116 The Impact of AI On Offshore & Entry Level Accountants

Summary

This video delves into groundbreaking studies comparing the productivity of knowledge workers using AI versus traditional methods across various tasks and technical skill levels. Surprisingly, the findings challenge preconceived notions about AI's impact on the workforce, particularly offshore workers and new graduates. Contrary to the belief that AI primarily automates menial tasks, the evidence suggests it enhances performance across the entire skill spectrum, including complex white-collar tasks. This shift could herald a new era where entry-level workers, empowered by AI, can quickly reach parity with their more experienced counterparts, reshaping the landscape for offshore staff and fresh graduates alike.

Takeaways

• 💭 Recent studies show that AI enhances productivity and quality of work for knowledge workers, challenging assumptions about future work dynamics.
• 🔥 AI impacts tasks across the entire skill spectrum, not just menial tasks, affecting both low and high-skilled workers.
• 🚀 Offshore workers and new graduates could benefit greatly from AI, potentially entering a golden age of accelerated skill development and contribution.
• 📲 Studies have found that AI can help complete tasks more quickly and with higher quality, with one study noting a 12.2% increase in task completion and a 25% speed increase.
• 🔧 However, AI's effectiveness varies by task type, with financial analysis tasks seeing a performance dip when AI is used.
• 🤩 Lower-skilled workers see a more significant performance boost from AI than higher-skilled workers, suggesting AI could democratize skill levels.
• 💻 The use of AI for upskilling and enhancing productivity is not just limited to entry-level tasks but extends to complex, strategic roles across industries.
• 👨‍💻 Offshore staffing is not just about low-level tasks; offshore workers are capable of performing high-level technical roles, and AI can enhance this capability.
• 📌 The narrative around automation needs to shift from fear of job loss to focusing on AI as a tool for enhancing work quality and efficiency across all levels.
• 🙋‍♂️ Emotional intelligence and human interaction skills remain irreplaceable, with AI automation likely increasing the importance of these skills in the workplace.

Q & A

What was the main finding from the Harvard study on AI's impact on knowledge workers?

The main finding was that participants with access to the AI model gp4 completed 12.2% more tasks on average, completed tasks 25% faster, and produced 40% higher quality output compared to the control group without AI access.

Why does the speaker believe the idea that AI will replace offshore workers is misguided?

The speaker believes offshore workers are just as capable of high-level technical work as onshore workers. The misconception comes from offshore workers historically doing more entry-level work, but with investment they can develop high levels of expertise like anyone else.

How did AI disproportionately help the bottom 50% of performers in the study?

The bottom 50% of performers saw a 43% boost in productivity with AI access, while the top 50% of performers only saw a 17% boost. This suggests AI can help lower performers reach parity with higher performers more easily.

What is the speaker's main argument around new grads and AI?

The speaker argues that pairing new grads with AI will help them be vastly more productive and capable than previously possible at the start of their careers. AI can help compensate for lack of experience.

What was novel about the meta GPT system?

Meta GPT simulated different expert agent roles working together on a software project, like a project manager, coder, tester etc. The interaction of these different skill sets produced higher quality output than a single AI agent.

How might an AI system that prepares tax returns be structured internally?

It would likely have different internal agents with perspectives like an administrator, detail reviewer, technical reviewer, and client representative that analyze the problem from different angles before producing the final output.

Why does the speaker say AI automation impacts all roles rather than just entry-level roles?

AI can help improve efficiency and quality at every level from administrative tasks to highly technical analysis. The output is only as capable as the knowledge provided, not inherently biased towards low or high level work.

What interpersonal skill does the speaker say is becoming more important with AI automation?

As AI takes on more technical work, skills like emotional intelligence, relationship building, empathy and compassion are becoming more premium for humans to complement the technology.

What evidence counters fears that AI will reduce jobs for offshore and new workers?

Studies show AI disproportionately helps lower performers, closing gaps rather than removing jobs. Given accounting's labor shortage and growing workload, AI should create more capacity, not redundancy.

