AI for Growth with Cliff Farrah

Explore how AI is reshaping revenue growth strategies in this insightful conversation with Cliff Farrah, Accenture's Chief Strategy Officer for Corporate Strategy and Growth. Here’s what’s in store:

• AI and Human Expertise: Cliff shares his journey from initial skepticism about AI's impact on careers to recognizing its role as a complement to human strategists. Much like doctors interpreting scans, experienced professionals will remain essential in leveraging AI for strategic decision-making.
• Game-Changing Investments: Learn about Accenture’s collaboration with NVIDIA and how their AI initiatives are driving unprecedented efficiency gains, cost savings, and creativity in marketing strategies.
• Support for Midsize Businesses: Discover how AI is becoming accessible to smaller companies, offering tools to enhance operations and compete effectively—without requiring massive budgets.
• Preparing for the Future: From educational institutions to corporate training, we discuss the critical role of upskilling professionals to thrive in an AI-driven landscape.

This episode dives into the opportunities and challenges of integrating AI into business, offering practical insights for anyone navigating the rapidly evolving world of strategy and growth.

Always growing.

Benno Duenkelsbuehler

CEO & Chief Sherpa of (re)ALIGN

reALIGNforResults.com

benno@realignforresults.com

Chapters

• 0:02 The Future of AI in Growth
• 11:21 The Power and Challenges of AI
• 24:28 Unlocking AI for Mid-Sized Businesses

Transcript

Speaker 1: 0:02

Hey, welcome to the Third Growth Officer Podcast, where we talk about all things growth, yes, even and especially those hard parts where you shed some skin and pick yourself up by the bootstraps. Hey, I'm Benno Dunkelspüler, Growth Sherpa and OG Hashtag Growth Nerd. We're on a mission to redefine success inside and outside the business, one TGO episode at a time.

Speaker 2: 0:33

Hi, I'm Cliff Farah. I'm the Chief Strategy Officer for Corporate Strategy and Growth globally at Accenture and I'm in Florida in the United States.

Speaker 1: 0:43

All right, Cliff, thank you so much for coming on a second episode. You and I did episode number 68 a couple of years back where we talked about the book that you had written, Growing the Top Line, and it was shortly after that, maybe a few six months or so after that, that you sold your consulting practice growth consulting practice to to accenture right we, yep, we were.

Speaker 2: 1:07

We were acquired two years ago by accenture into the corporate strategy division.

Speaker 1: 1:12

Yeah, yeah, so, um, we're going to talk about ai and ai in the world of revenue growth and growth strategies and, uh, when you and I talked a month ago or so, you were telling me this lovely story around an aha moment you had about AI and sort of the various stages of tectonic shift, sort of industrial revolution-sized tectonic shifts both of us have seen in our lifetime. Despite what our kids say, you and I have not witnessed the industrial revolution.

Speaker 2: 1:54

Well, haven't we? No, yeah, no, look, I think you know it's interesting. I think the conversation we were having, benno, was that in our lifetimes, you and I, we've lived through really transformative moments, uh, in business and and and in industry. One was, uh, you know, this shift from analog to digital, right like like we go that far back where we grew up with rotary phones and they became digital, and it was transformative and it really kind of moved us forward. We saw the advent of the smartphone and the implications of the smartphone in our world. We've seen amazing advances in medicine in our lifetimes, man on the moon and now reusable rockets that will land in a, you know, in a, in a, in a really tight landing zone. And so you and I were talking about AI and, you know, is it real, is it here to stay, is it impactful? And and the story I told you really had a lot to do with one of the one of the charters I have at Accenture is I lead what's known as growthai, which is our investment. We'll talk a little bit, I guess, about Accenture's investments in AI and generative AI technologies. As a company, I've been tasked over the past couple of years in developing tools for the growth strategy practitioner that leveraged generative AI technology and sort of our own unique proprietary data set that we've developed over time and it's you know, it's sort of an astounding thing when you see this capability live and you think about where we spent a good chunk of time as professionals in this craft over our careers, how quickly it's really made obsolete or commodity things that are efficiency driven right, but that's not what I think is super powerful.

