• You've heard of generative AI, but agentic AI might sound a little less familiar.
• Major industry players are working on AI agents for what some say marks the third wave of AI.
• But what exactly is agentic AI? Here's a quick rundown of the tech everyone's talking about.

Generative AI has been the talk of tech for a while now, but tune into your favorite business podcast and you'll probably hear a different phrase tossed around: "agentic" AI.

So what's the difference?

The two are closely related. You couldn't have agentic AI without generative AI. Definitions vary, but in general, agentic AI refers to AI technology that's capable of performing agent-like behavior that can autonomously accomplish complex tasks on your behalf.

Companies working on AI agents say they are intended to one day be digital coworkers or assistants to human workers in fields spanning from healthcare and supply chain management to cybersecurity and customer service.

Here's how some Big Tech companies explain the concept:

• Nvidia's definition says agentic AI "uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems."
• IBM says agentic AI is a system or program with "agency" that can "make decisions, take actions, solve complex problems and interact with external environments beyond the data upon which the system's machine learning (ML) models were trained."
• Microsoft says AI agents "range from simple chatbots, to copilots, to advanced AI assistants in the form of digital or robotic systems that can run complex workflows autonomously."

Some leaders in the field say agents are ushering in a new frontier in AI.

"In just a few years, we've already witnessed three generations of A.I.," Salesforce CEO Marc Benioff told The New York Times earlier this month. "First came predictive models that analyze data. Next came generative A.I., driven by deep-learning models like ChatGPT. Now, we are experiencing a third wave — one defined by intelligent agents that can autonomously handle complex tasks."

Salesforce, which launched its Agentforce suite earlier this year, has said it plans to have more than 1 billion AI agents in use for companies by the end of next year.

Google CEO Sundar Pichai recently said the company has been "investing in developing more agentic models" over the last year. (He defined agentic AI as being able to "understand more about the world around you, think multiple steps ahead, and take action on your behalf, with your supervision.") The company made agentic AI a major focus of its Gemini 2.0 launch this month.

OpenAI plans to launch an AI agent code-named "Operator" in January that would be able to use a computer on a person's behalf to do things like write code or book flights, Bloomberg reported last month, citing two people familiar with the matter.

The company previewed its latest AI model, o3, on Friday as the final announcement of its 12 days of "Shipmas" campaign.

• KPMG's head of AI, David Rowlands, is helping the firm transform for an AI future.
• He spoke with Business Insider about the barriers businesses face as they try to do the same.
• Don't focus on single-use cases for AI and sort out your data, he advised.

KPMG, one of the Big Four consultancies, has weaved AI into all its operations and is advising global businesses about how to do the same.

All employees across the firm's three divisions — accounting, tax, and advisory — have the ability to use AI. Everyone has access to a form of GPT and roughly a fifth of the global workforce have Copilot licenses, David Rowlands, KPMG's global head of AI, told Business Insider.

"Whatever they were doing already, they can now do quicker," he said in an interview.

But the vast majority of companies are still on the adoption path, and clients who come to KPMG are still thinking about how to get it going and how to get the data, Rowlands said.

Clients' concerns about AI have shifted over time: First, it was ethics, hallucinations, and trust; the past four or five months, it's been about realizing the business case and enabling the workforce to adopt it; and next, it's the question of data and how organizations differentiate through their data and protect it.

BI spoke with Rowlands about KPMG's own adoption journey and how the firm advises businesses as they deepen their use of AI.

One of the biggest barriers for companies to overcome is the focus on single-use cases for AI systems.

Many businesses are deploying an AI agent to sit over a curated database and pick out data to make rapid recommendations to a human operator, he explained. But systems must have reusability.

"What you have to think about is having AI embedded in your operating model," he said. "At KPMG, we're keen to get people beyond use cases because a point piece of technology, a point use case, hasn't been a particularly effective business case."

Clarity on the business case is also the best way to see a return on investment, he added.

The question of returns has been a hot topic among CEOs as billions of dollars continue to pour into AI infrastructure. Some economists and analysts have warned that money is being wasted on hype, while others have said the rate of improvement is slowing and AI is hitting a wall.

KPMG is buying into the hype. In 2023, the firm said it would invest $2 billion in artificial intelligence and cloud services in partnership with Microsoft over the next five years and expected the strategy to generate more than $12 billion in revenue over that period.

In November, it announced a $100 million investment in Google Cloud, which it said could drive $1 billion in growth.

Rowlands said it's hard to get clients to see the wider impact when they can't see an immediate ROI. But he said the benefits would come through improvements in growth, quality, and agility: "We already see that a copilot system saves about 40 minutes a week."