Why can't accounting firms simply fire workers if jobs are automated by AI?

Firms are constantly lacking enough staff. Any automation will be used to give existing employees capacity for higher value work, not to reduce headcount.

Outlines

00:00

🔍 AI's Impact on Knowledge Work and Skill Spectrum

This segment introduces the evolving landscape of AI in the workplace, particularly focusing on its effects on knowledge workers across various tasks and skill levels. Highlighting recent studies, the speaker challenges common assumptions about AI, emphasizing its potential to automate tasks beyond menial ones, affecting all levels of work. The narrative shifts towards the specific impacts on offshore workers and new graduates, suggesting a paradigm shift in how work might be distributed and valued. The notion that AI could democratize skill levels and enhance productivity across the board is floated, alongside a jest about new graduates buying out firms.

05:01

📊 Study Insights: AI's Varied Effects on Task Performance

Delving into specifics, this part outlines findings from studies involving consultants and AI, revealing that AI assistance leads to significant improvements in task completion and quality, especially in narrative-driven consulting tasks. However, a nuanced picture emerges with a study showing AI's limitations in financial analysis tasks, where AI-assisted participants performed worse. These mixed results illustrate the 'jagged edge' of AI's capabilities, suggesting both the potential and the challenges in integrating AI effectively across different work domains.

10:03

🚀 AI and the Golden Age for Entry-Level Workers

Focusing on the differential impact of AI on workers based on their skill levels, this segment highlights that lower-skilled workers see greater performance boosts from AI assistance compared to their higher-skilled counterparts. This suggests a 'Golden Age' for newcomers and entry-level workers, potentially leveling the playing field between novices and veterans. The discussion extends to the implications for offshore workers and new graduates, positing that AI could be a powerful tool for upskilling and democratizing access to high-level productivity.

15:04

🤖 Rethinking Offshore Work and Automation Assumptions

This section critiques prevailing assumptions about the role of offshore teams and automation's impact. It argues against the notion that AI will primarily displace entry-level or offshore tasks, suggesting instead that AI's reach across the skill spectrum could enhance the value of offshore teams. The speaker challenges stereotypes about offshore workers' capabilities and discusses the potential for AI to elevate their roles within firms, moving beyond the limited view of offshore work as inherently low-level or menial.

20:05

🧠 AI's Broad Impact and the Future of Work

Exploring AI's comprehensive impact, this segment discusses how AI could transform work across all levels, including complex and creative tasks. It introduces concepts like Meta GPT and autogen frameworks that allow for a multifaceted approach to problem-solving, potentially revolutionizing how tasks are approached and completed. The speaker envisions a future where AI-assisted roles span from administrative tasks to strategic decision-making, challenging traditional notions of work distribution and expertise.

25:06

✨ Optimism for Newcomers and the Human Element in AI

Concluding the narrative, this part reflects on the broader implications of AI for newcomers to the profession and the enduring importance of human skills. It suggests that AI's integration into work processes offers unprecedented opportunities for new entrants to make meaningful contributions early in their careers. However, it also underscores the growing importance of human-centric skills like relationship management and emotional intelligence, which remain irreplaceable by AI. The speaker closes with a positive outlook on AI's role in augmenting human work and fostering inclusivity in professional growth.

Keywords

💡AI Impact

AI Impact refers to the changes and effects Artificial Intelligence has on work processes, efficiency, and job roles. In the script, it's discussed in the context of knowledge workers and how AI tools, like large language models, are transforming their productivity and the quality of their outputs. The speaker emphasizes that contrary to popular belief, AI's influence extends across all levels of work, not just menial tasks, challenging traditional assumptions about the future of work.

💡Knowledge Workers

Knowledge workers are individuals whose main capital is knowledge. Examples include engineers, doctors, accountants, lawyers, and academics. In the script, the speaker contrasts the outputs of these workers when they use AI tools versus when they don't, highlighting significant improvements in efficiency and task completion speed facilitated by AI.

