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Democratizing AI through No-Code Platforms

Craig Smith header image
Craig Smith header image

Craig S. Smith is a former correspondent and executive at The New York Times. He is the host of the podcast Eye on A.I.


Technology often follows a familiar progression. First, it’s used by a small core of scientists. Then the user base expands to engineers who can navigate technical nuance and jargon until finally, it’s made user-friendly enough that almost anyone can use it.

Right now, building artificial intelligence software is making that final leap. New “no-code” AI platforms are replacing programming languages with simple drag-and-drop interfaces, and the implications are huge: Where it used to require a team of engineers to build AI-powered software, now users with a web browser and an idea can build that software themselves.

No-code AI is making it possible to deploy artificial intelligence — one of the most transformative technologies in a generation — without hiring an army of expensive developers and data scientists. These platforms are quickly growing increasingly formidable as they tap the muscle of large language models. That is democratizing the power of AI and accelerating its penetration and transformation of the global economy and of democracy itself. 

New “no-code” AI platforms are replacing programming languages with simple drag-and-drop interfaces and accelerating AI’s transformation of the global economy.

For example, no-code artificial intelligence helped give Democrats a fundraising edge over their Republican rivals in the 2022 U.S. election cycle, allowing Democrats to retain control of the Senate and blunt a Republican takeover of the House.

While many other factors were at play, the Democrats relied more heavily on AI in finding donors, according to professional fundraisers, bringing in more money from individual, small-dollar donors than their Republican rivals.

Take Democrat fundraising firm Sterling Data, which used a no-code machine-learning website, Akkio.com, to predict potential donors’ likelihood of giving money. It runs a subset of its database of 30 million potential donors through an Akkio model trained to spot likely donors for a particular candidate. The result is a prospective donor list ranked from most likely to least likely to give, allowing Sterling Data to focus its efforts without wasting time and money on the wrong people. The fundraising firm said that Akkio’s model builds prospective donor lists that consistently raise twice as much as lists built with other methods.

No-code artificial Intelligence helped give Democrats a fundraising edge over their Republican rivals in the 2022 U.S. election cycle.

AI tools like Akkio now allow organizations to scale in ways that were once impossible, crunching millions of data points in seconds and prioritizing the actions to take for maximum effect. These platforms promise to take much of the guesswork out of forecasting and increase the clarity of the near-term future for many businesses. They typically work on any kind of tabular data, predicting everything from winners in a horse race to how much steel a factory is going to need next year.

Removing friction from adoption will unleash the power of AI across industries and allow non-specialists to produce work much faster, with higher precision and predict the future.

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