AI has been a hot topic for at least a decade, but businesses still face obstacles to adoption. An annual survey by Deloitte suggests 40% of companies are concerned about AI technology and expertise costing too much. AI is democratized by making it widely accessible at a low cost using no-code solutions.
Artificial intelligence without programming is a category in the AI landscape aiming to democratize AI. AI and machine learning models are deployed using a no-code development platform with a visual, code-free, and often drag-and-drop interface. Non-technical users are able to easily build accurate models using No Code Artificial Intelligence by classifying, analyzing, and predicting data.
Why is no-code AI important for businesses?
AI models are needed by businesses. Forbes’ survey shows 83% of businesses cite AI as a strategic priority today, but there is a lack of data scientists. Over the last two years, there has been a double-digit growth in the need for advanced AI talent. A majority of AI talent is absorbed by technology and financial service firms, requiring smaller companies to rely on citizen data scientists to implement AI.
It takes time, effort, and experience to build AI models (i.e. to train machine learning models). Machine learning models can be easily adopted in business processes with no-code AI as it reduces the time to build AI models to minutes.
Google Trends indicates that, despite the increasing interest in no-code AI, it is still far lower than the interest in learning machine learning or auto-ML. AI solutions that do not require coding have not yet replaced data scientists. There is still a lot of development to be done in this field. More adoption will be enabled by maturing and integrating existing solutions.
What are the benefits of no-code AI solutions?
By offering no-code solutions to AI and machine learning, no-code solutions reduce the barrier to entry for individuals and businesses. Businesses can quickly and cost-effectively implement AI models using these solutions, and their domain experts can benefit from the latest technology.
Combine business experience with AI
The field of data science is still relatively young, and most data scientists do not have the same level of business experience as domain experts. According to a data science survey conducted by crowdsourcing platform Kaggle, a data science competition platform, respondents are most commonly 24-years-old and the median age is 30. The advent of no code solutions enables business users to leverage their domain expertise to quickly build AI solutions.
To create a custom AI solution, one must write code, segregate data, categorize it, structure it, train and debug the model. People who aren’t familiar with data science will take even longer to complete these. According to studies, low-coding/no-coding systems can reduce the development time by 90 per cent.
Automation and nocode technologies offer the obvious benefit of saving time and money. As companies can build machine learning models with their business users, they need fewer data scientists.
Help data scientists focus
Data science teams are often asked to perform easy-to-solve tasks by other employees at businesses that have already formed one. By enabling business users to address these requests themselves, no-code solutions minimize these distracting requests.
How does autoML differ from no code AI?
Nontechnical employees may be able to develop AI solutions more quickly by combining these categories. Currently, the categories differ slightly:
- The goal of AutoML solutions is to improve the efficiency of data scientists. Machine learning pipelines are transparent, which increases complexity but also makes it possible for data scientists to refine how models are built.
- No-code AI solutions assist non-technical users at every step in building a machine-learning model without requiring them to learn each step in detail. As a result, they are easy to use, but harder to customize.