Speaker 2: 4:02

I chatted with you a little bit about the moment the team delivered the first working prototype. For me it was a Friday afternoon. My anniversary was that weekend. Um, one of the team members, uh, uh, a brilliant, uh, developer, uh, who was working with us, she said hey, hey, look, you know, early anniversary present for you. And, um, I, I saw what the machine was capable. You know what the application was capable of. Right, our toolkit was capable of.

Speaker 2: 4:31

And, um, my heart rate, which usually runs at a really calm, cool 60 beats per minute, right jacked up to about 135 and it stayed there most of the weekend. I couldn't sleep. I, I was convinced that, uh, you know, my children were doomed to careers that were going to just be you know, things that I couldn't conceive of because of how transformative it was, and it wasn't so much the analytical capability of the AI. I sort of expected that, just given experience in deep learning and machine learning algorithms that I've been part of over my career. It was the prescription that it was able to do right. It would analyze and then it would prescribe and the and the, and the strategies, and the growth strategies that it was able to produce had the ring of truth and they were very aligned with, uh, you know what, what we might generate as practitioners, as experienced practitioners, and so that's what spiked my, my heart rate. And then, um, uh, I had this moment of epiphany, uh, on on Sunday night and, uh, my heart rate went back to 60 and I fell asleep and slept like a baby. And it was this and it goes to those milestones that we saw, and I likened it to healthcare in my head.

Speaker 2: 5:51

You know, when we were kids, there were x-rays, right, we fell off a swing set or we fell off a slide and you know, we hurt our arm. We'd go get an x-ray. And then, you know, there was ultrasound, and then there was MRI, and then there was CT scan, and then there was nuclear PET and then the software algorithms that would overlay some of the diagnostic, created 3D and color images and really allowed extraordinary insight into the pain that we were in. But there was always a doctor involved, right, there was always someone to interpret for us. There was never the technician never prescribed us, you know an approach. It was always a trusted advisor. And I think that's true about you know strategy practitioners, growth strategy practitioners who leverage AI capability in the future, which will be all of us right, um, our role will will revert to what I think are the most powerful contributions we make, which is not slide editing or, um, you know uh, uh you know, uh, the analytics that that we expect to run in the normal course of of delivery.

Speaker 2: 7:02

Um, it's, it's really the interpretation and the and the joint creation of treatment plans with our clients that are achievable, that that are where we're going to focus. So that was my, that was my story about this, but the game has changed and, uh, we'll, we'll talk, I'm sure, a bit about how we're approaching it.

Speaker 1: 7:20

So Accenture has made mind-boggling investments and thank you for sending me down one rabbit hole. I went down seven different rabbit holes. I spent several hours researching what Accenture has done with AI. I've listened to Phil Donish. What is his name? Hold on a second.

Speaker 2: 7:51

There are only 740,000 of us here, I know, I know.

Speaker 1: 7:56

I'm sorry, Paul Daugherty and James Wilson, also authors of the book Humans Plus Machines. That was a fascinating webinar under I think it was under the Harvard Business Review sponsorship and Accenture's sponsorship, taking your AI expert pool at Accenture from 40,000 to 80,000 people, which I think is from like 5% to close it to 10% of your workforce.

Speaker 2: 8:33

Yeah.

Speaker 1: 8:34

Talk a little bit about that investment.

Speaker 2: 8:38

It's legitimate. There are a lot of announcements that are made that are paper announcements, not public relations announcements.

Speaker 2: 8:47

Yeah, not this uh, not, this got quite a few forums. We, we, we are investing in the technology. It's our, in fact, we're investing in our baseline knowledge and understanding as as practitioners of the of the technology. And then, uh, we're we're investing quite a bit in developing use cases and our own value unlocks in every one of our functional areas of the company. So there's literally not a part of the company that is untouched.

