Monotype is keen for you to know what AI might do in typography. As one of the largest type design companies in the world, Monotype owns Helvetica, Futura, and Gill Sans — among 250,000 other fonts. In the typography giant’s 2025 Re:Vision trends report, published in February, Monotype devotes an entire chapter to how AI will result in a reactive typography that will “leverage emotional and psychological data” to tailor itself to the reader. It might bring text into focus when you look at it and soften when your gaze drifts. It could shift typefaces depending on the time of day and light level. It could even adapt to reading speeds and emphasize the important portions of online text for greater engagement. AI, the report suggests, will make type accessible through “intelligent agents and chatbots” and let anyone generate typography regardless of training or design proficiency. How that will be deployed isn’t certain, possibly as part of proprietarily trained apps. Indeed, how any of this will work remains nebulous.

Monotype isn’t alone in this kind of speculation. Typographers are keeping a close eye on AI as designers start to adopt tools like Midjourney for ideation and Replit for coding, and explore the potential of GPTs in their workflow. All over the art and design space, creatives are joining the ongoing gold rush to find the use case of AI in type design. This search continues both speculatively and, in some places, adversarially as creatives push back against the idea that creativity itself is the bottleneck that we need to optimize out of the process.

That idea of optimization echoes where we were a hundred years ago. In the early 20th century, creatives came together to debate the implications of rapid industrialization in Europe on art and typography at the Deutscher Werkbund (German alliance of craftspeople). Some of those artists rejected the idea of mass production and what it offered artists, while others went all in, leading to the founding of the Bauhaus.

The latter posed multiple vague questions on what the industrialization of typography might mean, with few real ideas of how those questions might be answered. Will typography remain on the page or will it take advantage of advances in radio to be both text and sound? Could we develop a universal typeface that is applicable to any and all contexts? In the end, those experiments amounted to little and the questions were closed, and the real advances were in the efficiency of both manufacturing and the design process. Monotype might be reopening those old questions, but it is still realistic about AI in the near future.

“Our chief focus is connecting people to the type that they need — everywhere,” says Charles Nix, senior executive creative director at Monotype, and one of Re:Vision’s authors. This is nothing new for Monotype, which has been training its similarity engine to recognize typefaces since 2015.

But the broader possibilities, Nix says, are endless, and that’s what makes being a typographer now so exciting. “I think that at either end of the parentheses of AI are human beings who are looking for novel solutions to problems to use their skills as designers,” he says. “You don’t get these opportunities many times in the course of one’s life, to see a radical shift in the way technology plays within not only your industry, but a lot of industries.”

Not everyone is sold. For Zeynep Akay, creative director at typeface design studio Dalton Maag, the results simply aren’t there to justify getting too excited. That’s not to say Dalton Maag rejects AI; the assistive potential of AI is significant. Dalton Maag is exploring using AI to mitigate the repetitive tasks of type design that slow down creativity, like building kern tables, writing OpenType features, and diagnosing font issues. But many designers remain tempered about the prospect of relinquishing creative control to generative AI.

“It’s almost as if we are being gaslighted into believing our lives, or our professions, or our creative skills are ephemeral,” Akay says. She is yet to see how its generative applications promise a better creative future. “It’s a future in which, arguably, all human intellectual undertaking is shed over time, and handed over to AI — and what we gain in return isn’t altogether clear,” she adds.

For his part, Nix agrees: the more realistic and realizable use of AI is the streamlining of what he calls the “really pedantic” work of typography. AI might flatten the barrier to entry in design and typography, he says, but “creative thinking, that state of being a creative being, that’s still there regardless of what we do with the mechanism.”

“Thirty-five years ago there was a similar sort of thought that introducing computing to design would end up replacing designers,” he continues. “But for all of us who have spent the last 35 years creating design using computers, it has not diminished our creativity at all.”

That shift to digital type was the result of a clear and discernible need to improve typographic workflow from setting type by hand to something more immediate, Akay says. In the current space, however, we’ve arrived at the paintbrush before knowing how the canvas appears. As powerful as AI could be, where in our workflow it should be deployed is yet to be understood — if it should be deployed at all, given the less-than-stellar results we’re seeing in the broader spectrum of generative AI. That lack of direction makes her wonder whether a better analog isn’t the dot-com bubble of the late 1990s.

In many ways, it mirrors our current situation with AI. As public access to the internet increased, a wave of dot-com startups emerged and with them increased venture capital, even though the internet at the time “never connected to a practical consumer need,” Akay says. Overvalued and without a problem to solve or a meaningful connection to consumers, many of those startups crashed in 2000. “But [the internet] came back at a time when there were actual problems to solve,” she adds.

Similarly, few consumers exploring AI are professional designers trying to optimize workflow; rather, AI is increasingly the playground — and product — of executives overvaluing AI as they attempt to automate jobs and try to push creativity out of creative professions.

Both Nix and Akay agree a similar crash around AI might actually be beneficial in pushing some of those venture capitalist interests out of AI. For Nix, however, just because its practical need isn’t immediately obvious doesn’t mean it’s not there or, at least, won’t become apparent soon. Nix suggests that it may well be beyond the bounds of our current field of vision.

Nix adds that in our Western-focused view of AI, we might not see the difference in our expansive selection of typefaces and how limited those choices might be for non-Latin scripts, for instance. That, and similar areas outside the Western mainstream of design, may be where the need for change is more apparent. “The periphery may end up driving the need-state [for AI].”

For all that, it remains unlikely that current models of selling typography will change, however. We’d still be licensing fonts from companies like Monotype and Dalton Maag. But in this AI-driven process, these generative apps may well be folded into existing typography subscriptions and licensing costs passed on to us through payment of those subscription fees.

Though, that remains more speculation. We are simply so early on this that the only AI tools we can actually demonstrate are font identification tools like WhatTheFont and related ideas like TypeMixer.xyz. It’s not possible to accurately comprehend what such nascent technology will do based solely on what it does now — it’s like trying to understand a four-dimensional shape. “What was defined as type in 1965 is radically different from what we define as type in 2025,” Nix adds. “We’re primed to know that those things are possible to change, and that they will change. But it’s hard at this stage to sort of see how much of our current workflows we preserve, how much of our current understanding and definition of typography we preserve.”But as we explore, it’s important not to get caught up with the spectacle of what it looks like AI can do. It may seem romantic to those who have already committed to AI at all costs, but Akay suggests this isn’t just about mechanics, that creativity is valuable “because it isn’t easy or fast, but rather because it is traditionally the result of work, consideration, and risk.” We cannot put the toothpaste back in the tube, but, she adds, in an uncertain future and workflow, “that doesn’t mean that it’s built on firm, impartial foundations, nor does it mean we have to be reckless in the present.”