Data Analytics and AI for 2024 and Beyond

AI lets people focus on high-value activities. Automating lower-cognitive and repetitive tasks reduces the risk of burnout and improves the employee experience.

Watch this insightful FP&A talk by Brian Kalish to learn how finance and accounting professionals can instead spend more time on the high-value work they are meant to do—using their creativity to raise the financial IQ across the organization, strengthening relationships with the business, and making informed decisions that drive growth.

Don't miss out on this valuable advice! Watch the recording now to stay on top of your data game!

Transcript:

It's just wanted to share with you just you know, a few thoughts that I'm seeing, that are taking place around the world.

So I'm not gonna read that to you. It's nice to have, in the background. But just to introduce myself from Brian Kailesh, I live in Washington, DC.

My background was about twenty years on the corporate side for very large financial institutions, like JP Morgan, a number of years ago I made a switch into edemia and into into, consulting. So now I spend a lot of time traveling the world.

Again, consulting, doing training, I teach at Florida International University in Miami, Florida.

And we can really tell that the world has come back. Hey, it's great to see so many faces here in the room today.

It's great to come to events like this because we can learn so much. But also I'm a huge fan of networking. So it's a great opportunity for everyone in the room to meet, if you don't already know, one hundred two hundred hundred new people today that can help you do your job.

Again, I'm a huge supporter of networking because you wanna build your network when you don't need it. Because when you need your network, you don't want to build one. So, like, you know, whichever, you know, initiative you want to take, I always tell people at events like this, meet ten people. You know, ten people you don't know, introduce yourself.

It's a great opportunity.

To give you an idea of how explosive the growth has been in this region over the last year.

I've been to here and to the UAE seven times in the last six months. So I'm doing about twenty five to fifty percent of my work right now in this part of the world. So two weeks ago, I was here in Riyadh. I'm here in Riyadh this week. Next week, I will be in in Corta's backyard in, San Jose, California.

So if I'm traveling that much, it means the world has come back after everything that we went through over the last couple of years.

My relationship with Encorda goes back about six years. One of my strategic partners that I work with Zee Capital Advisors, who's a strategic partner of Encorda in North America. It was truly joyful when Osama put some of the logos earlier, and those are e Capital logos. So it was truly a joy to see that.

So one of the things that I like to do is put up a dynamic slide.

One, I love it.

It tells a good story, and what's great is in a room with six hundred, seven hundred, eight hundred people, everybody looks up, because there's something going on. And why I like this slide so much is for me, it encapsulates what data analytics is all about, which is both of those models use the same And so I love quoting George Box, if you're familiar with him, which is all models are wrong. Some are useful.

It also ties into something that Albert Einstein said, which is model should be as simple as possible, but no simpler, and then it rolls in if you're familiar with Occam's razor, which is when given two potential solutions to problem, the simpler one tends to be the correct one. So just the idea of I can take same amount of data observations of the stars, and I can prove using air quotes that the earth is the center of the universe, and I can take that same data set and also prove that the sun is the center of the universe. So it's a nice slide to do a little bit of intro action.

So one of the things we wanna talk about, and we're not gonna go through all these points, but, you know, when we look at what priorities are for for c c f o's.

The the two that really jump out to me as far as our topic today is number two, which is develop and refine a data analytics strategy, and number five, which is set the technology strategy and roadmap.

So when we look at, you know, developing and finding a a data analytics strategy.

From the finance perspective, what has really changed over the last twelve years with the introduction of cloud, and it just had its twelfth birthday. If you think that the cloud was introduced with Microsoft Azure in twenty twelve, is finance people have had to learn more and more about technology. And that's not what we're strong at. And but because the world is changing so much, we have had to extend ourselves to understand that if we want to improve our world, we have to embrace technology, we have to embrace data analytics.

And so what I kind of like about this slide is it brings in this whole model, the the, what we call, DASM, but it's just the data analytics strategy operating model And just the whole thought about it is the fact that we need to tie what we're doing with data analytics to what the business is really doing.

And then priority number five for CFO's, again, is set, finance technology strategy and roadmap. And the real takeaway for me in here is the fact that the challenge that we're dealing with is is the triangle here, right, is we have forces driving urgency to innovate technology strategies.

And that comes the fact that we live in a world of very high volca, v u c a. Volatility, uncertainty, complexity and ambiguity.

Now thankfully, I would say the level of Volca is lower today than it was two or three years ago. But it's still very high. And where it really takes us to is if you look at, kind of the, the pyramid we have here, is that at the very top, we're dealing with dynamic market events, which is driving us to a demand more agility.

