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By Audrey Hingle —

AI is Evolving Fast—But Implementation will take longer

AI is Evolving Fast—But Implementation will take longer
Photo by Julia Weihe / Unsplash

AI is advancing fast, but its real impact will take longer than you might expect. In our featured article below, Mozilla Fellow and AI researcher Sayash Kapoor explores why adoption lags behind innovation—and what it will take to bridge the gap.

But first:

Join Mallory for an Inspiring Fireside Chat: Humanising AI for Gender Equity in South Asia

Mallory Knodel—founder of this newsletter, technologist, and human rights expert—will join Hera Hussain, founder of Chayn, and advocacy expert Ramma Shahid for a fireside chat titled “Humanising AI for Gender Equity in South Asia” at the 8th annual WOW (Women of the World) Festival Pakistan. They will explore how to bridge the gender gap in AI, increase women’s participation in AI development and decision-making, and make AI more equitable and accessible.

The session will be live-streamed on WOW Pakistan’s YouTube channel on February 1, from 4:00 to 4:30 pm Pakistan time, followed by a live Q&A.

The WOW Festival Pakistan, in partnership with the British Council, takes place in Lahore on February 1-2, 2025. Curated by the WOW Foundation, it brings together women and men of all backgrounds to celebrate feminist leadership and discuss issues affecting their lives. Since its inception, WOW has hosted over 100 festivals across six continents. This year’s theme, "Surkhaab," symbolizes the extraordinary and unachievable, mirroring the dedication of the women celebrated at the festival. Led by Amneh Shaikh Farooqi, the festival features eight panels, six workshops, and 100 delegates.

Entry is free, and the full schedule is available on the WOW Pakistan website.

Day: Sunday, 2nd February 2025
Time: 4-4:30pm Pakistan Standard Time (GMT+5)
Location: Alhamra Arts Council Lahore, Hall Number 2, Pakistan
Instagram: @wow.pakistanhttps://www.instagram.com/wow.pakistan
Youtube (live stream): @wowfestivalpakistan

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In 2025, AI Adoption Will Continue to Lag Innovation 

By Sayash Kapoor. Adapted from his piece which originally appears as part of the series Mozilla Fellows Share 2025 Tech Visions

Advanced generative AI, such as large language models based on transformers and text-to-image diffusion models, has seen rapid improvements in the last few years. But despite predictions that AI will revolutionize the economy in short order, the adoption of AI will be far slower. 

While specific sectors will face rapid changes, the broader economic impact will be tempered by what political scientist Jeffrey Ding calls the "innovation fallacy" in artificial intelligence deployment: the impact of general-purpose technologies like AI on the economy is realized when AI is adopted across sectors of the economy such as healthcare, education, and finance rather than through innovations in the technology alone. For example, in contrast to claims that having access to the "best" language model (such as DeepSeek's R1) will lead to the benefits of AI, it is the adoption of AI across different sectors of the economy that will lead to its productive impact.

We have seen this with past general-purpose technologies like the internet, which took decades to be adopted across the economy despite rapid initial innovation. We are already seeing the same for AI adoption: while generative AI capabilities are advancing rapidly, organizations still struggle to effectively integrate these tools into their workflows processes. This is both due to limitations of the technology (such as the lack of reliability and the propensity of language models to "hallucinate" or fabricate content in their outputs) and the need for institutional knowledge and expertise to adopt AI. 

Consider healthcare: AI has long been capable of transcribing conversations, but even deploying simple transcription applications to save time for clinicians while taking patient notes has run into challenges such as "hallucination": AI fabricating incorrect content as part of its output. This makes adoption slow, since hurdles usually need to be solved by domain experts in concert with technical experts. 

AI adoption also runs into institutional hurdles. Even when technical challenges such as hallucination are addressed, improving patient outcomes has other roadblocks: privacy regulations, integrating with existing workflows, and training clinicians in using AI. Such technical and institutional hurdles lead many to incorrectly conclude that AI won't be useful in domains like healthcare; the reality is that adoption simply takes far longer than we typically expect. 

The gap between the potential of AI and its practical implementation will define 2025. Despite improvements in AI models, using them productively in real-world settings, such as to meaningfully improve healthcare delivery, enhance education, or streamline government services, will remain challenging. The adoption of AI will require creating AI applications for different contexts, improving technical know-how (such as through training workers across areas of the economy), and diffusing access to state-of-the-art AI across industries, not just in tech. This will be more time consuming and less striking that building AI that has better capabilities. It might take decades rather than years. But it will be essential for spurring the adoption of AI in useful ways across the economy. 

I am grateful to Arvind Narayanan and Lindsey Dodson for feedback on a draft.

Sayash Kapoor is a Mozilla Fellow, a Laurance S. Rockefeller Graduate Prize Fellow in the University Center for Human Values, and a computer science Ph.D. candidate at Princeton University's Center for Information Technology Policy. He is a co-author of AI Snake Oil, a book that provides a critical analysis of artificial intelligence, separating the hype from the true advances. His research examines the societal impacts of AI. Kapoor has been recognized with various awards, including a best paper award at ACM FAccT, an impact recognition award at ACM CSCW, and inclusion in TIME’s inaugural list of the 100 most influential people in AI.

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