AI Adoption Accelerates Faster Than Ever
Key Points
- A recent survey shows 44% of IT professionals already use AI in programming and another 34% are experimenting with it, highlighting rapid adoption within the tech sector.
- Even non‑technical users, like the speaker’s mother who relies on a generative‑AI chatbot for recipe ideas, illustrate how AI is becoming a commonplace personal tool.
- Historical examples—from cars (≈45‑year adoption) to digital computers (≈53 years), email (≈20 years), word processors (≈10 years), cell phones (≈20 years), the internet (≈10 years), and smartphones (≈14 years)—demonstrate that the pace of technology diffusion has been dramatically accelerating.
- Although AI’s foundations date back to the 1950s, recent advances in generative AI suggest it will soon become a critical, ubiquitous tool in both workplaces and everyday life, likely sooner than many expect.
Full Transcript
# AI Adoption Accelerates Faster Than Ever **Source:** [https://www.youtube.com/watch?v=c9LQUI3VMJ8](https://www.youtube.com/watch?v=c9LQUI3VMJ8) **Duration:** 00:08:37 ## Summary - A recent survey shows 44% of IT professionals already use AI in programming and another 34% are experimenting with it, highlighting rapid adoption within the tech sector. - Even non‑technical users, like the speaker’s mother who relies on a generative‑AI chatbot for recipe ideas, illustrate how AI is becoming a commonplace personal tool. - Historical examples—from cars (≈45‑year adoption) to digital computers (≈53 years), email (≈20 years), word processors (≈10 years), cell phones (≈20 years), the internet (≈10 years), and smartphones (≈14 years)—demonstrate that the pace of technology diffusion has been dramatically accelerating. - Although AI’s foundations date back to the 1950s, recent advances in generative AI suggest it will soon become a critical, ubiquitous tool in both workplaces and everyday life, likely sooner than many expect. ## Sections - [00:00:00](https://www.youtube.com/watch?v=c9LQUI3VMJ8&t=0s) **AI Adoption: From Niche to Ubiquitous** - The speaker cites statistics on IT professionals using AI, shares a personal example of a family member regularly using a chatbot for recipes, and draws parallels between AI’s path to ubiquity and the historical adoption cycles of technologies such as cars and digital computers. ## Full Transcript
I saw a stat recently that surprised me
and also didn't really surprise me at
all and that is that
44% of it professionals already use AI
in their programming and another
34% are experimenting with it well okay
yeah it professionals sure but but what
about non Tey folks it's going to be a
while before everybody will start using
AI I uh right well you you might be
surprised after all I can just look at
my own family now my mom her favorite
generative AI chatbot goes by the name
of Tim and she chats to it about recipe
ideas Tim he came up with a mean baked
enchilada recipe I can tell you now the
bigger point we're making here is when
we ask this type of question is when has
the technology reached a ubiquity that
but means even those less likely to be
at the Leading Edge of adoption will
view it as an important tool so let's
start with some perspective and history
is a great wide-angle lens maybe it
helps to look at some technologies of
the past and they span from invention to
adoption to being every place and
particularly critical in the workplace
and I've chosen this list because of all
of these things are still used daily in
many workplaces right so let's begin and
we'll start with the car now that was
invented in 1886 it was the Ben's patent
motor car and was popular by the 1920s
or 30s so that's an adoption cycle of
around
45 years all right what's next the
digital computer that was invented in
1937 wide adoption in the office by the
1980s so we can say
53
years the first email that was sent in
1971 by Ray Tomlinson he doesn't
actually remember what it said it was
something like quiry UOP the top row on
of keys on a keyboard but wider adoption
was in the 80s or '90s so we can say
there the adoption cycle was something
like 20 years now word processing that
was invented in 1970 became popularized
in the mid 80s so we can say 10 years
for that the first cell phone was
invented in 1973 and they became widely
used in the mid90s so that's roughly 20
years the internet birth year is
considered
1983 that's aranet and it was
popularized by the mid to early '90s so
around 10 years later oh and the very
first internet connected smartphone many
are surprised that it was invented by
IBM in
1992 the Simon smartphones became
popularized in about 2006 so we can say
that's 14 years so with some quick
calculations on my calculator uh
invented in the 1960s but popularized in
the' 70s it's pretty easy to see and
feel that the cycle of adoption of new
technology in the workplace is rapidly
speeding up so will AI be critical to
your job and your everyday life yes and
really maybe sooner than some might
expect it's probably not even fair to
say that AI is particularly new either
AI properly got its start in the mid
1950s with Alan Ching's work on machine
intelligence but it's been a dependent
technology on a lot of other Innovations
we've already focused on for it to
achieve its potential that we've
recently seen through things like
generative AI but the point for you to
remember is that all of these
Technologies they started in a smaller
technology tribe before its common use
in work so AI will likely be prolific in
work in a very similar way now while a
majority of programmers here are already
writing code today with ai ai just like
computers and word processing and
smartphones will be considered essential
to your everyday work
productivity now there are primarily
three things that speed up the
technology adoption curves let's have a
think about what some of those are and
one of those is the
ease of access to that
technology so that's number one now do
we need a special device that's one of
the considerations do others also have
to have the device for it to provide
value well for AI That's yes you do need
a special device but it's just your
smartphone or your laptop so we have
that covered but there's also the ease
of access to data our workplaces will
have to make sure that AI models ingest
quality data to get the output within
the right parameters so access to
devices easy access to Quality data to
tray models
essential another thing that speeds the
curve is
ease of
use now we have to consider things like
does the user know how to access a
technology and do they know how to use
it do people need to be trained to use
it now as we've seen with my mom we've
seen the barrier of use dramatically
decrease as more people engage with
large language models through
chatbots but there will be field-based
training for AI to be used as a tool in
education in healthcare in field
research as the AI models and data that
enable the best work in these fields
will be different and it will be
important for us to understand the
basics of how AI works so we can prompt
it in ways that maximize value of its
output all right so that's the first two
what is the third important technology
adoption curve well I think we can
consider that one as
Precision does it need a certain tool to
work does it do the job well look
calculators calculators would not been
very popular if they hallucinated the
wrong answer 20% of the time and this is
where AI has grown substantially
recently but hallucinations with large
language models do remain an ongoing
area of focus but the good news is that
as we engage more with these AO models
it helps to train it so we can all play
a role in making AI better just by
working with it now ai is already used
substantially for customer service for
human resources and for managing
candidate hires and for lots of other
important work tasks and it's coming to
a workplace near you so what can you do
to learn and get better well I would
offer three points number one is Don't
Be Afraid get started at the start of
each one of these technology curves here
we've talked about they were they were
doubters and they were slow adopters
Horseless carriages they'll never catch
on number two play as with learning any
tool or technology it helps to try it
when you're not under work pressure and
when you have time to make mistakes it's
also a huge amount of fun and as we've
already established potentially quite
tasty as well and then number three
consider more structured learning and
the good news here is that we have an
option for you to consider today
designed for new explorers who want to
build their skills on AI just go to
skills build.org there are no costs and
it's there to help people learn about AI
so get yourself ready for the workplace
of the future a workplace where it's if
it's not already essential AI will soon
be common place oh and just just one
more invention the electric elevator was
invented in 1880 and that was widely
adopted 20 years
later if you have any questions please
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