CTRL-ALT-Compete

All right. Thanks for being here.

>> Thank you for having us.

>> So, I'm from Philadelphia. All right. And

we're kind of big on the Revolutionary War. That's kind of our our the name of

War. That's kind of our our the name of our game. Okay. There's an old colonial

our game. Okay. There's an old colonial American uh phrase around the Revolution. Join or die. We're all

Revolution. Join or die. We're all

familiar with this. Yes. Um

>> Cissan, I feel like for you and your company, it has been disrupt or die. M

die. M >> would you agree with that and why?

>> Uh so we're a 40-year-old company.

>> Yes.

>> We were born in tech.

>> Yes. In tech. We were born in the era of shipping CDs. That's when I joined the

shipping CDs. That's when I joined the company.

>> Oh, nice.

>> And so >> first mention of CDs on this on this stage today.

>> There are [laughter] there are lights in my eyes so I can't see this crowd, but I'm sure some of you maybe many of you uh were not even born in the era of shipping CDs. And so we, you know, we've

shipping CDs. And so we, you know, we've been through four plus massive technology shifts >> and uh and many uh economic cycles and

uh I I'll tell you the DNA of the company long before me has been about what you just said, live or die. Uh and

so we've had to figure out how to disrupt ourselves.

>> Yeah. Yeah. And and here you are standing today. What's your market cap

standing today. What's your market cap today? What's into it worth these days?

today? What's into it worth these days?

>> I don't know what the stock market did today, but you know, we're almost 190 billion. not too shabby after 40 years.

billion. not too shabby after 40 years.

So cheers. Um Ashoke, I want to come to you. Thank you for joining us. Um so in

you. Thank you for joining us. Um so in it made a big bet on machine and deep learning as we called it a decade ago. I

said earlier on the stage stays true for you. Um and my understanding is you

you. Um and my understanding is you really have to get the data ready to do something like that. Um tell us a little bit about that journey because we're talking about getting the data ready

now, but you guys were doing that a decade ago. That's right. Uh Andrew,

decade ago. That's right. Uh Andrew,

it's a pleasure to be here. What I'd

tell you is that a decade ago, as you said, we started to invest in three things. Number one, building the right

things. Number one, building the right team. Number two, building the right

team. Number two, building the right data platform. And then number three,

data platform. And then number three, building the right AI platform. These

three things work very very well together. The team has been trained on

together. The team has been trained on AI, on how to use data, how to govern it, how to manage it. We built the clean data pipelines that bring data to our AI

systems at scale, but then we really invested in connecting the data and the AI.

>> And then we built an operating system on top of this whole thing called Gen OS, which allows developers now to build massive applications at scale. To give

you an idea, in the last year, fiscal year 25, we had 3,500 independent projects and uh product experiences created on Genesis.

>> Yeah, that's remarkable. Um, I would like to know if you changed your strategy over those again 10 years or so, you know, if if you could have seen what was coming, [laughter]

hindsight 2020, were when you set out to make these changes a decade ago, did you pivot along the way, you know, at just seeing where the the market was going in terms of in terms of AI and capabilities?

>> Yeah.

So um when Cissan took over as CEO and the executive team launched one of the things that they defined was that Intuit is an AIdriven expert platform. That is

the company's strategy. That strategy

has not changed. What we did do though is start to evolve the technology in order to meet that strategy. And so we made deep investments in clean data at

scale. We made deep investments in

scale. We made deep investments in building an operating system that could allow people to access that data and build AI experiences and we were doing

this before the Genai revolution. Right?

When the Genai revolution came, we started to make investments in creating that operating system and that has really delivered measurable return on investment for our customers as well as

for Intuit itself.

>> Yeah. Sassan um into its founders 40 years ago >> said that the company's biggest competitor was paper and and the spreadsheet.

>> Yeah.

>> As we know it today. Is that still true?