Speaker 2: 9:16

When you think about generative AI and the potential value it can add to us as practitioners, I actually think your number's low. I'm sure it's a good stat, but if you're a part of Accenture now and you're not fluent in generative AI, you're probably an outlier as opposed to someone that's on the vanguard. You know someone that's on the vanguard. The funny story I have to tell is that when we were talking with Accenture about potentially joining the company, one of the value propositions I had was that I believed I could build an app based on the framework in the book. That would, you know, create good growth strategy, because there are only so many ways you can grow, and we've done, I think, a good job bounding that problem, and so I was pitching an app as part of our value proposition and there was real interest and appetite and co-investment in it and investment to build it out.

Speaker 2: 10:22

That has not only been the case. We have built out this capability now under this umbrella called growth, now called growthai, and the toolkit there, but it's far beyond anything that I could have offered using our growth framework. So it's, you know, it's an area that we have gone through all of the classic process that our customers are going through, which is first getting smart on the technology, being relevant in the technology, moving into proof of concept and prototyping, lots, of, lots of work, sort of training out just the capability, proving the capability. So it's kind of like the first step and then really, this phase that we're in now is the inference phase or the deployment phase, where we're seeing the actual value and that's quite powerful and it's really, really exciting to be a part of.

Speaker 1: 11:21

I try to put the published numbers. I'm sure there's a lot of to your point, about 40,000 to 80,000 people at Accenture being AI experts, whether that includes you or not, whether that's in department, you know.

Speaker 2: 11:42

However, you might, you might be, you know, maybe that stat really talks to you. Know developers and coders that are creating the engines potential Yep yeah. But I think, when you look at the strategy team and our advisory role and how you actually make money using AI, which is the real challenge right, that's. The real challenge is how do you make money at it I think that number is much larger.

Speaker 1: 12:11

Yep, yep, but I was just still fascinated by the published numbers of, you know, three billion dollars over three years. So a billion dollars seemed like it was around 10 of your cash flow or profit a year, which is a very significant investment. Uh, you know, if you put it as 10 of profit, uh, for any size company, that's a significant investment, right? And I read studies that are as bullish as saying the effect of AI on GDP growth rates is to double growth rates. So if an economy runs, you know, grows at 3% without AI, it would grow at 6%, with AI being evenly adopted, or adopted throughout the economy.

Speaker 2: 13:04

So it is staggering right, the hypothetical value of AI. Is that what you're saying? Yeah, at a GDP level. Yeah, look, I think the assumption of even deployment and the an economy is is a really bold uh it's a faulty assumption, right, it's an ambitious aim.

Speaker 2: 13:28

There are, there are there clearly are um situations where the value of uh ai is is absolutely transformative, right? So when you look at the use case I think Accenture's done over now 3,000 deployments of systems. When you look at the actual you know, efficiency gain, functional gains they're amazing. We've got lots of published data on it. You can research it. But in my own world I can now deliver a project in domains that we serve and have served in the past in a 30% to 50% more efficient model. And yet the challenge we face is the same challenge that every one of the companies that's adopting AI faces right now.

Speaker 2: 14:27

So, uh, so, ben, if we go, if we go to a client and, um, we say we can, we can make their Salesforce 30 to 50% more efficient at their jobs. Would you know a client of scale, decrease headcount by 30 to 50%? No, they just won't. And they and they won't because we don't trust the technology. Yet they won't because if they're a publicly traded company, they'd have to explain to the, to the market, why such a drastic shift in their workforce happened.

