Are AI agents changing the rules of business?
Take on Tomorrow
The episode explores the shift from traditional AI chatbots to 'agentic AI' that can autonomously complete complex tasks and transactions. G
Key takeaways
- At Slack, 50% more users are utilizing agentic coding tools than there are actual engineers on staff.
- Anthropic is cited as a leading example where 65-70% of code is written through Slack channels using AI agents.
Main topics
- Defining Agentic AI vs. Traditional Chatbots
- Redesigning Business Workflows
Notable quotes
Code is no longer the bottleneck. Ideas and craft and judgment are the bottleneck.
Conclusion
To capture AI's value, leaders must move past simple task automation a
Transcript preview
Speaker 4 (0:01) There's like an entire class of problems that we didn't think we'd get to address, perhaps sometimes in our lifetime that are now possible because we have these teams of agents at our disposal. Speaker 3 (0:11) Making things work in a technology environment today is going to get easier and easier. What's going to be harder is actually rethinking the way that work has been done for so long. Speaker 4 (0:22) An idea that you had on Thursday can be working product and shipped to tens of millions of users on Tuesday. Speaker 2 (0:31) AI agents are here, working alongside people, solving difficult problems, helping teams innovate, and revolutionizing old ways of working. Speaker 1 (0:42) But only 20 % of businesses are capturing a majority of AI's economic value, according to PwC research. So is your business building momentum around this next wave of AI and truly taking advantage? I'm Lizzie O'Leary, a podcaster and journalist. And I'm Speaker 2 (0:59) Femi Oke, a broadcaster and journalist. And this is Take On Tomorrow, the podcast from Speaker 1 (1:05) PwC. Today, could AI agents transform the way your business works? Speaker 2 (1:16) Shortly, we'll be hearing why Slack, the work operating system, is embedding AI agents into everything they do. But Speaker 1 (1:23) first, to understand the opportunity of this technology, we're delighted to be joined by Joe Atkinson, PwC's Global Chief AI Officer. Joe, welcome to the show. Speaker 3 (1:33) Thanks, Lizzie. Great to be with you both. Speaker 1 (1:35) Okay, we have to start with the basics. I think we need to understand... What makes an AI agent? What is it? And how is it different from the AI tools that many people have already been using? Why does this type of software have so much traction behind it right now? Everybody's talking about agents. Speaker 3 (1:53) Well, I think start with the way we use AI today. Traditional AI tools that most of us are used to include a chat window. We ask it to do something, it provides something back. The agent is a very, very different construct. Think of the agent in the background, just like you would another human worker. It gets an assignment. It gets some rules to follow. It gets some data that's available to it. And it's set off to go find out the answer or complete the transaction. Speaker 2 (2:18) What kind of work can AI agents do, Joe, that would have been completely unrealistic just two or three years ago? Speaker 3 (2:26) Think of an insurance agent that's answering a call from a customer or client, and the customer's asking them something, and they're tapping on the other side into a chatbot to get information. It's kind of the way most of us think about it. But now think of the agent being a technology agent and not an insurance agent. And instead, the customer is providing the input. The agent is making a determination in the background as to what information is necessary to answer that customer's question. They may be referencing policy. It may be referencing data sets around claims adjustment or damage or whatever the information might be necessary to respond to that customer. And then providing the customer not just with information, but with a completed transaction. The way that we experience AI today and the way that AI will continue to function in the future, very, very different. Speaker 2 (3:11) Thank you, Joe. We'll come back to you shortly. But first, to get a firsthand account from a company using these tools in their everyday work, I spoke to Rob Seaman, the general manager of Slack at Salesforce, who are incorporating AI agents into their platform at scale. I started by asking him about how businesses can get the most out of agentic AI. Speaker 4 (3:36) One, I think they have to have an experimentation mindset. I mean, one of the things that's most important is you're not going to get it right from day one. And very often, you know, we are wrong the first four, five, six, seven attempts. And it's about figuring out. how wrong you are as quick as you can in adjusting. And so in that regard, I would say people should have a very liberal approach to deploying agents in different areas and seeing what works. So like sitting around and waiting for the perfect use case is the wrong approach. Have Speaker 2 (4:09) you been able to use agentic AI to transform the capacity at Slack? Speaker 4 (4:14) When we went into the year, we had a goal and a set of things we wanted to achieve in the year. We delivered our entire roadmap in the first quarter for the year. And so it was like, okay, we got to kind of rethink how we do things now. So the interesting thing is code is no longer the bottleneck. Ideas and craft and judgment are the bottleneck. And we've seen that play out throughout all of Slack. And so we've done a number of things. We wanted to increase the overall AI proficiency of the team at Slack. And so we took our entire team, thousands of people. offline for three days to do what we call builder days, all jamming and vibing in Slack and AI to figure out how they can actually improve how they do their work. I mean, what's interesting is we actually have 50 % more users of the agentic coding tools within Slack than we have engineers. And that shows you like our product managers, our designers, our EAs, our HR team, everybody is contributing to the success of our customers. and our product itself. And so we've seen just like a tremendous productivity improvement. So we've been able to deliver more. We've been able to iterate faster and we've had to kind of restructure how we work as a result of it. Speaker 2 (5:23) Let me go big picture, which is why agentic AI will change the way we work. What are the opportunities? Speaker 4 (5:33) The opportunity for agentic AI is ultimately to increase human output and allow us to get back to the things that we are uniquely positioned to do, which is exercise our judgment, our experience, our craft, be creative. You know, these are things that... The agents are not great at right now, and we don't have a path to them being as good as humans. And so I don't see it being about replacing people at all. I see the bull case for this being augmenting people and ultimately increasing the upper bound of what's possible for companies and individuals that work within companies. And so what's interesting, and we see within some of the most advanced customers of Slack that are also pushing the