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Re-skill for AI
TIM RYAN: Just get in the game. Knowing this is gonna be a game that goes on for a long time, don’t rush, build the foundation. This gets to responsible AI.
What data are you using? Is that data right? Are the models working? Do you have the right governance, the right access, and the right testing? And our advice is to our clients, knowing you’re eventually gonna need to do this, do it upfront so you have that foundation there. That’s critical before you try to scale it.
BOB SAFIAN: That’s Tim Ryan, Chair and Senior Partner of PwC — the global professional services network that recently announced a $1 billion investment in AI, in part to re-train their 65,000 person workforce.
I’m Bob Safian, former editor of Fast Company, founder of the Flux Group and host of Masters of Scale: Rapid Response.
I spoke to Tim on this show last year, after PwC launched a multi-billion dollar employee engagement platform in the face of the Great Resignation. I wanted to talk with him again because, with the new initiative to embrace AI, PwC is taking the next step in the journey to re-skill its team.
Few business leaders meet with as many CEOs, across as many industries, as Tim. And so I also wanted to hear from Tim about what those leaders are both preparing for and hesitant about when it comes to the AI revolution.
SAFIAN: I’m Bob Safian. I’m here with Tim Ryan, chair and senior partner of PwC US. Tim, thanks for joining us.
RYAN: Bob. It’s great to be with you. Thanks for having me.
The impetus to PwC’s billion dollar commitment to AI
SAFIAN: So, you were on the show about a year ago, talking about a big investment you’d announced in a new tech platform for your workforce. More recently, PwC committed to another investment — this one, a billion dollar commitment to build and enhance AI capabilities. AI’s become the buzzword of the year. Fascination, fear, hopes, hype. How did this new investment come to be at PwC? What was the impetus, the idea behind it?
RYAN: So I’m actually gonna go back five years ago. Our people were worried about their relevance as the world was getting more digital. And so we made a commitment to our people, and we launched a program that internally we call “You Are Tomorrow.”
We said, we will not leave you behind unless you choose to be left behind. And we invested in teaching our people about bots, how to build automations, how to use visualization tools, how to use data. It was so successful, we shared it with the outside world. We called the Skills to Society, New World New Skills.
So now fast forward to the announcement you just referred to. What we saw very clearly is the next step in this journey is teaching our people AI. We’re fortunate to have a deep relationship with Microsoft that we have for many years. We’ve done collaboration with them over the past, like cyber and security and our tax business and many others. And with their relationship with OpenAI, we said, this is the time for us to really leverage our Microsoft relationship and the great partnership with them. And we committed to put a billion dollars behind that. That billion dollars really goes to a couple of key areas. One is developing solutions for our clients to do our part to help them stay relevant going forward. And the second part goes right back to what we started five years ago. So another step in the journey, something we’re really excited about.
SAFIAN: For me, when ChatGPT was first released late last year, it seemed like it was sort of a fun new thing. I didn’t realize what the impact was gonna be. Did it take you by surprise a little bit about how quickly this new generative AI has sort of moved through? And, what sort of turned for you about like, oh, now’s the time we have to do this.
RYAN: Clearly, we saw a tipping point, end of ‘22, beginning of ‘23. And for us, it was a question of, how do you scale it. I go back to this leadership lesson of… listen. Listen to your people, listen to your clients. So for us, it was really listening to those two stakeholders. When your clients are bringing up every meeting, when you’re hearing from your people, when they’re asking you what the next step in our journey is, how do they get involved?
Then, you know, it was time. So I had the privilege of going into the world economic forum, and you couldn’t escape without talking about ChatGPT, OpenAI and the like. So, all those different data points told us this was the time to go bigger. Fortunately, we weren’t starting from ground zero, which gave us the confidence to lean into that Microsoft relationship.
How leaders should respond to AI developments
SAFIAN: I’ve been hearing some confusion from CEOs. I’m guessing you have too, about exactly how to respond. Like there’s this imperative to take action to lean in, but some uncertainty about what exactly that means. What are you hearing about that?
