Generative vs Agentic AI: What’s the difference?

If you’re still reading after that headline, there’s no need for a cautionary Nerd Alert. We’re all nerds now. Welcome to the future.

In this post, we look at recent developer events from Microsoft and Alphabet Inc. featuring commentary from both companies' chief executives.

At Microsoft’s 2025 Build conference in Seattle and Google’s I/O in Mountain View, Calif., the term "agentic AI" emerged as a dominant theme. "Agentic" means "acting as an agent." It’s such a new term Apple’s spellcheck doesn’t recognize it.

Agentic AI stands apart from the more familiar generative AI, which has captured mainstream attention through tools like Midjourney, DALL·E, GitHub Copilot, Canva AI, Claude and ChatGPT — platforms that let everyday users generate text, images and video from simple prompts.

The conceptual difference is simple:

Generative AI creates media content based on text prompts.

Agentic AI, often using similar tools, solves complex problems with greater autonomy. Generative tools require a human to direct the action, while agentic AI operates with minimal prompting, following set plans to determine actions.

In an exploration of the topic, data collection firm Bright Data explains: “When you scrape LinkedIn with ChatGPT, you’re using agentic AI. When you ask ChatGPT to create an image, you’re using generative AI.

In other words, agentic AI outputs “job status: complete,” while generative tools produce content — text, images, voice or video — that’s often shared across platforms, sometimes without clear labeling as AI-generated.

Take Midjourney: It’s an image generator that controversially scrapes the internet for visual and narrative input to fuel its database. The approach has been challenged by visual artists who claim Midjourney and others have violated copyrights; meanwhile, Midjourney claims "fair use." Several major lawsuits are pending against Midjourney and others, including OpenAI, the creator of ChatGPT. Courts in several countries could soon weigh in unless settlements are reached.

The situation mirrors the rise and fall of the file-sharing service Napster, which threw the music industry into turmoil in 1999 when the company circulated digital music online and failed to compensate artists. Napster was sued by Metallica and Dr. Dre (among others) and went bankrupt before rebranding under a model that better respected intellectual property rights.

Anyway. Back here in the future, let’s say we wanted to create a map of this article. The result could look and feel like a real map in the strictest sense, depending on our inclinations, even if the premise is nonsensical. One feeds a text prompt into Midjourney; four visuals result. We pick one and tinker with editorial tools to improve quality.

Let’s try, “Generative and agentic AI are so confusing one needs a cosmic road map to remind us where we are.” We get these:

The captions having been added by a snarky human in post-production. You may hate this. You may love this. Either way, it’s here, it’s likely to stay, and it pays to understand.

Replacing software and coding with agents?

Agentic AI is far more complex than absurd images. It is the application causing fears of society-wide robotic takeovers because AI agents are autonomous. One directive might be, “Solve political turmoil in the Middle East, by any means necessary.” Another might be, “Build me a website.” Both are complex problems. Both require calculated solutions. Both may well be achievable with a minimum of human action.

Tina He, writing for the AI media firm Every, explains agentic AI by examining how someone might buy hiking boots online. A human might be drawn to a blog post titled “Top 10 Hiking Boots,” whereas an agent seeking to accomplish this task would not pay attention to the usual headlines and images associated with that theoretical blog post.

No, the agent would analyze underlying data “by looking for machine-readable structure such as specific product names like ‘Brand X Trailblazer Boot’; key features, such as ‘waterproof’ and ‘ankle support’; and categorizations like ‘hiking’, ‘outdoor gear’ and ‘footwear’.”

“Content designed primarily for human appeal — with compelling headlines and attractive visuals but lacking clearly identifiable product information, features and categories — might become essentially invisible to AI evaluators,” wrote He, adding that “information that is meticulously organized with clear categories (‘ontologies’) and standardized descriptions (‘schemas’) becomes highly visible to AI.”