In mid-2024, some of KPMG's surveys on returns were "ambivalent," but they're now "getting some anecdotal evidence of ROI," Rowlands said. This time next year, he added, COOs and CFOs are going to be positive about the returns they're getting.

Data will differentiate your business

How to approach data is another barrier for clients in their AI journey, Rowlands said.

"Organizations will be increasingly differentiated by the data that they own," he said. That requires becoming more mindful about where your data sits, who owns it, where it's generated, and how you keep it up to date.

Data will only be more integral as we enter the next stage of AI's evolution, Rowlands added. He expects that within the next 12 months, multi-agent models — a group of specialized AI agents that coordinate to solve a collective goal —will rapidly become a reality.

"That is where AI is going to start to have a big impact on solving some of the biggest problems, such as decarbonization," he said.

Preparing the workforce for these changes is part of implementing AI responsibly, Rowlands said.

KPMG ran a "24 hours of AI" training session in January this year. The key message was that everyone should know how to use AI against their problems and be trusted and innovative with their use of it in front of clients. The firm is continuing to train its workforce in data curation, looking after data, and prompt craft.

Rowlands doesn't deny that AI will have a "deep transformational impact" on the professional-services industry. He said there would be a rotation of jobs, as happened with the internet, but it wouldn't diminish consultants' purpose.

"We don't really think about replacing jobs. It's more about enhancing individuals and roles. And those who are using AI well are being more successful than those who aren't.

"Our consultants will, as they've always done, strive increasingly to make sure that our clients are getting valuable outcomes out of our work."

• Finance firms are keen on AI agents that can automate combinations of tasks.
• Demand for AI agents is giving birth to a new class of startups and VCs hungry to invest in them.
• It was a topic of conversation at the Evident AI Symposium in New York on Thursday.

"Talk to this like a teammate and treat it like a teammate."

That's Danny Goldman's guidance to private-equity customers of his startup, Mako AI, which offers a generative AI assistant for junior finance professionals and is backed by Khosla Ventures, an early investor in OpenAI.

His hope is that "engaging with Mako looks much more like engaging with a real human associate than a software tool," he previously told BI. Goldman, who worked in private equity before cofounding Mako AI, predicts that in a year or two, every junior on Wall Street will have their own AI direct report.

It's not just juniors, either. JPMorgan CEO Jamie Dimon, is a "tremendous user" of the bank's generative AI assistant suite. Teresa Heitsenrether, JPMorgan's chief data and analytics officer, said at a conference last week that JPMorgan is working toward giving employees AI assistants that are specific to them and their jobs.

Wall Streeters, say hello to your new coworker. Across the industry, AI agents are beginning to permeate the labor force as assistants who can help humans prep for meetings, write their emails, and wade through troves of information to answer questions almost instantaneously.

In many cases, AI agents are still limited to specific, individual tasks like querying internal data and creating PowerPoints and emails. To take AI agents a step further, technologists and startup investors are fueling a shift to so-called multi-agent systems that coordinate several AI agents to complete more complex tasks more autonomously.

Some tech executives at the Evident AI Symposium said they could see a world with more artificial intelligence agents than humans by 2025. But what will work and life look like in an increasingly hybrid world with humans and bots? Well, that's still being worked out, according to a number of tech executives at the Evident AI Symposium Thursday.

"What's really exciting about agents is that we are still figuring out the tasks they're actually good at, the tools they know how to use, the tools we have to teach them how to use," said Gabriel Stengel, cofounder and CEO of Rogo, which is building the generative AI equivalent of a junior banker.

Another question that still needs to be answered is how to define when an agent is smarter or not than a human, said Kristin Milchanowski, chief AI and data officer of BMO Financial Group.

To some extent, benchmarking humans against AI agents is already happening. In a recent University of Cambridge study that compared who could run a business better, AI outperformed humans on most metrics including profitability, product design, and managing inventory. But they fell short when it came to making decisions on the fly.

Heitsenrether, speaking at the Evident AI conference, told the audience that, over time, she expects AI to be seamlessly embedded in an employee's workflow. By this time next year, she said that she hopes to have a clearer picture of what a more personalized AI assistant for each employee might look like.

But unlocking more autonomous uses of AI is going to require more than technological breakthroughs.

"We don't have a lot of trust right now in these systems," Sumitra Ganesh, a member of JPMorgan's AI research team, said at the symposium.

"We have to slow-walk it to release it to people who are experts who can verify the output and go, 'Okay, that looks fine, you can take that action,'" Ganesh said. "But that's kind of babysitting these agents at this point," she added. "But hopefully, it's like training wheels — at some point, we will be confident enough to let them go."