💡Technical Skill Spectrum

The Technical Skill Spectrum refers to the range of skills from basic to advanced levels required in various jobs. The script discusses how AI impacts workers across this entire spectrum, not just those performing low-skill, repetitive tasks. This challenges the notion that AI will only automate menial jobs and suggests that even complex, high-skill tasks are susceptible to AI-driven efficiencies.

💡Offshore Workers

Offshore workers are employed in a different country than where the employing company is based, often for cost-saving reasons. The script explores how AI might change the demand for offshore labor, especially in contexts where these workers are engaged in tasks that AI could perform or enhance, suggesting a potential shift in how companies utilize offshore teams.

💡New Grads

New Grads, or recent college graduates entering the workforce, are discussed in the context of their integration into AI-enhanced work environments. The script proposes that AI could be a 'Golden Age' for these individuals by rapidly upskilling them and making them significantly more productive and valuable from the outset of their careers.

💡Generative AI

Generative AI refers to AI systems capable of generating new content, such as text, images, or code, based on their training data. In the script, the speaker discusses the role of generative AI, particularly large language models like GPT-4, in improving the productivity and task completion speeds of knowledge workers, illustrating its transformative potential in professional settings.

💡Task Automation

Task Automation involves using technology to perform tasks with minimal human intervention. The script challenges the assumption that AI will only automate low-skill tasks, suggesting that AI's capabilities span the entire skill spectrum and can enhance or even perform complex tasks traditionally reserved for highly skilled workers.

💡Performance Boost

Performance Boost refers to the significant enhancement in output or efficiency achieved through a particular intervention. The script notes studies showing that workers in the lower half of the skill spectrum experience a more substantial performance boost from AI tools than their higher-skilled counterparts, suggesting AI's potential to level the playing field in terms of productivity.

💡Fixed Amount of Work

The concept of a Fixed Amount of Work is critiqued in the script as a fallacy, especially in the context of AI's impact on jobs. The speaker argues that work is not a finite resource and that advancements like AI often lead to an expansion of work opportunities rather than a reduction, by enabling new capabilities and efficiencies.

💡Upskilling

Upskilling refers to the process of teaching employees new and more advanced skills. The script highlights how AI can facilitate rapid upskilling, particularly for new grads and offshore workers, by providing them with tools and capabilities that enhance their productivity and allow them to perform tasks previously beyond their skill level.

Highlights

Studies show high-quality benchmarks for knowledge workers using AI versus not, across various tasks and skill levels, challenging assumptions about work's future.

AI's impact goes beyond automating menial tasks, affecting jobs across the entire skill spectrum, including decision-makers and high-level positions.

Misconceptions debunked: AI affects more than just menial work, and the amount of work available is not fixed but can expand with technology and legislative changes.

Harvard Business School study found that participants using GPT-4 completed tasks 12.2% more and 25% faster, with a 40% higher quality in responses.

AI showed a decrease in performance for financial analysis tasks, highlighting the 'jagged edge' of innovation where AI excels in some areas but not others.

Lower-skilled workers see a significant performance boost from AI, narrowing the gap with higher-skilled workers and potentially leveling the playing field.

The 'Golden Age of Noobs': AI could enable rapid upskilling of entry-level and offshore workers, making them more competitive and valuable.

AI may disadvantage high performers by making it easier for lower-skilled workers to catch up, challenging traditional skill hierarchies.

Offshore workers are not limited to menial tasks; with AI, they can perform complex, high-level tasks, debunking stereotypes and opening new opportunities.

The advent of AI and new technologies like meta GPT and Microsoft's autogen framework indicate that AI can enhance work across all levels, not just entry-level tasks.

As AI automates more technical tasks, the value of human interaction, emotional intelligence, and relationship management increases in the workplace.

AI's role in automating tasks across the skill spectrum suggests that both offshore workers and new graduates have a bright future in industries adopting AI.

The narrative challenges the fear that AI will replace jobs, instead suggesting it will transform jobs and create opportunities for all skill levels.