Unfortunately, we're being impeded by our aging technology infrastructure which then slows down our ability to react at the same time the world is going faster and faster. So, again, we're embracing technology to solve the problems of today.

What's key though is technology is a tool.

Technology isn't the solution.

You have to have people, process, technology, and culture to actually come up with solutions.

What's changed so dramatically in the last twenty years is the technology that we have available to us is grown by leaps bounds.

So those were the top five priorities for CFOs.

I spent a lot of my time and the area of finance called FP and A Financial Planning and Analysis.

Again, these were their top five. What I'm really focus on is the number four and number five, which has developed a finance data and analytics strategy, and then I think what everyone's kind of interested in is accelerated AI, you know, implementation and finance.

And so when we look at the next slide, oh my gosh, it looks so much similar to the slide I showed you earlier, actually, I'm using the same graphic.

So, yes. Number two for CFOs was developing a data and analytics strategy, It was number four for FP and A professionals. Again, it's just the same idea that in order to succeed in this world today, we're way past the point of throwing people in Excel spreadsheets. We've really gotta leverage technology data analytics, but it's all gonna be tied into what the business is doing.

And so, again, when you talk to CFOs and you talk to FP and A professionals, you know, the numbers that we see, fifty eight percent see data analytics alignment with business strategy as one of the top three drivers of success in the organization.

And with every presentation, I would normally say there are three takeaway slides So today, I'm gonna have a fourth as I was reviewing actually this morning. So this is one.

And maybe number one or number two. But the goal is to create a business strategy that's in fused with data and analytics, not to have a separate data strategy and a separate analytic strategy.

Everything has to be tied to what the business needs.

So we get all excited we actually get to the AI point.

And what's interesting is that over the last two years, some the research I said, is actually AI hasn't gotten to the top five for CFOs, but even though it's only at thirty six percent in this survey, it actually got in the top five for FP and A professionals.

And one of the things that I find very helpful is people were saying, well, AI kinda sounds like science fiction.

Is it really something that's taking place? One thing I would say is difference between science fiction and technology is a matter of time. Right? So if you think about all the things that we didn't have twenty years ago that seemed like it was science fiction.

So whether you wanna talk about Google Translate, you wanna talk about smartphones, you know, you wanna talk about artificial intelligence, they come about. But one of the questions I get often is, well, how are people using it? Well, again, I would say this is actually this is the the slide that I added in in your top four, is these are the top twenty three business cases that people were using AI for today. And I like the way that it's set up in this prism because it's talking about business value and feasibility.

Right? It's easy not to have anything there at the bottom, right? If it's, you know, has little value and it's hard to do, it isn't gonna happen. But the fact that companies today are leveraging AI is truly impressive.

Right? So we wanna we look at the recommendations you know, it's the idea. And what's great is kind of fun. I know the last speaker was saying it's hard to go after the the keynote.

It's great to be number three because you've heard, you know, smart people have been talking about. And if you had some bad ideas in your presentation, you can quickly get rid of them.

But it's just the idea that, you know, we need to build an AI road map and the fact that was brought up earlier, you know, the fact that we need to have to create citizen data scientists with the people that we have.

So welcome to the birth of generative AI.

It was kind of fun for me this morning that, a former boss of mine, if you're familiar, Jamie Diamond, who's the CEO of JPMorgan Chase.

Gave an interview yesterday, and he came out, and part of the interview was saying, AI is real.

It's not a it's not a fad. It's not like what we saw with the internet boom twenty years ago. It's real. And to give you an idea of how real it is for JPMorgan, is they just hired for the first time a chief data analyst officer for the organization really focused on AI.

They have hired two hundred employees to focus on how JPMorgan can leverage AI.

And so to everyone in the crowd, first of all, full disclosure. I am way out the curve. I'm a huge believer in AI. I'm a huge believer in automation.

I think you should think about the impact that generate AI is gonna have as living in the industrial revolution in real time.

That's how big I think it's going to be. And so when we think about how's that gonna change our world, that's what we're talking about. So whether so I'm a little bit of a of a of a history buff, we had the agricultural revolution. We had the industrial revolution. We've had what you wanna call the computer digital revolution.

And what we're having with AI is on a scale similar. It is a world changing technology.

So Again, we've heard a lot about it. It really got big about fourteen months ago, November thirtieth of twenty two, when Chat GPT four o came out. People have gotten very excited about it.

But this is really the impact that it's had. And I love This is kind of a line chart on time it takes to reach a hundred million users.

So Second from the bottom is Uber. I love Uber. It's fantastic.

