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Power of AI with No-Code
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AI has been around for more than a decade, and some estimates claim it has finally reached critical mass. AI initiatives in most enterprises have moved beyond the experimentation and proof of concept stage. One thing that has steadily been on the rise is the investment and time needed for any AI initiatives to realize, and AI is still considered a niche and technologically exhaustive.

Due to the right reasons, AI is still limited to a few who understand the technology and the associated complex terminology. Additionally, AI is extremely hard to master. If you wish to create a unique data model for your specific business problem, it sometimes may take months to arrive at a plausible working solution.

No-Code AI intends to address this prevalent and often taken-for-granted technical-functional gap.

Let’s start

What is No-Code?

Simply put, No-Code stands for a set of tools that empower regular users to build applications, automate workflows and manage data without having any programming knowledge. No-code is Lego of enterprise software, i.e. Plug and play, simple, easy, blocks or chunks of functionality.

No-code platforms, such as Quixy offer rich visual interfaces to build apps and pre-built integrations to connect with other enterprise systems as necessary. No-code platforms are targeted toward Business users who have the right context of the business problems to solve.

The adoption of No-code platforms has been on the rise in enterprises over the years, and No-code is here to stay.

Before we delve into what No-code AI is all about, let’s first understand the Why and When to use AI.

Also read: Everything you should know about No-Code Development

Now, what is AI?

A typical business application is generally a hotchpotch of complex processes governed by rules. Simply put, they are a bunch of if-else-then statements, also known as Rules, in various combinations. Rules give businesses the power to automate workflows at scale but only when the desired outcomes are predefined. What if the outcome cannot be preempted but is completely dependent on the data and its context. 

For example, you wish to extract text from documents based on certain conditions, find the ideal marketing campaign strategy, or predict the sales based on historical sales information & current market situation. These are the situations where AI comes to the rescue. According to Forbes, 83% of businesses say AI is a strategic priority for their businesses today. Rules can also handle these situations, but they would be inherently slow and unreliable.  

Word of caution, AI is not the magic pill. What can be achieved with a few simple rules does not warrant the use of AI if the outcome is predetermined. With large data comes huge responsibility!

Finally, No-Code AI

No-code AI and No-code share many similarities; they both empower business users to build applications or models in a fraction of the time and cost scale. So, No-code AI is here to democratize AI for users with no or limited technical know-how.  

No-code AI aims to empower business users to create AI models and eliminate potential bottlenecks to adopting and leveraging AI in their business situations.  

To understand how No-code AI can disrupt the seemingly elusive AI barrier for Businesses, let us first comprehend the traditional AI process.  

Traditional AI is generally a 5-7 steps process starting from Data preparation, Feature engineering, Data pre-processing, Model selection, Hyper-parameter tuning, Model training, Model deployment, and finally, Workflow integration. These steps are generally non-linear in nature and take a lot of iterations to find the right combination of models and training parameters. Model deployment is another hassle that is time-consuming and expensive to set up and maintain. Traditional AI processes are generally slow to implement and need niche machine learning skills to build, deploy, and maintain.  

Comparatively, the No-code AI process involves four steps: Data collection & upload, Drag & Drop model training, Results analysis, and Workflow integration. The great thing about No-code AI is the supporting elements such as model selection, parameter tuning, training, model deployment, infrastructure, technical know-how, etc., are all handled by the No-code AI SaaS provider. This removes ~90% of hassles for the business users and significant savings on time and cost. 

No-code AI / ML platforms allow users with no AI engineering skills to optimize operations and solve critical business issues with relative ease. No-code tag evidently means less intimidating technical jargon and more visual drag-and-drop tools to build robust models addressing any business issue. No-code is also a boon for any business that lacks resources or time to build ground-up AI systems.

Advantages of No-Code AI

Let’s now look at a few additional advantages of No-Code AI

Advantages of No-Code AI

1. Become data-driven

According to Forbes, 83% of businesses say AI is a strategic priority for their companies today. There has been an increase in demand for AI talent in the market in the past two years. Building a data science team is both times consuming and expensive, especially when you are experimenting with being data-driven. No-code AI platforms or tools help you become data-driven without the data science team.

2. Speed

Experimentation and iteration are the key here. With No-code AI platforms, rapid model creation and testing are the norms. This allows for rapid model building and showcasing results to the business stakeholders more often for approvals or aiding in critical business decisions.

3. Accessibility

Due to relatively low upfront investment, flat learning curve, and no challenge of skill gap, No-code AI platforms mitigate the adoption of AI in small and medium-sized organizations. Additionally, No-code AI empowers business users to experiment with AI and realize the value faster.

4. Usability

Drag-and-drop plug-and-play allows business users to build AI solutions quickly and cost-effectively. Since the target audience is non-technical business users, the platform is generally easy and self-serviceable.

5. Quality

With Business users as the target audience for the No-code AI tools, the risks with data are carefully thought out at the platform or product level. Measures such as Human-in-the-loop allow for fool-proofing the processes from unforeseen issues during the regular operations.

6. Scalability

Underlying infrastructure comes with the No-code AI platform that automatically scales up or down based on a load of building and deploying models.

Conclusion

No-code AI process is simple, fast, cost-effective, and saves time by a big margin compared to a traditional AI process. No-code AI fosters innovation, a data-driven attitude, and faster decision-making in organizations without the need for expensive data science teams and large infrastructure.  

No-code AI space is growing and has the power to transform any business. These platforms or tools remove the hurdle of upfront capital and a large data science team which SMBs may find daunting to invest in, while also levelling the playing field against the large enterprises.

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