In our last article, ‘The Vision Behind Sway AI’, we spoke about how Sway AI has dramatically simplified the process of building and implementing AI for enterprises with their end-to-end no-code architecture, in this post however, we’ll take it a step further and uncover why no-code AI technology is critical for unblocking AI adoption within enterprises.
AI adoption advances, but foundational barriers remain
Much of the history of artificial intelligence (AI) research has been marked by false starts and overhyped solutions that failed to live up to their promises. The goal of building a machine that can “think” like a human has proven to be among the most intractable computing problems ever.
All of that has changed with the advent of machines based on artificial neural networks (ANNs). ANNs attempt to mimic the brain’s ability to recognize patterns and make inferences. AI researchers arrange
the artificial neurons into layers and design the inputs and behavior of each neuron. This allows new algorithms to complete narrowly defined tasks that are beyond the ability of conventional algorithms.
The researchers take this concept a step further with the idea of deep learning. Deep learning algorithms self-adjust as they are “trained.” To do this they process high volumes of known input data. Over many iterations, the algorithm’s parameters are adjusted until the machine can give the “right” answer, even when it’s given input data the algorithm has never seen before.
As a result, AI has been in the mainstream, with practical applications such as Netflix recommendations, machine translation, and medical diagnostics. Large enterprises now embrace AI and introduce new applications every day.
And yet, AI technology isn’t as pervasive as it could be. Why?
Answer: Because it’s still hard to do.
The Issue: Scarce Resources for AI Development
AI development is very complex and requires high-priced software developers and data scientists with specialized expertise. Much of the current AI development is done with programming language that has a steep learning curve and takes a long time to master. Because AI development is still new, resources like data scientists are scarce and the demand for AI practitioners is high.
The result is that deep-pocketed enterprises have snapped up most of this talent, leaving everyone else to scrape by as best they can, or forego their AI initiatives altogether. The gulf between enterprise AI haves and have-nots is wide and shows few signs of improvement.
However, an exciting new development promises to “democratize” AI and make its power available to more organizations around the world: No-code AI tools.
No-Code: The New Frontier in AI Development
What is no-code AI? No-code AI tools allow anyone, without coding experience or training, to build AI by using drag-and-drop interfaces or wizards that guide them through the process. This means that organizations can build their own customized AI tools, at the same time, they keep costs down and speed up their development times. No-code AI gives stakeholders without software programming skills an opportunity to do what they do best: analyze data and design strategies for their businesses.
No-code AI is designed for non-technical users. There are three main categories of no-code AI:
- Visual drag-and-drop tools, which allow users to map out their workflow in a visual interface
- Wizard tools, which offer pre-built models that are easy to follow
- Apps that utilize AI to automate tasks such as predictive analytics and smart assistant chatbots
There are many benefits to using no-code AI tools:
- Organizations with limited development staff can create their own AI applications without any coding expertise whatsoever. Companies no longer need dedicated developers to build their AI projects.
- No-code AI makes it easier for organizations to integrate new technologies into their workflows because the range of no-code AI tools is expanding.
One of the most important things about no-code AI is that it offers enterprises a way to get started while it avoids the high costs associated with hiring specialized developers.
Conclusion
We are still many years away from general-purpose AI that can understand any arbitrary command you give it, figure out the best way to execute it, and then carry it out. Modern AI is best applied to narrowly defined tasks that do not involve intuition. AI is quite good when the range of possible input data is constrained and contains recognizable patterns.
Even within those limitations, a wealth of AI-enabled applications is possible. With the growing number of no-code AI development options and preconfigured models, it’s now becoming possible for enterprises to rapidly build new and more complex AI processes and do so without coding. As no-code AI becomes more robust and easier to use, adoption will accelerate. Sway AI intends on becoming a major proponent in that acceleration with their No-Code Visual Platform, announced to the market in early February, which automates a majority of the required AI tasks allowing enterprises to implement AI with ease.
We stand on the brink of a revolution in AI development. Even the smallest enterprises can experiment with AI and learn how it can make their operations leaner and more efficient while it improves their customer experience. This revolution will be driven by a new generation of no-code AI development tools such as Sway AI’s no-code technology.
It’s an exciting time to delve into AI. Come aboard!