If anyone has kids and try to explain to them what a life was before Uber, we would walk outside and we would raise our hand and a car would come by and hopefully take us where we wanted to go versus now, you know, we on our on our phone. Just ask for a car to come and take us where we wanna go. It took Uber about six years worldwide to get a hundred million users.

At the top, Chat GPT took about two months. This has spread all over the world. Everyone has it.

Everyone in this room can use it. It's twenty dollars a month, I think, is the most basic And, again, whether it's barred, it's it's not an advertisement for any particular product, but, you know, whether it's chat GPT, whether it's barred, everyone can use it, it will make your life easier because it just accelerates everything that we do. We're talking about it more Obviously, there's a lot of stats about how it's being leveraged.

This is slide number three I'd like you to keep.

And the big statistic is right here.

Genative AI It's kinda funny they stopped at nine hundred and fifty million because I would have rounded up to a billion. I think it sounds better. But genitive AI is to create nine hundred and fifty million jobs around the world by two thousand and thirty.

The challenge, underneath it, it will probably destroy or automate about eight hundred million jobs.

So if I I just presented you a technology that I said would create a hundred and fifty million new jobs around the world, everyone would say Brian, you're a fantastic work raid you can be on the cover of Time magazine.

The challenge is it's going to be very disruptive.

It's just going to change. Again, there's eight hundred million jobs that are gonna be destroyed, nine hundred and fifty million they're gonna be created. The other point that someone brought up earlier, the impact Goldman Sachs thinks that AI could raise global GDP by seven percent.

It's fundamentally gonna change our world.

So when we think about just cases that people are using, again, just wanna share whether it's content generation, data extraction, content summarization.

Me personally, I love content summarization.

I have chat chat GPT read my emails and tell me if I'm interested in reading it. So, again, it's just think about it as an electronic employee that just operates at an incredibly fast pace.

I don't wanna steal my thunder for my last comment, but really think about again, whether it's automation, re robotic process automation, whether it's generative AI, it's just another employee.

That is just able to do work really, really fast.

But there's need to be guidelines.

Right? I don't know if people are familiar. I will ask for a show of hands on this one, and because I think it's fun. Has anyone heard So raise your hand if you've heard that generative AI hallucinates.

So it does because it's a computer program, and if it can't find the answer, it makes one up.

And so again, as has been said many times in the past, trust, but verify.

So you can ask I mean, share with you real quick how I found out about generative AI was a new story in my local paper, which is the Washington Post, but it was about the fact that teachers in high schools these are seventeen and eighteen year old students, but the teachers could not differentiate between papers, essays that were written by students and that were generated by Chat GPT.

That's how good it can be. So what's happened is it's just the world that we're going to so think about everything you write.

In the next couple of years, you're gonna spend much more of time being an editor than being an author.

ChatGPT will generate eighty five, ninety percent of the content. You'll just improve it.

So we need to we just need to have guardrails in place. So whether it's the model selection, we always wanna have humans in the loop. And so the idea being there are things that humans do well, and there's things that machines do well. And the things that machines do well we should have them do it because the whole idea is we pay these really bright people that work for us.

To do really low IQ activities.

So what we are trying to leverage with automation with generative AI is just move low IQ activities off the plates of high IQ people so they can do the things that humans are really good at.

And again, a number of different cases doesn't matter what industry you're involved in.

Everyone's gonna be touched. If you think your industry is not gonna be touched by this, are incorrect. It's gonna touch everything, you know, whether it's in in data, whether it's in customer service, it's in business ops. Again, it's just we're going to increase our efficiency, our productivity by leaps and bounds.

And again, all different kinds of applications that we can have, again, financial stress testing, advanced forecasting, You know, when we think about empowering FP and A, again, all these different functions that we can do natural language. I'm a huge fan of natural language, we probably again, I make broad assumptions. I will assume that most people in this room leverage natural language processing at home. If you have Alexa or Siri, that's what it is. You ask a question. There's no coding involved.

I would guess feel free. If anyone's in the room, either grab me, you you can share it right now or grab me when through the day. If anyone is using natural language processing at work, I would love hear about it. So we've got technology that we have at home that we don't use at work.

So I think that's one of the things that are gonna be changed. Because why Should we have to run a report when I should have the ability? Siri, tell me how many, you know, you know, what were my sales numbers by SKU, by store number, by product, by geo by channel. We should have that available to us, and we will.

We haven't had it because humans can't do it fast enough.

AI can.

So really in conclusion, my fourth slide that I think is worthy of taking away Just remember, AI is not gonna replace people.

People who leverage data analytics in AI are gonna replace those that don't.

So to keep us on schedule, those were my comments this morning. Thank you so much for your attention. Have a great rest of the day. In Corta, thank you so much for the invitation, and I wish you all well.