RYAN: There’s no doubt the world in general is more challenging today than it was three years ago. If you think about just inflation, Russia, Ukraine, there’s a number of challenges that our clients are dealing with.
They’re under pressure from their investors to deliver better returns. Their customers want more and more from them. And one potential way to deal with some of these pressures is embracing the power of Generative AI. Part of the questions we’re getting from clients is, how do I scale it? Where do I start? How do I do it responsibly? How do I manage the risk? If my business is regulated, how do I manage that complicated risk? But without a doubt, this is the year where we’re seeing more or more use cases. We’re seeing companies that were not involved, they’re wading into the water at this point.
SAFIAN: Yeah, well, because there’s this straddle that’s going on between falling behind as a business or as an industry. And then the potential risks of moving too fast of, you know, getting over your skis in some ways.
RYAN: Without a doubt, there’s this concern about falling behind. But I think pragmatically, much of the world today is in effectively the same place. The reality is, as people embrace and learn, there’ll be things that work, things that don’t work. Our advice to our clients is just get in the game. I think this is one where measured and consistent approach is gonna be better off. The reality is that with the number of resources out there, there’ll be the opportunity to be fast followers. So the big part of advice we’re giving to our clients is: get in the game. But knowing this is gonna be a game that goes on for a long time, don’t rush, build the foundation. This gets to where we focus on responsible AI.
So what we mean by responsible AI is, what’s your foundation? What’s the controls that you have over there? What data are you using? Is that data right? Are the models working the way you anticipated those models are working? Do you have the right governance, the right access, and the right testing? And our advice is to our clients, knowing you’re eventually gonna need to do this, do it upfront so you have that foundation there. That’s critical before you try to scale it. ‘Cause ultimately you’re gonna need to answer those questions.
SAFIAN: Do you have a sense yet whether there are certain functions that will shift to AI faster than others, or whether there are certain industries that might shift faster or is it too early to know any of those things?
RYAN: I don’t think it’s too early. Whether what I’m gonna say turns out to be right or not is another thing. But the way we’ve looked at it is, non-regulated businesses in general will be earlier adopters. So think consumer and other areas, areas that are highly regulated like financial services or healthcare will be slower because of the risk of getting it wrong, right? So you’ll see it in non-regulated businesses. And then the biggest area first is large scale homogeneous, frequently repeated activities. In our business, as an example, we have thousands of team across the country that pull information off of databases. We do like engagement letters, audit opinions. Those today are largely done manually. That is a perfect place to leverage AI.
Now, you’ll still check it and validate it when it comes out, but those are great use cases for AI. You also have areas like call centers, where companies are looking for ways to interact with customers. You have areas like insurance and claims processing and how do you identify the magnitude of a claim. Data ingestion is another area. We worked with a global energy company, where we used AI to do data ingestion as it went from one old system to another system. Those areas where it’s large volumes, repeatable tasks, are really good early day use cases where we see opportunities to leverage the power of generative AI.
How PwC is applying AI across the company
SAFIAN: Mm. I mean, I know PwC comes out of an auditing background and that auditing function is one that we’ve heard about, could be automated. Is that happening to the auditing functions?
RYAN: It’s actually happening across all three elements of our business: auditing, in our tax, in our consulting. So we have platforms that our entire audit business is run off of. And we have artificial intelligence that’s being built right into that platform. If in a typical audit you would test journal entries, and at a large company that’s multinational, it’s impossible to test manually. It’s impossible to test all journal entries. AI gives you the ability to test large populations, which gives investors more confidence in the numbers that they’re using.
Same in our tax business, one of the big things we do in tax is we ingest massive amounts of data off of our client systems to prepare their tax returns, do their analysis, assess compliance with laws and regulations. AI allows us to do that in a more efficient way and increasing the degree of confidence.
SAFIAN: And not that, I don’t need a person anymore, that the AI can just do it for me?