AI's impact on financial analysis tasks underscores the importance of understanding its limitations and the need for human oversight in certain areas.

The potential for AI to standardize capabilities among workers of different skill levels could lead to a more equitable and efficient workforce.

Transcripts

we're getting some really high quality

studies for the first time benchmarking

knowledge workers outputs when using AI

versus not using AI just in general on

different types of tasks but also on the

technical skill spectrum and I think the

results are surprising and May challenge

some of the assumptions we have about

how work is going to change in the near

future so come on in let's talk about it

specifically how does this stuff impact

offshore workers and how does this

impact new grads those fresh baby cheek

new grads that we need to come in and

help us out and ultimately buy us out of

our firms right that's really what we're

concerned about here so come on in let's

talk about

[Music]

it I'm just kidding I'm I was kidding

about about new grats just buying us out

that's not why we want you here we want

you here because this is such a

a fun and challenging profession that's

why we want you here okay I think the

general I I see people saying oftentimes

around AI the same standard Trope that

we saw we've always seen with automation

that oh AI is going to be great to aate

automate the menial tasks and get us get

us on to performing higher value work

and I don't think that's necessarily

true it will automate menial tasks but

it's going to automate tasks on the

entire skill Spectrum this is really for

the first time it's interesting it's for

the first time that like white collar

stuff is getting automated and the

decision makers the important people

their jobs are actually at risk too it's

not something that is being put upon

like the lower skilled workers it's

impacting everybody and I still don't

know that people have their heads around

this because I keep hearing things like

well there goes offshore and what are

all the interns going to do and there's

kind of two like inherent fallacies in

that one is that AI only impacts menial

work which is absolutely absolutely

incorrect if anything it's more

disruptive to like mid mid uper level

folks for reasons that we're going to

get into but the second misconception

here is just that there's a fixed amount

of work to be done and that this is like

the biggest fcy in all the AI ending

anyone's jobs discussion is the idea

that there's this fixed volume of work

to be done and in public accounting that

could not be further from the truth

riddle me this if you run a firm and you

have a team and you found a way to

automate one of your team members jobs

or half of their jobs would you go out

and fire that person tomorrow no you

absolutely wouldn't like I like that was

would have never been in been the case

in all of my firm running years we were

so hungry for more good people and

constantly trying to upskill people and

do everything we can to automate for

them so that they they can keep doing

higher value stuff and I don't know what

better example we need than Co to show

us that there's not just a fixed amount

of work in this profession you get

legislative changes you get I there's a

hundred different examples of when the

workload increases and contracts and for

whatever reason we still go into work we

still work all day and then we come home

and that's probably going to happen

until the end of time until you like

give yourself permission to work less

but that's another podcast episode so

the there's this notion that there's a

fixed amount of work to be done in that

that totally isn't the case and so in

the last couple months we've actually

got some interesting studies around that

like try to as best as they can fairly

Benchmark giving a set of workers AI to

work with and having a set of workers

complete the same tasks without Ai and

they've gone a long ways to try to like

randomize this and ensure that it's not

going to be biased towards people that

maybe already had like experience using

you know a chat GPT or something like

that because there's definitely an

element of learning the tool in fact one

of these studies one of the things they

benchmarked was even like giving them a

primer on this tool and so they pulled

in folks that had never used it before

