“Whether you identify as having a disability or you don’t, at some point in your life, you’re going to benefit from an access feature.”

Maayan Ziv, founder and CEO of AccessNow, wasn’t speaking in abstractions.

She’s talking about a reality that touches the estimated 1.3 billion people worldwide experiencing significant disability, according to the World Health Organization. That’s nearly one in six people navigating daily environments built with varying levels of inclusion, and often, none at all. 

At Elevate Festival in Toronto, Ziv joined Google Canada’s Natasha Walji to talk about how artificial intelligence is changing that landscape. Their conversation traced the evolution of AccessNow from a frustration-born idea to a platform mapping accessibility data in cities around the world, revealing how AI is helping scale that work without losing its human foundation.

Ziv’s message was clear: accessibility isn’t a side project or an afterthought. It’s a signal of how seriously we take participation, and how intentionally we design for it. 

Her story shows what it looks like when innovation starts with lived experience and builds outward.

Building a movement from lived experience

Ziv founded AccessNow a decade ago after realizing how little reliable information existed about accessible spaces. 

“Ten years ago, I was really kind of finding myself in a moment of real frustration,” she says. “I use a wheelchair, and I always need information about accessibility, but realistically, it’s pretty hard to find good answers.”

What began as a small, volunteer-driven project in Toronto has grown into a global platform that maps and reviews accessibility in cities worldwide. AccessNow helps users find accessible places and experiences while working with governments, retailers, and tourism operators to improve inclusion.

Early on, Ziv faced resistance, and suggestions that she focus on philanthropy and addressing accessibility “for good.”

“A lot of people assumed that accessibility was a charity situation,” she says. 

“But I was really set on creating a company that can scale and also educate people on the very viable market and business opportunity that accessibility could lend any company.”

The numbers back her up. Accessible tourism alone represents a $58-billion annual market, yet few companies plan for it strategically: “The goal really is to be able to answer accessibility questions from every place on Earth.”

The ambition to make accessibility information universal eventually led her team to AI.

When AI starts learning from lived experience

In 2019-2020, AccessNow began exploring AI as a way to automate and expand how it gathers, verifies, and interprets accessibility data. 

“We really looked at AI for scale,” Ziv says.

“It really has been a huge way in growing the value that we add, because we’ve been able now to take our vast data that is quite diverse, and focus on very different lived experiences of all different perspectives.” 

Training their models on these data sets, the team looked at key points like image data, sensor data, and when people are in motion.

“We’re able to start to analyze and understand, you know, are those spaces going to be accessible for people before they even get there? And actually let us know if that’s true.”

AccessNow combines crowdsourced reviews with data from partners like Google Maps to create a richer, more accurate picture of accessibility worldwide. It collects data on lighting, entrances, terrain, and even sensor data from mobile devices that track bumps and curbs.

AI makes it possible to merge and analyze these data buckets. 

The one wrinkle? 

“It might get things right, but there might also be some hallucinations involved,” Ziv says. 

“That’s a real problem when it comes to accessibility. Ten years ago, the problem was no data. Now the problem is, there are answers out there, but are they trustworthy? Are they accurate? Do they reflect real lived experiences?”

To ensure accuracy, AccessNow trains its models using verified community data and continually tests results through user feedback. 

“It’s always going to be about our community,” she says. “We’re always checking in. Did we miss the mark, or are we actually supporting people?”

Making AI accountable to real people

Ziv says the real challenge now is not just collecting data, but understanding its impact. 

“It’s really important to think about where that data is coming from, and also recognize that disability needs to be part of that conversation,” she says. 

“It’s really easy to generate bias, and we need to be aware of that.”

For her, responsible AI means ensuring that diverse experiences are reflected in the systems we build. 

“What we say about AccessNow is that accessibility really reflects the broad spectrum of human experience,” she says. “Thinking about who is reflective in those data sets and ensuring that we have that broad representation is really important as we think about the responsibility of the tools we’re creating.”

That philosophy extends to how AccessNow develops technology. The company holds a patent for its proprietary tech, but also leverages tools like Google’s Gemini to free up time and resources for community engagement. 

“We’ve been able to shift the focus of what we develop so that we can leverage tools and actually focus more on impact,” Ziv says.

The goal, she explains, is to move from interpreting accessibility to predicting it, and offering that holy grail for so many tech companies: personalization. 

Inclusion as a measure of leadership

Asked where she sees the greatest opportunity for Canada in the next five years, Ziv’s answer was straightforward: inclusion through innovation. 

“AI is going to be in every business and every industry,” she stated. “It’s really changing the way in which we understand the world.”

She believes Canadian founders have a chance to lead globally by designing technology that bridges divides instead of deepening them. 

Engaging with image or text data used to be inaccessible to people who are blind or non-sighted, she explained. 

“The ability to bridge divides between people through technology is something that’s always excited me.”

Walji closed the session by underscoring the urgency of AI adoption in Canada. 

The country has exceptional talent and a thriving ecosystem, she noted, but still trails other developed markets in AI adoption. She cited a recent Public First report commissioned by Google Canada that suggests that generative AI could increase Canada’s GDP by up to $230 billion.

Her number one piece of advice to business leaders: “experiment, experiment, experiment,” citing how Ziv herself was experimenting with how best to use AI back in 2019, before many founders were using it. Walji also advises leaders to: 

• Build with community
• Apply a responsibility lens from the start. 

Ziv’s journey exemplifies all three.

For her, accessibility is not just a feature, it’s a measure of how well innovation serves everyone. 

“We want to be right there at the human experience,” she says. “To just give people the additional tools to do what they want to do: to travel, to find a great job, to do things they care about.”

Final shots

• Accessibility is an innovation opportunity, not a compliance exercise.
• AI can scale inclusion if trained with representative data.
• Leadership in the AI era means designing systems that understand people before automating them.