RYAN: Yeah. So no, Bob, we continue to believe that the world will need humans. The reality is, most elements of most people’s jobs, there’s a mundane part. They are right for the use of generative AI. And we see the ability to free up time to do more of the critical thinking, more of the analysis, more of the innovation, more of the softer skills that add value to not only how you feel as a person, but also to the customer. So, our strategy is what we call human led and tech powered.
SAFIAN: When we come back, we’ll hear details about how Tim and his partners are executing on their bold $1 billion investment in AI, and what kinds of industries and companies are best positioned to surf the AI wave. Stay tuned!
SAFIAN: We’re back! Before the break, we heard PwC’s Tim Ryan talk about why his firm is spending $1 billion on AI, and the advice he’s giving other CEOs about how to address the new tech wave.
Now, Tim talks about the undeniable impact of big tech’s ‘Magnificent Seven,’ and why AI could spark broad economic growth. Plus, he shares lessons about building expertise across a team, what kind of business culture enables success in a tech transformation, and how AI can unleash our own personal potential like never before.
Inside PwC’s re-skilling efforts around AI
Part of this billion dollar investment is that you’re gonna retrain and re-skill the whole workforce — 65,000 people starting now. So, do you know yet what that looks like?
RYAN: Yeah, so Bob, yes. One of the things that we bet on five years ago is that if we teach our people to fish, they will be best equipped to apply that knowledge to help our client. Meaning there’s no way you can sit in the center of an organization and figure out every use case. And now this next journey is, every person in our firm will go through the basics of AI.
We’ll teach Generative AI to everybody. What are the risks, what are the benefits, what are some sample use cases? We will have gamification, we will have rewards, we will have short videos that are fun to help them learn it. What we launched last year as part of our new people strategy is a cutting edge learning platform, where every person in the firm can customize their learning journey. What’s now available is deeper AI learnings for those who wanna go deeper beyond the baseline. And then we already have thousands of deep technologists, and then we will also invest in them to take it to the next level.
SAFIAN: I’m not a software engineer or a technologist, and so, while I’m intrigued by these new AI developments, I find myself sometimes struggling with how to become more expert in them myself. I’m curious what you have done to better acquaint yourself with what these new tools can deliver. Is there a personal retraining that’s different whether you’re an executive or do you have to get in the trenches in the same kind of boot camp as everyone else?
RYAN: So I mentioned we have thousands of technologists. I literally have received hundreds, a couple of hundred emails showing me…here’s the research that I did. Here’s where I think the firm should be going next. Every single piece that I get, I read and I study. It has stretched me beyond belief. By the way, some of them also point out the risks and it’s not all one sided.
The second thing is, one of the big reasons I’m on the road almost a hundred percent of the time, is I’m out meeting with our clients and our teams and I’m getting to see what we’re doing in supply chain, in healthcare, in banking, and I’m getting to see those use cases. I sit on a few outside boards and I get the ability to see experts come in and talk to us. And then of course I’m experimenting, right?
I’m experimenting as an individual. We know it won’t be a straight line. We know it’s gonna require more investment. But we certainly know that it is something in order to lead, we need to continue to move forward on.
How AI increases competition
SAFIAN: Investors are certainly rewarding the big tech players — the ‘Magnificent Seven’ as they’re being called now, right? Apple, Amazon, Alphabet, Facebook, Nvidia, Microsoft, and Tesla. It makes it feel like competition is narrowing. I know you’ve said that you feel like AI increases competitiveness. Can you explain how those two things work together?
RYAN: Yeah, I do. I think there’s clearly some companies that innovated the technology. They’re being rewarded because they’re creating the opportunity for all of us to innovate. But then you’ve got the rest of us who aren’t necessarily innovating the technology. I think the playing field is leveled at this point. Like, whoever embraces it, whoever can scale it. And that’s why I love this podcast. This all comes back to management. High quality management teams will win. It’s not, the best technology will win. High quality management teams will win. Those management teams that embrace change, that bring their people along, that know how to implement technology, that know how to make sure you’re getting the right return, the right outcome to do it responsibly. All management teams aren’t created equal. The ones who partner with those seven organizations and not recreate the wheel, but leverage what they’ve done. They’ll be the ones who are rewarded over time.