>> It is actually. And just maybe briefly uh for your audience, you know, we serve consumers, businesses of all sizes and um and we focus on things that matter to

them, right? Which is money, cash flow.

them, right? Which is money, cash flow.

uh as I hear I hear they're concerned about the money.

>> Yeah. Yeah. Right. But but the reason I start there is you you're talking about cash flow, you're talking about survival taxes bookkeeping and accounting.

>> And um and there's an incredible fear factor when it comes to how do I grow my business? How do I manage my business?

business? How do I manage my business?

Uh am I going to have money to make payroll? And uh and you know, 75% plus

payroll? And uh and you know, 75% plus consumers live paycheck to paycheck. So

this is a a real you know we talk a lot about AI but there's like a real customer here uh that matters and what what we need to do for them which is how

do we power their prosperity and I say that just to say that the majority to your question the majority of both consumers and businesses fall in a bucket that we call non-conumption and

what we mean by that is um for instance businesses uh use 10 to 25 apps to manage their business >> most of the time their data and their insights are trapped in individual apps

and so they also have to have a tax accountant a bookkeeper to help them advise them uh and we and they use Excel spreadsheet Google sheets and so it's all non-conumption meaning they don't

use a platform to >> run their personal life or or their business for you >> and 40 years ago yes it was all paper uh today it's just a different form of

paper it's all in apps but it's all still trapped the insights are still trapped which is why those that we serve rely a lot on people, >> right?

>> And we believe people will still be a huge part of the equation along with AI, which uh I think it's counter to what many talk about depending on the industry they serve.

>> So if if they're really just looking for a better piece of paper or a better spreadsheet or or whatever it is, but really they're looking for a solution to their problem, right? Let's be honest.

Um and we talked about this earlier on on stage with the CEOs of Freshworks and and Zero earlier today, right? what what

do they really actually care about? Just

a solution to their problem. Um why

spend all this money on AI? I mean it's whisbang. It's you know really great. We

whisbang. It's you know really great. We

can do all this extraordinary thing. If

the bar is paper low >> you know why do all this? Is it just to gain customers from you know the the the the clutches of of paper and

spreadsheets? I mean you don't have to

spreadsheets? I mean you don't have to try that hard. Right.

>> That's right >> or wrong. No, I I love the question that uh that you're asking. First of all, um I I remind ourselves at the company all the time, customers don't care about AI,

right? Everybody talks about AI, but the

right? Everybody talks about AI, but the reality is a consumer is looking to increase their cash flow. A consumer is looking to power their prosperity to make ends meet. A business is trying to get more customers. They're trying to

manage their customers, sell them more more services. And we bet the entire

more services. And we bet the entire company before this topic was popular more than 70 years ago on really three things. One, it's what Ashoke talked

things. One, it's what Ashoke talked about, which is data. Uh we have to make sure that our data is clean. It's

customers data, not ours. It's clean.

It's usable. It's digestible by the platform. The second is in order for us

platform. The second is in order for us to grow, >> we declared seven years ago, we need to deliver done for you experiences. What

does that mean?

>> From lead to cash as a business, we'll help you manage your leads. We'll help

you manage your cash flow, we'll do your taxes for you, your accounting for you, we'll give you advice on whether or not you should buy inventory and done for you for consumers from credit to wealth, help you build your credit if you don't

have credit to how do you manage your money and grow your wealth. And what we said was the only way to do that was data, >> AI, >> right?

>> And seven years ago, we said hi, human intelligence.

>> Uh if you look at our addressable market, the majority of it is is influenced by people. people that are tax experts, accountants, bookkeepers that are advising you on what to do.

Although there the work is completely changing and we're automating it with AI, we believe AI plus HI is essential to reshape the category, which is really what the investments are that we've

made. So really, it's a long answer to

made. So really, it's a long answer to your very short question.

>> That's all right.

>> Um, customers don't care about AI.

>> Yeah.

>> What they care about is help me grow my business. Uh, help me prosper. And we

business. Uh, help me prosper. And we

have found the only way to do that is to combine technology automating everything for them with human intelligence on our platform that can actually give you the human touch and the advice. Yeah.

