3 Ways No-Code is Democratizing AI
July 26, 2022

Loren Goodman
InRule Technology

We have become accustomed to so many different technologies in our lives today. Most share a common history — there was a democratizing force that brought it from an abstract, unattainable thing we only heard about to something we can no longer live without. Take the computer — for decades, computers were larger than refrigerators and were only accessible to the largest companies or nations. Today though, most of the world carries one in their pocket. Mass-marketed desktop computers balanced cost and operational restraints with measured capabilities tailored to the needs of an individual; they were relatively easy to use, and one did not need to know how they worked to get value from them. They provided immense value for its users.

Looking at the world of emerging technologies, artificial intelligence (AI) appears to be the next technology on the cusp of breaking into the mainstream, thanks to the development and growing proliferation of no-code AI. A code-free technology that enables non-AI experts to implement and test their ideas without any need for a data scientist, no-code AI will prove to be a democratizing force within the AI industry enabling greater accessibility and use by businesses outside of the Fortune 100.

For businesses to remain competitive, they must invest time, money and resources into their AI capabilities. Luckily, with no-code AI, much like the desktop PC, there are varying levels of investment accessible to all instead of just those that can leap the historical barriers to entry. There is no need to establish a data-science practice, and there is no need to learn complex technologies.

To reap value, you need data and a system of automation; no-code AI brings the automation, and most organizations are already overflowing with data. A 2020 Salesforce report, which surveyed 100 global IT and engineering leaders, found that company departments utilizing workflow automation reduced time spent on manual processes by 66% and reduced cost by 46% compared to year-over-year outcomes. By streamlining manual processes through no-code AI models, businesses can scale faster while reducing the consumption of human time and increasing the accuracy of predictions.

Here are three key ways no-code AI is democratizing the technology:

1. No-Code AI Removes the Need for A High Degree of Training

It is no secret that a labor shortage exists for highly technical and skilled employees. Companies across all industries have difficulty finding and retaining qualified data scientists who can develop and create AI/ML models. This skills gap isn't going away anytime soon. No-code AI workflows empower citizen data scientists, including business analysts and other subject matter experts, to create, train and deploy powerful machine learning models. Another benefit of no-code AI is the relatively flat learning curve, allowing it to be quickly taught, replicated, and scaled across departments. This enables employers to combat the skills gap within their workforce by incorporating no-code tools training into employee development and onboarding.

2. Quicker Model Creation and Faster ROI

For companies lucky enough to have a data scientist on their staff, no-code AI enables them to work faster and more efficiently than before. No-code AI provides data scientists with automation and reusability that allows quick delivery of prototypes and iterative improvements using model explainability, revealing areas of model weakness. By employing no-code AI, data scientists can easily pinpoint problem areas within models, allowing managers to address any issues before they manifest into greater dilemmas quickly. Optimizing these processes frees up valuable bandwidth for data scientists to focus on more specialized research and projects within the company.

3. Better Explainability + Bias Detection Are Baked In

The Silicon Valley ethos of “move fast and break things” is gone. After years of eroding trust by big tech, consumers and businesses want to ensure the tech they invest in follows the “first do no harm” principle. Because no-code AI is created with the goal of enabling non-data scientists to harness the power of AI, it needs to be embedded with a higher level of explainability and bias detection to reduce the risk of human error.

No-code AI has proven to be a simple yet powerful solution aiming to bring AI to the masses. By democratizing AI with improved accessibility, businesses, regardless of size, will be able to compete more aggressively with AI in their toolbox.

Loren Goodman is Co-Founder and CTO of InRule Technology
Share this

Industry News

May 08, 2024

MacStadium announced that it has obtained Cloud Security Alliance (CSA) Security, Trust & Assurance Registry (STAR) Level 1, meaning that MacStadium has publicly documented its compliance with CSA’s Cloud Controls Matrix (CCM), and that it joined the Cloud Security Alliance (CSA), the world’s leading organization dedicated to defining and raising awareness of best practices to help ensure a secure cloud computing environment.

May 08, 2024

The Cloud Native Computing Foundation® (CNCF®) released the two-day schedule for CloudNativeSecurityCon North America 2024 happening in Seattle, Washington from June 26-27, 2024.

May 08, 2024

Sumo Logic announced new AI and security analytics capabilities that allow security and development teams to align around a single source of truth and collect and act on data insights more quickly.

May 08, 2024

Red Hat is announcing an optional additional 12-month EUS term for OpenShift 4.14 and subsequent even-numbered Red Hat OpenShift releases in the 4.x series.

May 08, 2024

HAProxy Technologies announced the launch of HAProxy Enterprise 2.9.

May 08, 2024

ArmorCode announced the general availability of AI Correlation in the ArmorCode ASPM Platform.

May 08, 2024

Octopus Deploy launched new features to help simplify Kubernetes CD at scale for enterprises.

May 08, 2024

Cequence announced multiple ML-powered advancements to its Unified API Protection (UAP) platform.

May 07, 2024

Oracle announced plans for Oracle Code Assist, an AI code companion, to help developers boost velocity and enhance code consistency.

May 07, 2024

New Relic launched Secure Developer Alliance.

May 07, 2024

Dynatrace is enhancing its platform with new Kubernetes Security Posture Management (KSPM) capabilities for observability-driven security, configuration, and compliance monitoring.

May 07, 2024

Red Hat announced advances in Red Hat OpenShift AI, an open hybrid artificial intelligence (AI) and machine learning (ML) platform built on Red Hat OpenShift that enables enterprises to create and deliver AI-enabled applications at scale across hybrid clouds.

May 07, 2024

ServiceNow is introducing new capabilities to help teams create apps and scale workflows faster on the Now Platform and to boost developer and admin productivity.

May 06, 2024

Red Hat and Oracle announced the general availability of Red Hat OpenShift on Oracle Cloud Infrastructure (OCI) Compute Virtual Machines (VMs).

May 06, 2024

The Software Engineering Institute at Carnegie Mellon University announced the release of a tool to give a comprehensive visualization of the complete DevSecOps pipeline.