclusion that technology will,2519.04,3.9
will disrupt markets do you remember,2521.079,4.141
borders borders imploded because of,2522.94,4.38
Amazon that's just the name of the game,2525.22,4.5
so if you need to close the doors and,2527.32,4.259
pivot maybe that's what you need to do,2529.72,3.96
and it really sucks because nobody wants,2531.579,3.601
to go out of business nobody wants to,2533.68,3.54
lay off you know hundreds or thousands,2535.18,4.02
of employees because you're going out of,2537.22,4.5
business that being said it's probably,2539.2,4.34
going to happen,2541.72,4.16
now even if you don't go out of business,2543.54,4.84
layoffs and pivots are coming they're,2545.88,4.239
actively happening,2548.38,2.88
um you know like you remember telephone,2550.119,3.361
operators telephone industry didn't go,2551.26,4.8
away telephone operators did and so,2553.48,4.26
going through these pivots is going to,2556.06,4.26
be very difficult and and very painful,2557.74,3.9
for some people,2560.32,3.36
so what I want to leave you with is this,2561.64,4.32
idea that there are three guiding,2563.68,4.14
principles that you should probably keep,2565.96,6.0
in mind as you Embrace generative Ai and,2567.82,7.259
that is Trust dignity and respect so,2571.96,5.22
first make decisions that prioritize,2575.079,5.101
earning and keeping trust once trust is,2577.18,4.86
lost it is very difficult to get back,2580.18,3.24
and if you look at some of the,2582.04,3.12
technology or tech companies out there,2583.42,4.679
that have abused the markets trust abuse,2585.16,4.38
their customer trust by violating,2588.099,4.201
privacy and that sort of stuff I gotta,2589.54,4.2
tell you like I'm never going back to,2592.3,2.819
those platforms I don't know I don't,2593.74,4.26
care what they do and so if you sell,2595.119,5.281
your trust if you if you sell your,2598.0,4.5
trustworthiness in the age of generative,2600.4,4.5
AI you will probably not be able to get,2602.5,5.04
that back because Above All Else a lot,2604.9,4.439
of people are are caring more and more,2607.54,4.319
about privacy and not being abused and,2609.339,5.461
manipulated uh by the corporations that,2611.859,4.98
we engage with if you watch my my,2614.8,3.539
channel you know that I am very very,2616.839,3.661
skeptical of corporations that being,2618.339,4.201
said I also understand that corporations,2620.5,4.14
are here for a reason and they provide,2622.54,5.4
uh critical goods and services to all of,2624.64,4.32
us,2627.94,4.02
so make sure that you put trust front,2628.96,4.92
and center with the way that you deploy,2631.96,4.32
and use uh generative Ai and the,2633.88,4.199
decisions that you make a strategic,2636.28,3.539
decisions you make around generative AI,2638.079,4.801
dignity so this is something that is one,2639.819,5.361
of those more intangible things which is,2642.88,4.62
you know how do you prioritize human,2645.18,4.419
dignity this means,2647.5,3.72
um this means treating people with,2649.599,4.02
respect respecting the Dignity of their,2651.22,5.16
time off respecting the Dignity of their,2653.619,5.46
competence Their Fear so this is another,2656.38,4.739
thing A lot of people are absolutely,2659.079,4.02
Paralyzed by fear because they don't,2661.119,5.101
know what's coming and as a CEO you,2663.099,4.381
might not know what's coming either but,2666.22,3.119
if you treat people with dignity and you,2667.48,3.48
say you know what I'm not going to,2669.339,4.081
compromise on this value then they're,2670.96,3.54
gonna like you more they're gonna,2673.42,2.699
they're gonna give you more of the,2674.5,3.66
benefit of the doubt and and trust you,2676.119,4.261
to see it through and then finally,2678.16,4.8
respect respect for human rights respect,2680.38,4.56
for privacy respect for the way that,2682.96,4.859
people feel if you prioritize respect as,2684.94,5.879
well as trust and dignity then you know,2687.819,5.101
even if your company implodes or even if,2690.819,4.081
you have to lay off people you're not,2692.92,4.14
gonna you're you're you won't regret it,2694.9,4.98
put it that way you will not ever regret,2697.06,5.64
prioritizing trust dignity and respect,2699.88,5.04
no matter what else happens,2702.7,6.84
and so with this my my caution to all,2704.92,7.08
Executives and leaders out there in the,2709.54,3.9
age of generative AI is do not,2712.0,3.78
compromise your ethics and principles,2713.44,5.04
but also be courageous and make some,2715.78,4.2
bold decisions because if you're not,2718.48,4.92
making bold decisions other people will,2719.98,5.879
so for a quick recap we talked about the,2723.4,3.84
people processes and Tools around,2725.859,4.5
generative AI this is you know,2727.24,4.98
generative AI is just like any other,2730.359,4.161
software it provides new capabilities,2732.22,5.119
new opportunities but also new threats,2734.52,4.78
one of the key ways to look at,2737.339,4.0
generative AI is look at where it's,2739.3,4.2
better faster and or cheaper than humans,2741.339,3.721
this is where you're going to get the,2743.5,2.94
most bang for your buck when you're,2745.06,3.539
either building your own generative AI,2746.44,4.62
tools or you're buying or procuring,2748.599,5.881
generative AI goods and services,2751.06,5.88
uh and then second to last with,2754.48,4.68
self-improvement as an executive leader,2756.94,4.379
if you're not using generative AI to,2759.16,5.04
improve yourself somebody else is namely,2761.319,4.321
your competition and you're gonna get,2764.2,3.899
left behind and then lastly the slide,2765.64,4.14
that we just did was ethics and courage,2768.099,4.441
which means whatever happens whatever's,2769.78,5.46
coming if you if you compromise your,2772.54,4.319
ethics you might regret it but if you,2775.24,3.06
don't compromise your ethics you will,2776.859,3.421
not regret it so choose the path of,2778.3,4.019
least regret this is um actually a,2780.28,4.38
mantra that I live by is what decision,2782.319,4.861
will I regret least in the long run and,2784.66,3.84
then be courageous about it because,2787.18,4.02
again this is a bold time with a,2788.5,4.92
tremendous amount of opportunity but uh,2791.2,4.32
you know fortune favors the Bold so,2793.42,4.14
thanks for watching I hope you got a lot,2795.52,4.26
out of this thank you very much and uh,2797.56,4.32
again reach out on LinkedIn or patreon,2799.78,3.66
and let's talk if you want to if you,2801.88,2.939
want to talk about any of these topics,2803.44,3.98
cheers,2804.819,2.601