>> And we believe that will be the case for decades to come. But the role of the hi, the human will change.

>> So quick poll for the audience. How many

people have gone to the store for AI? I

really need to buy some AI today.

>> Zero hands. Andrew, to

>> your point, >> if I could add to that, probably no one has gone to buy uh AI, but probably a lot of you want work done for yourselves, right? You want to have

yourselves, right? You want to have technology that do work that you would uh rather do uh have the machine do.

What we've found is that with our agents, on average, customers are saving 12 hours per month with routine tasks

that they would have had to uh perform.

They're getting paid five days faster.

They're 10% more likely to be paid full.

And as a person who's run small businesses in the past, I can tell you numbers like that are very meaningful.

12 more hours means 12 more hours that I can spend building my products, understanding my customers, so forth.

And we have so many more statistics like this that show that the AI and the human intelligence combined together actually help people do better in their financial.

>> So this is really exciting. Can I just take 30 seconds and uh add to what Ashoke just said? Make make it sort of real in terms of what a business experience is. So as I said,

experience is. So as I said, >> customers don't care about AI, >> right?

>> Uh but and what we have launched is is a virtual team of AI agents that can hand off things seamlessly to a human >> that will do things like help our customers manage their leads,

>> uh help invoice and create estimates on their behalf. they're always in control.

their behalf. they're always in control.

>> Uh to follow up with customers that have overdue invoices, write everything for them, tell them which customers um are overdue and which ones typically pay on time and which ones they could actually get paid earlier. So we do all of the

work based on leveraging the customer data and AI capabilities to do the work for the customer. So the stats you're hearing from Ashoke, >> um we have an AI um accounting agent that will do a lot of the

categorization. That's the 12 hours a

categorization. That's the 12 hours a month they're saving. Yeah,

>> our payments AI agent customer doesn't know what it is. It's just it helps them with estimates, invoicing, getting paid.

And that's the tangible stuff that where we believe we can change the world to do the things for customers that has a real economic impact around the world.

>> Totally. I just want to call attention to the fact that Ashoke has the letters A and I stitched into his the right sleeve of his shirt in case anyone doubted him. [laughter]

doubted him. [laughter] >> Well, he has one stitched on his head, but we put makeup on. Can't see.

>> All right. [laughter] All right. I was

going to say I want to see the tattoos later, gentlemen. Um, all right. So, uh,

later, gentlemen. Um, all right. So, uh,

uh, I want to ask one more question and then and then we should go to the audience for them. Um,

>> look, you guys have so many customers.

How many?

>> 100 million plus.

>> Yeah. So, you have an an unbelievable view into the economy >> of of a certain segment. I know you serve all segments, but you especially serve small and medium businesses in

terms of quantity. I would like to know in your opinion how they're doing in this economy. This is a very odd

this economy. This is a very odd economy. [snorts] Um and you know many

economy. [snorts] Um and you know many of them fear AI or don't care about it or whatever. So what are you seeing

or whatever. So what are you seeing across the board?

>> Yeah, it's a great question. Uh ju just brief context. Out of the 100 million

brief context. Out of the 100 million about 10 million are businesses of all sizes.

>> Yeah.

>> And and the businesses that we serve aren't concentrated in any particular industry. So, we will serve plumbers,

industry. So, we will serve plumbers, landscapers, construction, real estate, wealth management. I could go on and on.

wealth management. I could go on and on.

>> Um, the two big things that I would say is listen, the job market is still strong.

>> Yeah.

>> Uh, credit scores um are lower that they've ever been.

>> Um, particularly with Gen Z.

>> Uh, credit balances are at the highest that they've been. Uh, particularly with Gen Z, their credit balances, um, credit card balances are up 36 37%.

>> But they still have jobs.

