The proof is in the pilot: Why AI process experiments can’t wait, according to futurist Steve Brown

“Are you fascinated by AI and maybe a bit tired of ChatGPT?”, asks Steve Brown, noting the show of hands raised in the audience at One World Trade Center.

The futurist is laying out the case that AI’s enterprise honeymoon is giving way to a proof-of-concept era where trust is essential and use case selection is crucial. Brown, futurist, entrepreneur, and Google DeepMind alum, reassures us that AI collaborators will help us do our jobs more effectively. His advice for companies seeking to leverage AI to outcompete their rivals: Start piloting now.

”If you’re not investing in AI, you’re the one that’s getting left behind,” cautions Brown.In a talk for our Face Value series, Brown draws on a quarter-century of experience in AI and autonomous agents, including tenures as Chief Evangelist and a futurist working in Intel Labs, plus a more recent stint at DeepMind, Google's AI research lab.

• The video, Advantage AI: How to capitalize on the tech shaping our time with Steve Brown is available to watch on-demand. 

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“Remember, today AI is as bad as it's going to be. It’s only going to get more and more capable over the next few years,” says Brown. “If you’re not already running AI pilots and experiments then you need to start doing that.”

One company bucking that trend, he says, is JPMorgan, which has launched a number of generative AI deployments. Others should follow suit, he advises, and that urgency should extend across all 3 dominant AI types now in use: discriminative, generative, and agentic. Let’s take a look at the three models. 

Why the 3 types of AI matter:  Discriminative, Generative, and Agentic

• Discriminative.  “This is classic machine learning,” says Brown. These supervised AI models typically distinguish among different classes or categories within a labeled dataset. Think detecting objects, recognizing faces, distinguishing between words, splitting Netflix viewers into taste groups, and nudging Amazon customers with ‘you might like...’

• Generative. Models that create realistic content – such as text, images, code, or audio – by making use of multimodal large language models and image generators through a technique called diffusion. Think how Dall-E generates realistic images and art from natural language prompts, or how ChatGPT can write, debug, and explain code in multiple programming languages.

• Agentic. One of the latest advances in the field, Agentic AI pushes beyond just classifying data or generating content to independently perform tasks and make decisions through goal-oriented behavior.

How agentic AI tools will drive enterprise productivity gains

“Where we are going next is agentic AI,“ says Brown. “These are autonomous AI agents that can handle complex tasks. They will go away and work on them and come back with results.”

So what will it take for today’s conversational, content-making chatbots to transform into tomorrow’s autonomous AI agents?  “We are all going to have machine co-workers. Those agents are eventually going to start talking to each other. Think of an AI marketing agent that could talk to a legal agent to clear a deliverable. That is where we're headed.” He adds: “Agentic AI models can elevate the customer and employee experiences while opening new pathways for companies to boost operational excellence.”

Brown continues: “These AI agents are coming, and coming fast… The first agents are out now, but they’re not very good. We are looking at a time frame of 2025, 2026 with surveys showing many large enterprises beginning to deploy agents in the next one to three years.”

Addressing AI apprehensions, the futurist says: “We have this fear that AI will be dangerous, that it’s going to take our jobs, or at least make our jobs not very interesting anymore. But the future of work is going to change… It’s going to change in a way that will be initially fun for all of us. These agents are collaborators going to help us do our job more effectively.”

Here are three ways Brown believes agentic AI can boost company operations

• Elevate the customer experience – Agentic AI will level up sales support, customer support, technical support. “Most importantly, it will find new ways for customers to have a conversation with you,” says Brown. As an example, Brown asks his audience to imagine a travel website powered by agentic AI: “Right now, buying a ticket is largely a filtering experience. It’s not very fun… Now imagine a travel company with a front-end agentic AI so when I ask for a flight to New York, it has already learned my preferences in airlines, seating, flight times, routes, and accommodations. It’s like having a face-to-face conversation with a 1970s travel agent. Assuming the price is the same, which of the two companies are you going to invest in?”

• Boost the employee experience, attract top-notch talent – “Think about the productivity of your employees. If you can use AI to offload low-value work and support your employees, elevate their capabilities so they can be more successful in high level work, you’re going to boost the productivity of your organization, improve your business, your employee satisfaction, and reduce turnover,” advises Brown. As job applicants scan the workforce landscape, he warns, they will prioritize companies that invested in agentic AI tools.  

• Achieve operational excellence – “If you’re not using AI to optimize your operations, you’re leaving value on the table,” he says. “There should be an urgency to move forward and start running pilots and experimenting on customer experience, employee experience, and operational excellence.” The futurist believes agentic AI can go much further, with agentic AI machine co-workers that will collaborate with each other to complete multi-step tasks. 

To make the most of AI, businesses must continue to run pilot experiments and trial launches to see which use cases can actually drive the most business growth. “The ability to use AI to differentiate yourself in the market place is high,” says Brown. “That’s why right now you need to be launching trials to differentiate your company, create new value for customers, and leave the competition behind.”

Casey Sanchez

Writer

Casey is a writer at Celonis. He has written about technology, engineering, and finance for Deloitte, Exponent, and Google for Startups. His work has appeared in The Los Angeles Times and as branded content for Wired UK.