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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
0:00I saw a stat recently that surprised me 0:03and also didn't really surprise me at 0:05all and that is that 0:0844% of it professionals already use AI 0:12in their programming and another 0:1734% are experimenting with it well okay 0:21yeah it professionals sure but but what 0:24about non Tey folks it's going to be a 0:27while before everybody will start using 0:29AI I uh right well you you might be 0:34surprised after all I can just look at 0:36my own family now my mom her favorite 0:40generative AI chatbot goes by the name 0:42of Tim and she chats to it about recipe 0:46ideas Tim he came up with a mean baked 0:50enchilada recipe I can tell you now the 0:53bigger point we're making here is when 0:54we ask this type of question is when has 0:57the technology reached a ubiquity that 0:59but means even those less likely to be 1:02at the Leading Edge of adoption will 1:04view it as an important tool so let's 1:07start with some perspective and history 1:09is a great wide-angle lens maybe it 1:11helps to look at some technologies of 1:13the past and they span from invention to 1:17adoption to being every place and 1:20particularly critical in the workplace 1:22and I've chosen this list because of all 1:24of these things are still used daily in 1:26many workplaces right so let's begin and 1:30we'll start with the car now that was 1:31invented in 1886 it was the Ben's patent 1:35motor car and was popular by the 1920s 1:39or 30s so that's an adoption cycle of 1:42around 1:4445 years all right what's next the 1:47digital computer that was invented in 1:491937 wide adoption in the office by the 1:531980s so we can say 1:5653 1:57years the first email that was sent in 2:001971 by Ray Tomlinson he doesn't 2:04actually remember what it said it was 2:06something like quiry UOP the top row on 2:09of keys on a keyboard but wider adoption 2:12was in the 80s or '90s so we can say 2:14there the adoption cycle was something 2:16like 20 years now word processing that 2:19was invented in 1970 became popularized 2:22in the mid 80s so we can say 10 years 2:26for that the first cell phone was 2:29invented in 1973 and they became widely 2:31used in the mid90s so that's roughly 20 2:35years the internet birth year is 2:38considered 2:401983 that's aranet and it was 2:42popularized by the mid to early '90s so 2:46around 10 years later oh and the very 2:51first internet connected smartphone many 2:54are surprised that it was invented by 2:55IBM in 2:571992 the Simon smartphones became 3:00popularized in about 2006 so we can say 3:04that's 14 years so with some quick 3:08calculations on my calculator uh 3:10invented in the 1960s but popularized in 3:12the' 70s it's pretty easy to see and 3:16feel that the cycle of adoption of new 3:18technology in the workplace is rapidly 3:21speeding up so will AI be critical to 3:25your job and your everyday life yes and 3:29really maybe sooner than some might 3:32expect it's probably not even fair to 3:35say that AI is particularly new either 3:37AI properly got its start in the mid 3:391950s with Alan Ching's work on machine 3:42intelligence but it's been a dependent 3:44technology on a lot of other Innovations 3:47we've already focused on for it to 3:49achieve its potential that we've 3:51recently seen through things like 3:53generative AI but the point for you to 3:56remember is that all of these 3:57Technologies they started in a smaller 4:00technology tribe before its common use 4:03in work so AI will likely be prolific in 4:06work in a very similar way now while a 4:10majority of programmers here are already 4:12writing code today with ai ai just like 4:16computers and word processing and 4:18smartphones will be considered essential 4:21to your everyday work 4:23productivity now there are primarily 4:26three things that speed up the 4:28technology adoption curves let's have a 4:31think about what some of those are and 4:33one of those is the 4:36ease of access to that 4:40technology so that's number one now do 4:45we need a special device that's one of 4:47the considerations do others also have 4:49to have the device for it to provide 4:51value well for AI That's yes you do need 4:54a special device but it's just your 4:56smartphone or your laptop so we have 4:58that covered but there's also the ease 5:00of access to data our workplaces will 5:03have to make sure that AI models ingest 5:05quality data to get the output within 5:08the right parameters so access to 5:10devices easy access to Quality data to 5:12tray models 5:14essential another thing that speeds the 5:17curve is 5:19ease of 5:23use now we have to consider things like 5:26does the user know how to access a 5:28technology and do they know how to use 5:30it do people need to be trained to use 5:32it now as we've seen with my mom we've 5:35seen the barrier of use dramatically 5:38decrease as more people engage with 5:40large language models through 5:42chatbots but there will be field-based 5:45training for AI to be used as a tool in 5:48education in healthcare in field 5:50research as the AI models and data that 5:53enable the best work in these fields 5:54will be different and it will be 5:56important for us to understand the 5:58basics of how AI works so we can prompt 6:01it in ways that maximize value of its 6:04output all right so that's the first two 6:07what is the third important technology 6:09adoption curve well I think we can 6:11consider that one as 6:15Precision does it need a certain tool to 6:19work does it do the job well look 6:23calculators calculators would not been 6:25very popular if they hallucinated the 6:27wrong answer 20% of the time and this is 6:30where AI has grown substantially 6:32recently but hallucinations with large 6:34language models do remain an ongoing 6:37area of focus but the good news is that 6:40as we engage more with these AO models 6:42it helps to train it so we can all play 6:44a role in making AI better just by 6:47working with it now ai is already used 6:50substantially for customer service for 6:53human resources and for managing 6:54candidate hires and for lots of other 6:56important work tasks and it's coming to 6:59a workplace near you so what can you do 7:03to learn and get better well I would 7:04offer three points number one is Don't 7:09Be Afraid get started at the start of 7:12each one of these technology curves here 7:14we've talked about they were they were 7:16doubters and they were slow adopters 7:19Horseless carriages they'll never catch 7:22on number two play as with learning any 7:27tool or technology it helps to try it 7:30when you're not under work pressure and 7:31when you have time to make mistakes it's 7:34also a huge amount of fun and as we've 7:36already established potentially quite 7:39tasty as well and then number three 7:43consider more structured learning and 7:45the good news here is that we have an 7:46option for you to consider today 7:49designed for new explorers who want to 7:51build their skills on AI just go to 7:53skills build.org there are no costs and 7:56it's there to help people learn about AI 7:59so get yourself ready for the workplace 8:02of the future a workplace where it's if 8:04it's not already essential AI will soon 8:07be common place oh and just just one 8:11more invention the electric elevator was 8:13invented in 1880 and that was widely 8:16adopted 20 years 8:23later if you have any questions please 8:26drop us a line below and if you want to 8:28see more videos like this in the future 8:30please like And subscribe thanks for 8:34watching