>> Yeah. uh and that's what's really keeping things together and so therefore everybody is being watchful about what they buy what they don't why at what prices um for businesses what we see across our base is the word I would use

is stability >> um profits cash flows are are stable um one element of it is they're on our platform so it's biased data um digitization is helping them

>> but what I would say is industries like manufacturing um insurance are actually up uh industries like lending, real estate are actually down in profit. So

overall it's stable but depending on country state >> very very sector driven.

>> Thank you for that. All right, let's go to the audience for questions. Questions

for the in it fellows.

>> Yes, we've got one way in the back. Your

name and who you're with, sir.

>> Thank you. Hi. Hi. Uh Samir Gulati from Zen Business. Um one of the hardest

Zen Business. Um one of the hardest things about small businesses is actually getting started and the first couple of years, right? Right. A lot of the things that you talked about don't even apply in many cases.

Given your position in the industry, how do you think about using AI or the combination of AI and HI to enable that and make it easier?

>> Yeah, it's a great question. Uh, you

know, f first of all, I'm inspired by what many are doing to help businesses get up and running much faster than they could before. But a couple of tangible

could before. But a couple of tangible examples that I would use. One is uh with our platform uh once you give us a few pieces of information that we um ask for like what what are your goals? What

are you trying to achieve? Uh and you know for instance uh depending on where you are in your cycle if you're 30 days in, if you're 60 days in uh we will in essence ingest your data. If it's

website data, if it's data that you put together a business plan on an Excel spreadsheet, whatever it may be, if it's handwritten notes where you can take a picture of, we'll ingest because first we need to understand what are you

trying to do? We'll ingest that and then based on that make recommendations uh like if you're make it real. If it's a if it's a plumber, uh then we'll help a plumber with what are the basic things that they need and then a plumber

they're on the road. they're trying to get business and so being able to um estimate and and create an invoice with progress payments to get paid right away is the capabilities we enable them with.

So really what we can do now that frankly we couldn't do before is based on who you are, what you're trying to do, and the millions of customers that we have on our platform that are like you, we can help you with what to get

set up with right away because you don't need all the capabilities that we have.

uh what you need is what's specific to your situation and then based on leveraging your data because we we use machine learning knowledge graphs a lot

of uh data and of course genai to help automate tasks, workflows and functions but we can get you up and started right away and that also teaches us by the way what else you may need and that we um uh

are in the midst of uh making something generally available where you can do Vive coding and just say here's what you know I need done and we'll to do it for you. And so a lot of that just helps

you. And so a lot of that just helps reduce the time to get started and to get your first customer and to get your first sort of cash flow in your bank account. And once we do that, then

account. And once we do that, then you're on a roll. And that's really our focus in terms of the benefit for customers to get started.

>> Thank you for your question. All right,

gentlemen. I have two quick lightning round questions before we before we wrap it up here. The first is um you've recently signed an OpenAI deal. Um are

you concerned about controlling your customer relationship given that?

>> Uh we're very excited about the deal.

There are three principles that that um are really important. One is the customer experience and the relationship. When the customer when

relationship. When the customer when we're engaging the customer, they know you're they're using the inuit platform.

>> Uh the second is the customer's data does not leave our four wall. So it's

our data, our models that are being trained. So the data and models and the

trained. So the data and models and the way the platform uh behaves matters and just the economics have to matter and the economics are the same for us before and after the deal. So and the thing

that's very exciting with open AI is it's it's the values and relationship we have with them which is we both want to drive prosperity for the end customer and I think it's going to be a gamecher in the long term. All right. And then my

last one is I'm I'm asking on behalf of everyone here and everyone watching on the live stream, when will AI be able to do my taxes, gentlemen?

>> Well, I don't want to do it anymore.

>> AI and HI does your taxes today. We we

have uh you know, just to make it real, right? We have um millions of customers

right? We have um millions of customers where AI does a lot of the drudgery for them and then hands it off to a human and the human finishes it for them. So,

we'll do your taxes today for you.

>> Wonderful. There we go, gentlemen. Thank

you very much. A round of applause for them.

>> [applause] >> Thank you so