Speaker 2: 15:02

It's highly unlikely that the investor community is smart enough about the potential impact that they're going to reward them for that kind of behavior. Yet frame, I think, where measurement, reward systems and investor mindset has to align with the realities of an AI enhanced world. So, in my example, if I told a consultant working with me at Accenture a year ago that, hey, I'm going to take away 30% to 50% of your chargeability because we're more efficient now, they'd probably run for me, they wouldn't want to work with me at all. Right, because they're measured on on on chargeability. And so there is this natural transition that we're all going to be working through, uh, as we embrace and explore and understand the power of uh, of AI. Um, that, that, I think, is uh, is natural and to be expected.

Speaker 1: 16:07

And and, of course, just uh, well, uh, let's talk a little bit about um, about um AI refinery. I was watching um a little video on Accenture, about a partnership that you entered just, I think, last month with NVIDIA, where a case study or proof of concept, they were using a marketing example, um, where a uh ai functionality and ai processes reduce the manual steps by 30 to 40 percent or 25 to 35 percent something like that six percent cost savings and 25 to 55 percent faster speed to market, which you had mentioned a minute ago, right?

Speaker 1: 17:00

So those are staggering efficiency gains. Whether that's going to be passed on to the outside world immediately or not is also a matter of how you know there are investments to be made before you know. You have to pay for those savings before you get those savings Right.

Speaker 2: 17:24

Yes. So a couple, a couple of um, uh, high level thoughts about this right. First off, yes, we, we made a big announcement with uh in video. We're very excited about it. Um, you know the, the leadership role that we're playing in AI is not just technical. It's also sort of successfully deployed use cases driving economic return for our clients. That's good for our client, it's good for our partners like NVIDIA, it's good for the ecosystem that serves the AI applications that we're deploying.

Speaker 2: 18:05

When you think about the current solutions that exist in the world and you use marketing as an example and you think about the time spent in marketing, we're only beginning to really understand and dip the toe into the next level of modality that is being brought to the market through AI. So right now, we're all prompt-based, right, we're all type prompts and prompt engineering, which is a super sophisticated word for writing a smart query like a Google query, but it's just, you know, for use with an AI engine or generative AI engine, just for use with an AI engine or generative AI engine. I highly encourage you to go play with the next tier up, which is now sort of text to image. So when you start thinking about marketing and the creative process and you look at the power that a, that uh, a simple sentence, is able to uh drive in terms of efficiency and polished output, um, uh, in creating an image that you might have to work for a long period of time with a uh, you know, with a creative agency, we can now do things where, um, we, we can rapidly prototype using text-to-image technologies and then we're moving into an environment that's going to be voice interface not typed interface and voice-to-video kinds of interface and interactions. And so we're only at the very, very, very early stages of what's possible from a content creation, value creation paradigm. Up to this point, I think what we've seen is an awful lot of classic investment in a new technology that's focused on efficiency and quality, and those are two KPIs, two metrics that are pretty measurable right, like when we talk about value creation at the root of the story. Up to this point, I think at the root of that value creation story has been quite a bit about, you know, about improvements in time to market, improvements in step reduction, count reduction, all that kind of stuff. That's the step that we all kind of went through from analog to digital. Once we're all digital Right, once we're all AI enabled, that will be the new norm, right? So there's this stair step in efficiency that we should expect to see, and then that becomes plateau and that becomes baseline.

Speaker 2: 21:01

Book I wrote is growing. The top line. It's how do we leverage AI and generative AI technologies to create entirely new accretive revenue streams. And the clients I work with, just given their scale, for it to be interesting to them, there has to be nine zeros associated with whatever the improvement is. So when you start thinking about billion dollar revenue based opportunities that, but for AI and generative AI, would not exist, that's actually a very involved and sophisticated problem to solve. So that's where we go. Next. It's a much more uncertain problem to solve and I think it aligns with where the advisory industry as a whole is moving. But yeah, so anyway. So that's where I play and that's what I'm excited about. And so when I think about our current offerings in the market and I look where we're pushing towards, I think you're going to see the revenue side of the profit equation become more and more important as we work with our clients.

