Welcome to the forefront of conversational AI as we explore the fascinating world of AI chatbots in our dedicated blog series. Discover the latest advancements, applications, and strategies that propel the evolution of chatbot technology. From enhancing customer interactions to streamlining business processes, these articles delve into the innovative ways artificial intelligence is shaping the landscape of automated conversational agents. Whether you’re a business owner, developer, or simply intrigued by the future of interactive technology, join us on this journey to unravel the transformative power and endless possibilities of AI chatbots.
The Era of AI as Chatbots is over, welcome to the Era of AI as Corporate Agents. Don’t believe me? Time for a roll call of corporate pronouncements over the last month:
We are building a business agent focused on helping entrepreneurs and businesses across the world use our tools and others to grow their efforts, reach new customers, and serve existing customers better.
— Mark Zuckerberg, CEO of Meta, 29 April 2026 (source)
We are at the beginning of one of the most consequential platform shifts that will change the entire tech stack as agents proliferate and become the dominant workload.
— Satya Nadella, CEO of Microsoft, 29 April 2026 (source)
The next phase of AI is going from you supply some text to an agent and get more text back, or even you supply a bunch of code and get more code back, to we are going to have these agents running inside of a company doing all different kinds of work.
— Sam Altman, CEO of OpenAI, 28 April 2026 (source)
As AI models have become more sophisticated, we see customers evolving the use of AI models from being used to answer questions in a chatbot-like fashion, to actually automating tasks on their behalf, and to automate process flows within the organization.
— Thomas Kurian, CEO of Google Cloud, 23 April 2026 (source)
The shift from generative AI and the query mode to agentic AI and the command and action mode is leading to another step up in the amount of tokens being consumed.
— C.C. Wei, CEO of Taiwan Semiconductor Manufacturing Co, 16 April 2026 (source)
The market has moved from prompts to agents. That shift is a massive opportunity for us. Customers want systems that can reason, use tools, operate across workflows, and perform reliably inside real business environments. That means orchestration, control, observability, security, integration, and governance.
— Denise Dresser, OpenAI’s Chief Revenue Officer, 12 April 2026 (source)
Platforms and workflows and workloads and automation and agents agents agents and…and…it’s all so very soul crushing. As I mentioned last week, in theory I’m glad that the major AI companies are focusing their attention serving “enterprise” clients, in the hopes this means they’ll do less damage to our childrens’ cognition. In reality, however, the industry-wide pivot toward channeling agentic AI into corporate IT departments does suck some wind out of one’s intellectual sails, at least if you’ve spent the last several years using AI-as-chatbot as means of comparing and contrasting AI with human cognition.
This shift to agents is significant, but what does it mean for our supposed “AI future”? “Prediction is very difficult, especially if it’s about the future,” Neils Bohr is rumored to have said, so I generally steer clear of speculation about the business side of AI (the occasional OpenAI-as-Enron analogy excepted). That said, were I to be hypnotized and interviewed by consultants about what lies ahead for AI, here’s how it might go…
Are you saying AI chatbots will go away?
No. ChatGPT will still be around, and various chatbot interfaces such as Gemini and the like will be inserted (not to say jammed) into a wide suite of software tools we use, whether we ask for them or not. But the efforts of the major Big Tech AI “hyperscalers” will no longer be primarily aimed at improving the quality and usefulness said chatbot interactions with consumer users. The frontier of AI development will be on improving agents.
What about “prompt engineering”?
Not a thing, if it ever was. The fundamental value proposition of agentic AI is that it figures out how to solve problems independently using “command and control” instructions, rather than through dialogue with users. Apologies to those who tried to “Learn The Art of The Ask” because that was time wasted.
Will this put an end to promises of Artificial General Intelligence?
I think so. For the past three years, we’ve had to endure endless claims about how feeding data and adding compute chips to large-language models would lead to some sort of super-sentience, “scale was all we need,” etc etc. But look again at that quote from OpenAI’s chief revenue officer, now the focus is on “orchestration, control, observability, security, integration, and governance.” No time for superintelligence when there are TPS reports to generate.
Does this make you a little sad?
Unexpectedly, yes. While I’ve been steadfast in poking holes in claims that chatbots put us on the fast track to human-level artificial intelligence, the truth is I’ve relished the broad attention that’s been directed toward deep scientific and philosophical questions regarding cognition, consciousness, what makes us human, etc. Agentic AI feels like a pretty hard turn towards the corporate and the technical. Not my jam.
But might AI agents be a form of AGI?
No. No man. Shit no, man. What we’re seeing right now is that agentic AI is potentially useful for multi-step tasks involving large data sets and grappling with relatively objective methods to determine what’s true or false. As Nathan Lambert from the Allen Institute for AI observes:
Frontier labs are investing astounding sums of money in mastering these current foci — i.e. code, terminal tasks, etc. — while starting to push into more diverse knowledge work tasks. These newer tasks encompass specialized domains, such as accounting, law, healthcare, etc. They are still agentic, but require more expertise and often integrations with existing software or domain-specific tools.
Coding, we’re there already. Terminal tasks, to the extent that means “stuff that can only get done on a computer terminal, such as cybersecurity,” also plausible. Finance and accounting? Sure. Healthcare? Well, obviously I have concerns. Law, uh, not really a deterministic profession, as anyone who’s ever tried a case can tell you. Beyond that, who knows. Construction seems safe.
Do you expect AI-in-education enthusiasts will pivot to talking about AI agents transforming learning?
Sigh, yeah. I’ve noticed my professional “education world” lags my professional “AI world” by six to 12 months, so by the end of this year we should see EdTech companies promising us agents that will personalize learning to unlock six sigma gains and blah blah blech. This won’t be any more effective than using AI chatbots as tutors, of course, because the process of learning is just about the least deterministic thing imaginable. But I’m already steeling myself for the delusional hype about agents heading our way.
What would you say you do here?
As you can tell, I’m struggling. Going forward, I don’t want to parse the business plans of AI hyperscalers, that’s not my beat. Will there still be enough on the cognitive science side of AI to cover? Possibly, especially if Gary Marcus is right that new forms of AI are incorporating neurosymbolic reasoning methods. Still, one does have to wonder whether AI is going to end up like email, something ubiquitous in our professional lives yet deeply and profoundly uninteresting as an object of study.
Ugh. Let’s close with some cathartic release.
I recently appeared on a Canadian podcast called Eh I (gotta love it) to discuss the limits of AI in the classroom—you can find our conversation here.
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