and it was just an AI chatbot and the

folks who they gave like a really highle

primer vastly outperformed the folks who

used it who didn't have that primer a

great reminder of the value of just

knowing a little bit of prompt

engineering and that sort of thing AKA

send your team my chat GPT videos but

interestingly what at least the two main

studies that I saw both found I'll

reference this one from uh Harvard

Business School It's actually an

interesting read navigating the jagged

technological Frontier field

experimental evidence of the effects of

AI on knowledge worker productivity and

quality that is a mouthful I'll put a

link to this in the show notes if you're

interested in general participants with

access to the large language model gp4

completed 12.2% more tasks on average

and completed tasks 25% more quickly

than those without access to Ai and the

context here is it was a group of 385

participating Consultants were given a

set of 18 Consulting tasks and so this

what does this tell us this tells us uh

maybe how helpful it is on Consulting

tasks right which is not necessarily

always the stuff that we do I think a

lot of this is actually like narrative

type of thing which would completely

make sense that it would be super

helpful there it says the responses

produced by the Consultants with access

to generative AI were more than 40%

higher quality compared to a control

group I don't know how you measure that

but that's a big Delta another

interesting tidbit here they ran a

second experiment where they required

study participants to analyze a

company's brand performance using

insights and financial data the

responses were evaluated based on

correctness and there was a notable dip

in performance among those with access

to the AI compared to the control group

subjects in the control group were

correct about 85% of the time while

those in the two AI access categories

saw an average decrease of 19 percentage

points by comparison so the folks uh

that used AI for financial analysis

scored 20% worse and actually part of

the the idea of this study they call it

the what is it the jagged edge of

innovation the jaged tech techological

Frontier it's just like the difficulty

of knowing what it will do well and what

it won't do well and how to ultimately

trust it when you don't exactly know

what it's going to nail and what it's

not going to nail cuz when it's magic

it's amazing until it does something

really dumb and you don't always know

when that's going to come but the most

interesting thing in this that the last

two studies I've seen both said was that

those participants who were categorized

as bottom half skill performers saw a

large larger boost in performance from

having access to AI 43% when completing

experimental task compared to the bump

experienced by top half skill performers

just 177% so the folks in the lower 50s

percentile in terms of their performance

levels coming into the study increased

performance with AI by 43% folks who are

in the top half only increased by

17% and this makes sense in general if

you try to use this stuff for your area

domain expertise it's not always that

impressive right but if I use this for

something I don't know anything about

like cooking or coming up with a

cocktail recipe or applying a tourniquet

in battle like these aren't things that

I'm an expert in so it's going to be

really helpful there and I suppose by

extension then it makes sense that the

people who maybe within your field are

not as accomplished as you have more to

gain by using that AI than you do and so

to bring this back around to Gra Brads

and offshore staff what this tells me is

that this could be the Golden Age of

noobs the Golden Age of of entry-level

skill people of upskilling folks at a

level that like was never before

possible if we can get our

underperformers to improve to a level of

parity with the folks who were the over

performers it's like this now this

standardization of capability if

everybody has AI now there's a a much

smaller Delta between those new folks

and the folks who were high performers

previously and so to me if anyone is

disadvantaged by this it's the high

performers I think right because it's

easier than ever before for the

underperformers to reach parody with

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looking at the the offshore uh