Speaker 1: 22:03

Is Accenture offering or is Accenture creating AI tools apps for internal use or also as a subscription model to sort of for clients to self-service?

Speaker 2: 22:23

Yes, on everything. So, when you think about internally, we are 100% in on finding ways that we can deploy artificial intelligence, generative AI, to help make us more efficient and better at our craft. Whatever our craft is right, any, any functional area could be hr, it could be legal, it could be, you know, software generation, it could be growth strategy. Yeah, we also are building uh environments for our clients and uh, we're deploying that toolkit for our clients in the in the process of delivering our work with our clients. So, yeah, we literally are active in every flavor layer of this amazing dish that is called generative AI that's available in the market globally.

Speaker 1: 23:22

Right. So your perspective, your lens, as you know, whether it was in your prior as founder of Beacon Consulting, which you sold to Accenture, or now at Accenture, you're focusing on Fortune 100 companies. I mean, it's primarily the billion-dollar, multi-billion-dollar companies in the United States or globally. Certainly, how do you think about and as an aside to the the thought process around fortune 100 companies? As you said earlier, you know, everything is if it doesn't make a billion dollar difference, it doesn't make a difference, right? Um, so accenture, investing a billion dollars a year into this building the capability, makes total sense. My company, realign, works with small to mid-sized businesses. So we're talking $10 million to maybe $200 million revenue businesses, of which there are tens of thousands, not a hundred, right? And the investment and the thought process is just completely different. Right, when you're running a $50 million company, even if that $50 million company were to be a $5 million profit, 10% profitability and then you put 10% of that, now you're making a half a million dollar investment into AI is the equivalent to the $1 billion a year investment that Accenture is making. So with a half a million dollars, there's less you could do, obviously, than with a billion. How do you?

Speaker 1: 25:14

What is your recommendation to CEOs of these mid-sized? Is your recommendation to CEOs of these mid-sized, small to mid-sized businesses to prepare for AI Like? What are the first obvious things that they must spend time and money on? Let me just I'll have another follow-up after that Are you ready to learn how to evaluate like a Sherpa so you can build new revenues like a Sherpa? So you can build new revenues like a Sherpa? Introducing our growth evaluation workshops where you will learn about growth evaluation concepts and methodologies, problem definition, growth killers, opportunity scoping and goal setting, case studies and group discussions, apply learnings cross-functionally and get a certificate while you're at it, for you, for your company, for your growth growth evaluation workshops. For booking, contact Alexis at realignforresultscom.

Speaker 2: 26:19

Yeah, no worries. So, look, I think there's some good news. When you think about the people who benefit most the organisms, the companies that could benefit most from the use of AI and generative AI technologies it's actually the more average performers that get the biggest yield right. So the C students get more out of generative AI than the A students.

Speaker 1: 26:44

No, wait a minute. Mid-sized businesses are not C students.

Speaker 2: 26:46

Listen, I didn't even make mid-sized in my own company. So I say this I'm not in any way denigrating that community. I mean, that is the lifeblood of innovation in the world.

Speaker 2: 26:59

But I think initially there's this preconception that you have to spend an awful lot of money to be able to leverage AI, generative AI. You know solutions. I don't think that's true. I think there are a number of OPEX-related acquisition models for AI capability that exist today that are super useful in just about every functional area of the business, and really it's just a question of tracking down what's out there at $29.99 a month as a subscription to get yield. Example Adobe does a tremendous job on the text-to-image front for very low subscription fees per month and the impact for a small or medium-sized business with respect to the quality of their, you know, marketing collateral is through the roof. Marketing collateral is through the roof.

Speaker 2: 28:14

I highly encourage you to try Microsoft Copilot. When you're writing a presentation or writing a document or editing an email, a lot of time trying to edit out to improve the things we're creating is tremendously powerful, and then that's true in the coding domain as well. So you're seeing quite a few as a service, subscription-based ways to access the power of generative AI that are not cost prohibitive. Where it gets more expensive, but even that the price is coming down. Where it gets more expensive is when you train on your own data and I think it's super important that, as medium-sized businesses dip their toe in the world of model training, which is really kind of teaching.