SAFIAN: Mm. How much do you worry about a shift in the competitive landscape for your firm? I mean, I’ve seen McKinsey’s put out reports, Accenture’s talking about re-skilling, they’re doing, like, how do you gauge where you guys are relative to your own competitive set?
RYAN: We have really good competitors. Like, we operate in a highly competitive industry. But I think it’s remiss to compete purely on technology. It is all about people and technology. And if we’re gonna help a financial institution transform, if we’re gonna help a retail organization look at new ways of engaging with their customers, leveraging generative AI, it is about, how do you bring stores along? How do you bring distribution sites along? How do you bring the supply chain along? And all that gets down to people understanding an industry, which is something we’re very good at.
SAFIAN: It’s a bit of a juxtaposition that at a time where we are embracing a technology that is more human-like and takes on more human tasks, that you are saying, what will differentiate you is the human side of your business, not necessarily the technology side.
RYAN: Yeah. Bob, if I go back right now, I would tell you 50% of our clients have failed efforts that go into the cloud implementing new ERP, implementing new platforms. History is both humbling and an important teacher. I’ve never met a client who have said, I would’ve succeeded if I only chose technology A over technology B, provide A over provided B. I’ve never met one. What I’ve all met is, had I invested more of my people, of how we’re gonna run that bank branch differently, how we’re gonna run our risk management function differently.
That’s the area, when you look back of, when companies succeed or fail, it is all about the people. AI is massively exciting, but 10 years ago, 15 years ago, it was the cloud. And some have succeeded on the cloud and others have found ROI, revenue growth, efficiencies elusive. And the difference between those who have succeeded, those haven’t, is about the quality management, how they brought people along and taught them new ways of working. Think about it, the average life of a Fortune 1000 company 20 years ago, was 34 years, now it’s 17, it’s almost cut in half. But the ones who are succeeding are the ones who are evolving their workforce, the people who interface with customers. So we passionately believe it’s about people armed with the best technology.
SAFIAN: But we’re not gonna have people-less organizations, people-less companies. You’re not worried that there are gonna be fewer jobs or less needs for human… You’re shaking your head no.
RYAN: I’m not, I’m not Bob, because I see growth. The productivity and efficiencies that generative AI brings will drive more growth, and with that growth, people will be put to work. When you look at some of the big macros that are happening, we’re seeing more investment in FinTech, more investment in Cleantech, more investment in climate. So when I look at the big picture, I do see menial tasks going away. I do see massive productivity, and that’s why I’m very bullish on jobs at this point in time.
SAFIAN: And if you have fears or concerns about where AI might lead us, where do those sit?
RYAN: I worry that AI people run to the presumption that it’ll dehumanize us. I do worry about irresponsible use of AI. But most importantly, Bob, I worry that people don’t get on board for their own sake, for their own sake. Like I want an environment where people can achieve their full potential. In order to do that, if they’re not proficient in the tools, and I think a big part of my job and many other leaders is to create that environment where people can achieve their full potential. And if we give them the right tools, the right environment, they will do amazing things.
SAFIAN: Tim, this has been great.
RYAN: Yeah, Bob, thank you very much for having me. And thank you to your listeners as well.
SAFIAN: Listening to Tim, it’s a reminder for me to keep exploring AI’s evolving use-cases in my own day-to-day work.
For someone like me who isn’t engineering-minded, studying AI can feel intimidating. But no matter your experience or your age, now is an ideal moment for growth. To be willing and open to trying new things, to become familiar with even the things that scare us… that’s how we build wisdom in times of rapid change.
I’m Bob Safian. Thanks for listening.