discussion because I've seen a lot of

people talking about this that this

ultimately will will hurt offshore

workers the adoption of AI I I think

there's a number of things like loaded

into that line of reasoning the main one

being the super broken mental model that

says offshore workers are just going to

do low entry level menial work I'll let

you in on a secret offshore workers are

capable of absolutely everything from a

technical standpoint that on workers are

and it's like it sounds dumb to say

aloud but it's like these people are

humans like they can learn every bit as

as quickly as the people that we have

onshore the main thing that most

companies aren't going to do is they're

not going to put them in a client facing

capacity at least in Professional

Services you won't do that but because

the first work that went offshore

culturally was like low-level entrylevel

menial stuff that nobody else wanted to

do is this really unfortunate projection

onto offshore workers that that's all

they're capable of when I know firms

who's most senior technical people most

senior ta tax technical people are

offshore often times it means building

that investment yourself like investing

in people over decades and getting them

to where you want them to go there are

talented people I mean all all the big

firms are offshore so those people like

you could hire a big four person in the

US that's super talented you can do the

same offshore but they're going to be

really hard to get just like they are

here in the US but if you believe that

you can develop somebody onshore to a

level of expertise promise you you can

develop an offshore person to that same

level of expertise so what I get really

excited about when I read this is the

notion that I could pull in offshore

folks who are not like the mega

highlevel technical big four types but I

can pull people in and actually upskill

them faster than ever ever before by

pairing them with AI which for me makes

them more value Val than ever to bring

this back to college grads same thing

like that makes those people more

valuable to me than ever the notion that

I could pair a college grad with an AI

and they're capable of more productive

output than they could be otherwise I

mean we all know when we were Juniors

just the astronomical time you spent uh

floundering and trying to figure

something out because you were afraid to

ask another question and you just burned

like entire afternoons in the sunmer

summer trying to figure out something

really dumb because you just don't want

to be the numpty that has to ask imagine

having a little friend you could ask who

wouldn't judge you who like there was no

fear of asking stupid questions my gosh

like chat assistants are going to be so

so valuable for juniors so if we all of

a sudden have like Junior technical

people that are capable of way way more

I have a really hard time imagining

there's not going to be something for

these people to do right if anything if

an entry level person will get me 80% of

the capability of a person with a

decade's experience like I would think

that person how to be concerned now

ultimately in our space we are so so far

from anybody need needing to be

concerned because there are so many

things to do and so many more people

that we can help and more things that we

can do for all the people that we

already have that I mean I genuinely

believe nobody is in a position where

they're like oh we found a way to

automate what you do see you later it's

just not realistic I don't think and so

I heard this this came up last week at

an in an executive Round Table and there

was kind of just this implicit

assumption that it was almost kind of a

bygone conclusion that oh we won't we

won't really need our offshore teams

anymore and I just I think I think what

that's actually founded in is the past

realities around automation the stuff

that you would automate is like data

extraction data entry stuff like that

are we I think we have some assumptions

that maybe we're not aware of that are

founded in past types of Technology

where the stuff that was most ripe for

automation were the tasks that the entry

level people were doing but that's

absolutely not the case with AI

everything on the skill spectrum is

subject to like AI being able to help

you get that stuff done more efficiently

do it completely for you right now I

genuinely don't think it is concentrated

at one level of expertise Spectrum or

the other if you think about stuff like

the most technical research oh my gosh

the power of a I to go through mountains

of documentation super super nuanced

documentation and make connections

instantly in a way that would take you

so so so long to do doesn't mean it's a

a replacement for your verification and

for you going in and doing a lot of that

digging too but some of those hairiest

things that require the connection of a

bunch of stuff that a junior person may

not be aware of AI is going to be

tremendously helpful for that stuff so

another couple interesting technical

developments that I think lean into this

even further uh a little bit around kind

of the architecture of how AI is

continuing to get better and what the

solutions that ultimately like can

prepare tax return or or do these really

complex tasks will look like it was

maybe a month or two ago there was a

project put together that was really hot

for a while called meta GPT and what was

novel about meta GPT is meta GPT the

multi-agent framework work was it

basically created these avatars

simultaneously that would work with each

other and bounce things off of each

other to get to a higher quality final

product and this was specifically

created around the notion of software

development and so if you have a

software agency that's not like a single

person with all of the expertise doing

all of this stuff right you have

different roles within that agency

people with different types of expertise

that add their own make their own

contributions to a project and as a

result kind of the rubbing together of

those different skill sets creates a

higher quality output and that was kind

of the premise of metag GPT and so you

would task it with creating a an

application and within that you had a

bunch of different agents you had an

engineer agent and its jobs were to

write code review code debug code you

had a QA agent its job was to write

tests and run tests these these are like

tests for the system to see if it breaks

that sort of thing Quality Assurance

third you had a project manager it would

write tasks assign tasks to different

agents review I don't know what that is

review design and review code you have

an architect it would write the design

review the design and review the code

you had a product manager and then you

had a boss that was managing the overall

requirements of the project and all of

those different agents worked together

on that same task and they would

critique each other and iterate on

exactly what they were doing through all

of those different perspectives and this

was really novel and yielded a much much

higher higher quality output than if you

simply toal language model how to do a

thing and then asked it to do it it

turned out that all of those different

perspectives and how they interacted

with each other yielded a higher quality

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everybody gather around take take one