This potentially upends how the internet works commercially, with wide-ranging consequences for social media companies that often serve as online marketplaces and tend to rely on such traffic and advertising for revenue.

“Traditional advertising is designed to appeal to human psychology,” He said. “In a world rich with agents, your product needs to be positioned for AI comprehension. It's no longer just about brand awareness or emotional appeals — it's about ensuring your digital product is structured in ways that make AI systems confident in recommending it.”

Microsoft CEO Satya Nadella, speaking at Build, believes such agents could replace not only how we shop but also software as well as coding. Microsoft is a lead investor in OpenAI for good reason; Nadella is betting on the ability of AI agents to bypass the kind of work that would (say) create an Excel spreadsheet, because all a human would have to do is ask for an end result, and the agent would assess the data, perform the spreadsheet itself and produce whatever the project required --  be it a graph or Python code or an extensive white paper on XYZ.

Such agents won’t follow human orders the way generators do. It’s more like they’ll move on their own across the internet, over platforms, through software. Microsoft CTO Kevin Scott, also speaking at Build, compared the current era to the first days of the internet when important design decisions allowed experimentation without much oversight.

Scott urged online standards to mimic the past, to allow agents to “talk to everything in the world” or they won’t be able to maximize potential.

“The important thing about them isn’t that Microsoft’s opinion gets expressed, or some big tech company’s opinion gets expressed, or that we’ve won some kind of technical argument,” he said. What’s important, he said in an interview with GeekWire, is to “get to the thing that’s really ubiquitous as quickly as humanly possible.”

Google is likewise betting on AI agents. The search-engine giant recently introduced its Agent2Agent protocol, which is an open standard that lets AI agents communicate and collaborate across systems.

Want more information? Watch this. And this. And this.

They’re training the AI bots on what!?!

Media.com's view on AI is that our mission to restore public trust in online information is more critical than ever, for the simple reason that AI bots are being trained on content from unverified sources. In simple terms: garbage in = garbage out.

With misinformation and disinformation present throughout the internet, the quality of “AI food” fed to supercomputers is at best a cause for concern. At worst, it is lethal. 

As Google and other search engines are now prioritizing AI-generated results over organic search results containing direct excerpts from web pages, it is inevitable that civilization’s quest for reliable information is at risk of being derailed if the AI bots are also being side-tracked with content or data from unauthenticated sources.

When one considers the overwhelming majority of online profiles across the major social networks are unverified, and AI bots are consuming their content and data, the risk of big problems starts to emerge. A lack of integrity in source materials means a lack of accuracy in the results. Media.com CEO James Mawhinney has something to say on the point:

“Policy makers must realize that we are entering a very dangerous phase of human evolution where computers are being trained using data from unauthenticated sources. This includes unverified social media profiles where users have no accountability for what they publish. AI programs are effectively ‘feeding off’ content from sources that these social networks cannot identify. This is why Media.com’s mission is so critical and timely. AI will otherwise magnify the harms caused by misinformation and disinformation.”

Moreover, AI has been around for much longer than the recent hype suggests, in less sophisticated forms. This is why Media.com knows AI is here to stay – because it has already been part of our everyday lives for decades.

Take the calculator. A simple, inanimate object which for many of us lived on our desks ready to work. None of us thought “Hey, why don’t I try using artificial intelligence to solve that math problem?” Instead, we simply plugged in numbers, knowing that the calculator is probably faster and more accurate than we will ever be.

So, AI has a place. It has had its place for years before, and will have its place for years to come. The big questions are “How can AI be made safe?” and “How much damage will it do in the meantime?”

P.S. We asked Google’s AI “personal assistant” (Gemini) to assess. It said this:

“Yes, AI bots, especially automated content creators, can be said to ‘feed off’ social media in several ways. They consume public data, analyze it, and then produce content that can be used to manipulate online discussions, spread misinformation, or inflate engagement metrics, according to researchers at Georgetown and Stanford universities.”

In other words, even AI is worried about AI. Stay tuned.