Speaker 2: 29:06

So if the current like you know, if GPT 4.0 is the equivalent of a really smart, you know graduate student, right with an MBA and you wanted to get his doctorate in business and on your business, then you would train it on your data and so it would get smarter and the answers get much more specific and more powerful because it's smarter in the topics that you care about and the experiences that you've had as a business. So what you don't want to do is give up that data, put it into the public domain, put it into the general engine, just because it saved you a little bit of money up front in the training process. So I think that's something that companies have to pay a lot of attention to. But I think there are plenty of ways for small and medium-sized businesses to access the power of generative AI and the other thing that I think is true and I was talking at Tulane University and there were a bunch of students from the B school there and we were talking about-.

Speaker 1: 30:15

Your alma mater right.

Speaker 2: 30:18

No, no, I was not able to go there.

Speaker 1: 30:21

I thought I was. Where did you go to school?

Speaker 2: 30:23

My wife and my children all went there, but Okay, and your money.

Speaker 2: 30:27

And my money. But we were talking about the fact that the cohort of students who are graduating now will be really the first cohort that part of their onboarding process at larger companies will highly involve artificial intelligence and generative AI tools that they'll be expected to use in their jobs, and that's going to be supply push from the enterprise companies that are investing in these technologies and they want them to become a standard as a part of business. In four years, the students will be taught in schools. I joked on stage. I said listen, if I ever teach a class here, everything in the class would have to be generated by generative AI Anything that didn't involve a toolkit that lever be generated by generative AI Anything that didn't involve, you know, a toolkit that leveraged AI or generative AI algorithms.

Speaker 2: 31:25

And the reason is I don't want to read shitty papers excuse me, bad papers, right, like I want to read. I want to read well-written, well-articulated, well you know, reasoned positions, and then I want to engage in a dialogue about it right, an advisory dialogue about it. And so I think you're going to see within four years that students are fluent in these publicly available technologies. They'll be fluent in the technologies that companies have invested in helping universities develop curriculums in right and make available for their students, and then I think they will pull through into small, medium-sized business. Some of this AI-driven excellence that's going to be available, that'll become far more mainstream than what people might be experiencing today.

Speaker 1: 32:16

It's going mainstream. Cliff, if I could ask, I actually have like 20 more, maybe 10 more questions that I would like to ask you, but I'm trying to keep it to around 30 minutes because that happens to be sort of at the average commute commuting time that people will listen to and watch a podcast. Thank you so much for sharing your insights, highly educated insights, from one of the biggest, if not the biggest, consulting company.

Speaker 2: 32:54

More importantly, we were rated the best, the best. There you go. Management consulting firm in the world. Bigger is not always better, but better is always better.

Speaker 1: 33:01

Right you go. Management consulting firm in the world. Bigger is not always better, but better is always better. All right, all right. Thank you so much, cliff. If folks wanted to get in touch with you, do they just find you on LinkedIn or?

Speaker 2: 33:11

Absolutely. Feel free to reach out. I'm happy to you know, engage and answer any questions you might have.

Speaker 1: 33:16

Excellent. Thank you so much. We will. I look forward to maybe our third podcast a couple of years from now again.

Speaker 2: 33:24

Can't wait, ben, I'll always enjoy it All.

Speaker 1: 33:25

Right, man, appreciate you having me on.

Speaker 2: 33:27

Thank you, thank you, Neil Bye.

Speaker 1: 33:33

Thank you for listening to this episode of TGO Podcast. You can find all episodes on our podcast page at wwwrealign4resultscom. You can find me, Benno, host of TGO podcast, there as well. Just email Benno B-E-N-N-O at realign4resultscom. Let's keep growing.