another's hands now we can all agree the

way that we exchange information with

clients very important can be a massive

time waster if you don't nail it but I

get it the fear of training clients on a

portal system right what if you end up

not liking it what if you train a whole

pile of people on this giant system and

then you're like turns out this actually

isn't the one for me or this new super

cool AI rocket ship platform just took

off now I got to get all my clients to

move here's the thing that is the best

argument for why your client portal

experience ought to be separate from

your workflow management tool you

getting what I'm saying co-pilot man all

they want to touch is that client

experience just the portal giving you a

mega flexible platform for how you want

to work with your clients so that if the

workflow stuff changes if you want to

pull in a different tool for that you

can without changing the client

experience pretty smart especially in

these scary Changing Times of AI right

right actually got a uh a demo dat

coming up on the main YouTube channel

from co-pilot in the next week or two

where we actually get Hands-On with it

you can see even even more about it so

you're looking for a cool modern client

portal experience check out co-pilot

Link in the show notes and this is kind

of building on you know something we've

talked about in the past Chain of

Thought prompting where when you're if

you're talking to chat GPT and you want

it to solve a complex problem you'll get

a much higher quality output if you ask

it to solve it step by step because it

kind of as it outlines stuff step by

step it is changing the probabilities

related to like what is subsequently

generated and in that study where gp4

passed the CPA exam this step-by-step

approach actually increased it score by

20 points so it makes a big difference

in the quality the output metag GPT the

notion of having all these roles and

they interact with each other is kind of

a further development of that concept

and this got picked up again recently

because Microsoft just launched their

own version of this framework that's

it's a little more flexible it's not

specific to developing software it's

really interesting it's called autogen

I'll put links to all this stuff in the

show notes autogen enabling Next

Generation large language model

applications and it lets you in a more

modular way build basically what metag

GPT was explaining and you can even

design kind of different ways for those

agents to interact like you can have a

hierarchical version where you have kind

of a boss and everyone reports back up

to that boss you can have like a more

circular sort of thing and then what we

do what this ultimately looks like I was

talking with Ashley Francis about this

the other day when it comes to tax and

accounting you're probably going to have

these agent roles uh that really

represent like human roles on the entire

expertise Spectrum so take a tax return

for example like an AI that ultimately

will prepare tax turn behind the scenes

there's probably all of these different

agents attacking that problem from

different angles so you've probably got

something like an admin that is like

ensuring that the project is moving

through the steps and the documentation

is like in line with the company

standards stuff like that second you

probably have like a detail reviewer the

person that's making sure that you know

this number got keyed in correctly over

here just making sure there wasn't

transpositions that sort of thing third

you probably have a technical reviewer

the person who is reviewing the output

more through the lens of the technical

rules fourth you probably have the

client who is considering does this

outcome align with past Communications

I've had and the expectations we had for

this outcome you probably got this whole

cast of characters that is approaching

the problem like from their own

different perspective and you'll notice

it's not all entry-level stuff like the

the agents are speaking into this

project at every single level of

expertise they're whittling away at that

problem in the context of you know a

month end close and an accounting firm

it probably looks similar you've

probably got an administrative sort of

thing where it is managing the movement

of the entire project itself you may

have roles that look like a traditional

finance department so maybe you've got

like a bookkeeper an accountant a

controller a CFO maybe even a CEO that's

looking more at the kind of over-the-top

results but some of the bigger more

complex AI applications that will come

together to perform perform this really

complex novel task right now it looks

like the way that stuff's going to get

done is by collections of Agents acting

through the lenses of different roles

and the fact that this research has

floated up to the top and you have

people like Microsoft investing in these

Frameworks to help people develop things

this way to me this is really compelling

proof that what llms are ultimately

great at is not the menial entry level

work is all of the work is the entire

vertical it's simply a matter of the

knowledge that you put into that

language model that is what it's going

to do really well the perspective that

you give it the things that you want it

to prioritize ultimately that's what

it's going to do and that can be SE

Suite level stuff or it could be entry

