While artificial intelligence (AI) and Nocode are not so recent topics, these two computing concepts have been omnipresent in the media in recent years.
This media explosion started with Nocode a few years ago and the rise of APIs and the Cloud. Then by AI with the release of Generative AI models like ChatGPT which clearly shook the Earth.
And this time we can really assure that it's not a hype. Because ChatGPT reached 100 million active users in January, in just one month. That's better than TikTok or Instagram.
So why so much innovation and so much noise about Nocode and AI?
So many innovations because the need to create applications is growing faster than the human resources expert in these subjects. Nocode and AI respond to these challenges by making software development accessible to the greatest number of people.
So much noise because, as we have just said, the uses once reserved for developers and data scientists are now accessible to business people in a company.
Adoption is at the center of this whole revolution.
This rapid and massive adoption has also raised many questions and concerns about jobs, security and the economy as a whole.
IBM recently announced that it has paused hiring for "back-office" roles in anticipation that Nocode and AI will be able to automate much of their work.
Google, Microsoft, Facebook, Amazon, Alibaba: the giants are all in on it.
So here we propose to explore with you the intersection of AI and Nocode and their potential impact on businesses.
Without dwelling too much on this concept, Nocode refers to the set of tools that allow complex computing tasks to be performed without programming skills.
We can mention the creation of chatbots, websites, web and native applications or data analysis.
If you want to know more, we have written a full article on the subject.
AI, or Artificial Intelligence, is a field of computer science that seeks to create systems capable of performing tasks that normally require human intelligence. To learn more about generative AI, we invite you to read this article.
This can include tasks such as learning, natural language comprehension, visual perception, problem solving and even creativity.
Today, it is data scientists who are able to deal with these subjects. This is why it is important to be able to couple AI with Nocode - which has this perpetual goal of making any complex task accessible.
Before Nocode, a web developer was needed to develop a simple web page, a website, an application. Now we can use tools like Webflow, Bubble, FlutterFlow and many other Nocode tools.
The same thing is happening with artificial intelligence. Until recently, it was unthinkable to create and deploy AI models without working with data scientists. Now it is possible with Nocode AI tools.
Nocode AI can therefore be defined as tools that allow non-expert profiles to apply artificial intelligence without having to write a line of code.
These Nocode AI tools then allow "Business People" to incorporate data from their operations into accessible tools and apply models and algorithms for processing and reading data in order to quickly answer analytical questions. With Nocode, AI brings a new level of abstraction in the ability to develop. And that's remarkable.
Although these Nocode AI tools are largely more accessible, it should still be noted that knowledge of machine learning goes a long way in manipulating certain platforms.
But at Alegria.group, we truly believe that AI will increase by 100 what we are able to automate because it will handle the complex and creative steps for us.
The ability to give context to these tools and to generative AI models in particular will allow us to go much further in creating complex systems.
We can finally say that chatbots will be useful and fulfill the promise of accurately responding to user requests.
Let's see how the meeting of AI and Nocode will shape the uses of tomorrow.
At Alegria.group, we are passionate about the subject and we have distinguished two different approaches between AI and Nocode.
Nocode tools have evolved enormously over the last few years and we can affirm the whole range of use cases in the software development world. Here are some examples and use cases:
We are now entering a new phase of development and maturity for these tools with the integration of AI within the Nocode platforms.
We have identified three types of integration:
We are starting to see more and more Nocode tools integrate a wizard (called copilot) where the objective is either to inform the user about a specific request or to execute an action.
AppSheet, Google's Nocode solution, relies on generative AI to allow its users to generate small applications based on data connected to the solution just by typing a few sentences. The AI will then ask a series of questions to refine the search to make sure it fetches the right data from the right tables.
Their explanatory video, in action!
Microsoft Power Platform has also integrated the power of GPT into its services to allow the generation of simple actions and applications from natural language. Namely if it was already possible to generate applications from an image or a Figma design.
Here is their presentation video
To stay in the Microsoft universe, Bill Gates announced on March 16, 2023 that the Copilot solution based on GPT-4 has been added to the Microsoft 365 suite (Word, Excel, PowerPoint, Outlook, Teams, OneNote...). This is a huge break considering the installed base of all these applications.
Webflow, Notion, Bubble, WeWeb or FlutterFlow - to name but a few - have also integrated AI into their platform.
And as for Make and Zapier, it is now possible to integrate GPT into your workflows to give them context. The use cases are endless.
As you can see, the stakes are high for each of these publishers to stay in the innovation race.
We are referring here to the set of products that perform specific operations in order to do the work that an employee would do.
Let's take the example of Otter.ai which is a solution that transcribes your meetings live and then creates a summary of a meeting and proposes a list of actions to be taken assigned to each person involved.
A considerable time saving for companies and employees who have a lot of meetings.
We've all experienced it. We've all dealt with chatbots where we're desperately waiting for a person, endlessly. Or a chatbot that would only redirect you to long-winded FAQ articles where information is hard to find.
This is a real breakthrough. We can now train chatbots on proprietary data and the AI will be able to process the information in this entire internal knowledge base to respond in a clear, concise and relevant way to the user.
It's a total win-win: the company automates for the user and improves customer satisfaction.
Here we change our perspective to focus more on the processing and analysis of data from models that are built via statistical techniques or machine learning.
A very common use case is predictive analytics to predictcustomer churn.
The promise of Nocode's AI tools is to allow more business-oriented profiles to import data and take advantage of pre-designed models in order to achieve the expected objectives.
Here are some other examples that are now being addressed by Nocode AI tools:
The objective of this part is to give you a quick and global idea of some of the possibilities and use cases that are available with Nocode AI tools and the integration of generative AI using Nocode.
This list is not exhaustive.
Here are three use cases that we have identified among many others:
The most notable use case for experience and satisfaction is that of the chatbot, which will be able to provide information based on each organization's data in order to provide answers in a personal, personalized and accurate way.
It should be noted that while Nocode AI tools offer many benefits, they do not entirely replace the need for in-house AI experts or the need for external experts like Alegria.solutions. These tools are best used to complement existing skills and expertise.
Generative AIs are trained on large amounts of data, which can include personal information, which raises some concerns.
That said, Microsoft recently announced that it could make private servers available for companies to use generative AI and train it on their own data.
Generative AI models are often trained on massive data, some of which may be sensitive or private. It is crucial to establish governance practices that ensure that the data used respects privacy and individual rights, and that it is used ethically and legally. This includes compliance with regulations such as the RGPD in Europe, mentioned above.
AI models can reproduce or amplify biases present in the data on which they have been trained. Governance mechanisms are needed to identify and mitigate these biases.
Nocode AI opens up exciting new opportunities for businesses and professionals. By combining artificial intelligence with code-free development tools, we are witnessing a revolution that makes technology more accessible than ever.
The benefits of this convergence are numerous: simplify the creation of applications, improve the efficiency of processes, personalize customer experiences or automate tedious tasks. However, this evolution also raises questions and challenges, such as privacy, governance and algorithmic bias (ethics).
Balancing the use of Nocode AI tools with human expertise is critical to maximizing the benefits while ensuring ethical and responsible use of this technology. The future of Nocode AI is bright, and it is exciting to imagine how it will shape businesses and society in the years to come.
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