level stuff and so as we were kind of

having these conversations last week I

kind of initially took it for granted

like yeah we're talking about automation

so it's going to be the entry-level

stuff and it's going to be you know the

entry-level people ultimately that are

at risk but maybe that's not a problem

because we can't find new people right

but the more I thought about it as I was

looking more into autogen recently and

thinking about metag GPT as I'm reading

some of these new studies that are

coming out all of these things are kind

of corroborating that notion that it's

not the entry level stuff that's at risk

everything is at risk really probably

and maybe at risk isn't the right way to

put it but everything can be improved we

can improve upon the way that we're

completing virtually all of these tasks

which is great news like CEO wants to

get home for dinner just as much as the

entry level dude right and so I like I

don't wait into the whole pipeline

discussion and CPA exam and all that

stuff but this is one area where uh like

I'm all of the evidence that we have

right now I think points to the fact

that that this is great news for people

coming into the profession it it's going

to be an accelerant for them to make

meaningful contributions you remember

what your first couple years in the

profession were out in a stinky

Warehouse somewhere counting potatoes

like man nobody's going to miss that

stuff so the notion that new people can

come in and be much more productive than

ever before that's great news that is a

big old win for all of us in my book and

I would also extend that as far as

offshore staffers Staffing offshore

workers where maybe that goes sideways

is in a situation where the firm just

doesn't have the right mindset and isn't

treating those people as like peer

members of the team but rather this like

lower level team that's only allowed to

do menial things I think that's a

massive waste I mean that's just like

like I guess I don't get why people I

guess see offshore teams through such a

different lens it'd be like going out

and hiring a bunch of people from a

different college and saying like oh

they're not capable of this other work

like they're capable of all of the same

things strategically when you plug these

people into your business like yes

you're probably not going to put

offshore team members and client facing

roles but we can't even manage to get

the work done like it is all hands on

deck in this profession right now could

you use more people to help you do all

the technical stuff absolutely now one

thing that is the same I think one thing

that does carry over from the old

automation tropes is just the continued

March towards there being a shrinking

amount of space for folks who can't be

human for people who can't build

relationships with other human beings uh

we've been saying that about automation

for for a long time there's less and

less room for that person who's going to

sit back in the corner and just crunch

numbers all day and not manage

relationships or manage people uh AI is

going to keep pushing Us in that

direction I think it sure seems that way

right now if you go out and you hire 10

entry level people and they're capable

of really high level powerful stuff

that's awesome but then what do their

jobs become it skews then more heavily

towards relationship management rather

than doing the work right now if your

job is 50/50 relationship management and

doing the work I see AI knocking off

more of the doing of the work tasks than

the relationship management tasks which

which just take time sure there's stuff

like writing emails and all that that it

can help with but ultimately AI

automating a bunch of work is probably

impacting the technical stuff more than

the human stuff

so I would say that remains unchanged

we're continuing to go down the path of

it being more important to be able to be

human to build relationships to be you

know have high emotional intelligence to

be able to make people feel like you

care about them to be able to like

listen and be compassionate and have

empathy and all that stuff that is

becoming more important by the day and I

think especially as we have more digital

experiences and more things get

productized and we talk to chat Bots

more instead of actual people we're

going to get more and more of a premium

on human and person experiences and

service that is human not a chap bot so

we still got to figure out how to be

human not just for work but because

that's also just a good thing to do you

know okay if you are offshore working

for like a US company if you are a new

grad if you're considering coming in

another profession in my mind this is

all good news if you have people who are

afraid of this or like fellow students

who have been spooked by this please

share this everything here seems to

point to AI actually being killer for

you and this is win for everybody like

the boss they want you to be as as

productive as possible too right so this

all seems like really good news to me uh

what do you think anything you've seen

that would would make you think the

opposite or any compelling evidence that

we've got to the counter to this would

love to hear it uh we're still kind of

figuring this stuff out day by day right

so thanks for coming and hanging today

and I'll see you in the next

one

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