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Artificial Intelligence in Education: How It’s Changing Teaching

Artificial Intelligence in Education: How It’s Changing Teaching

Artificial intelligence (AI) is causing profound transformations in several sectors, and education is one of the fields most impacted. From personalized classrooms to automated assessment systems, the use of AI artificial intelligence in education has been gaining increasing prominence. As a result, the impact of AI in schools is reshaping the way teachers teach and students learn, promoting a true digital transformation in education.

In this article, you will understand how AI is being applied in education, what the main tools are, the benefits (and challenges) of this revolution and how to prepare for this new scenario.

Recommended readings for further study:

Application of artificial intelligence in the classroom

What is Artificial Intelligence and how does it connect to education?

Artificial Intelligence is a field of computing that seeks to develop machines capable of learning, reasoning and making decisions. In the educational context, it is applied to personalize learning, automate administrative processes and offer more dynamic and inclusive teaching experiences.

The applications of artificial intelligence in education They range from smart tutors to platforms that automatically correct tests or create lesson plans based on each student's needs.

Practical applications of AI in the classroom

Artificial intelligence is no longer a distant promise and has become an integral part of contemporary educational reality. Instead of waiting for an uncertain future, teachers and students are already using AI-based technologies in a wide range of school activities. This transformation is happening quietly but with great impact — and best of all, with accessible tools that do not require advanced technical knowledge.

Next, we will explore how this presence of AI is realized in everyday education. More than presenting platform names, the goal is to reveal practical possibilities, demonstrate how each resource can be inserted into pedagogical dynamics and, most importantly, encourage educators to begin their journey with AI — even if it is with small steps. After all, each tool presented here can be the starting point for a profound transformation in the way we teach and learn.

1. Adaptive learning platforms

Solutions like Khan Academy with AI from OpenAI offer personalized learning paths based on student performance, adjusting content in real time.

2. Auto-correction and smart feedback

Platforms like Gradescope and Socrative use AI to correct objective tests and offer detailed performance analysis, saving educators time.

Additionally, you can create automated correction flows using Make integrated with Google Docs or Notion, allowing you to deliver activities with personalized feedback.

3. Virtual Assistants and AI Tutors

Tools like ChatGPT, Google Bard and Khanmigo are used by students to clarify doubts and reinforce content based on natural language.

Educators can also use Dify to create custom educational interfaces and subject- or skill-specific tutor bots.

4. Content creation with AI

Educators can use AI to generate quizzes, presentations, and even lesson plans with tools like AI-powered Canva, Notion AI, and ChatGPT, accelerating the preparation of teaching materials.

If you want to go a step further, you can use the Agents Course with OpenAI to create interactive educational experiences with full personalization of content and the student journey.

Further reading: The best Artificial Intelligence tools

Practical examples of the use of AI in education

Benefits of AI in Education

In addition to its growing presence, artificial intelligence in education offers significant advantages, such as:

  • Personalizing learning: each student learns at their own pace and style. As a result, it is possible to better meet individual needs.
  • Automation of repetitive tasks: more time for the teacher to focus on mediation and relationships. In addition, it reduces the wear and tear on operational processes.
  • Inclusion: Students with special needs benefit from features like auto-reading, captions, and real-time translation. On the other hand, it’s important to make sure these tools are accessible to everyone.
  • Engagement: More interactive and adaptive content increases student interest. This makes learning more engaging and effective.

Challenges and precautions in the use of AI

Despite the benefits, the use of AI in education also requires attention to points such as:

  • Student Data Privacy
  • Over-reliance on technology
  • Inequality of access to digital tools
  • Digital literacy for teachers

Therefore, it is essential that educators prepare themselves not only to use these tools, but also to deal with the impacts they can generate in the school environment.

How Educators Can Start Using AI

To start using the artificial intelligence in education, even without technical knowledge, teachers can explore AI in their daily lives with simple tools. Here are some initial ideas:

  • Try ChatGPT to generate questions, summaries or lesson plans.
  • Use Canva to create visuals with automatic suggestions.
  • Explore platforms like Khan Academy with AI to enrich teaching.

In addition to these options, it is possible to implement more robust solutions with no-code tools:

Furthermore, a practical way to advance is to train yourself with specific training. If you are an educator and want to master these technologies, also see the AI Agent and Automation Manager Training, where we teach how to use AI in practice, with a focus on productivity and automation in teaching.

Future of education with AI teacher interacting with dashboard

The Future of Education with AI

THE artificial intelligence in education It will not replace teachers, but it will be a powerful ally. The combination of the educator’s human perspective and the analytical capacity of AI can take teaching to a new level of personalization, scale and impact.

This movement represents a true digital transformation in schools, where technologies such as educational chatbots with AI, personalized tutors and pedagogical automation become part of everyday school life.

As more institutions adopt these tools, the difference will lie in how to use them ethically, creatively and strategically. To achieve this, ongoing training of education professionals will be essential.

Further reading:

Want to transform your educational practice with AI? Get started now with practical training, even if you've never programmed before: Discover our AI and NoCode course

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Neto specialized in Bubble due to the need to create technologies quickly and cheaply for his startup. Since then, he has been creating systems and automations with AI. At the Bubble Developer Summit 2023, he was listed as one of the greatest Bubble mentors in the world. In December, he was named the largest member of the global NoCode community at the NoCode Awards 2023 and first place in the best application competition organized by Bubble itself. Today, Neto focuses on creating AI Agent solutions and automations using N8N and Open AI.

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The market is changing – fast. Artificial intelligence is no longer a trend, it has become a necessity. Companies are cutting costs, optimizing operations and looking for specialists to implement AI in their daily lives. And this is exactly where the AI profession comes in. AI Manager Course.

NoCode AI Manager Course: What it is, Who it is for and What its Objectives are

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Artificial intelligence (AI) is reshaping the way the financial sector operates, from risk analysis to the automation of complex processes. More than a trend, AI has become a strategic tool for financial institutions that want to increase their efficiency, reduce costs and offer personalized experiences. Within this scenario, the use of AI agents for finance has been gaining ground as a practical and accessible application for companies of all sizes.

Financial dashboard with automated charts and visuals representing artificial intelligence

AI Software Development in the Financial Sector

Creating AI-based solutions in the financial context requires robustness, security, and adaptability. Developing this type of software requires an architecture that is prepared to handle large volumes of data, continuous learning, and the ability to provide accurate insights.

In addition, systems need to be able to handle sensitive data, integrate with multiple sources (such as banks, brokerages, and ERPs), and adapt quickly to regulatory changes in the industry. Flexibility and modularity are core elements of any AI architecture for finance.

Integration with Existing Infrastructures

Much of AI’s success in the financial sector depends on its integration with legacy systems. This includes internet banking platforms, CRMs, payment gateways, and compliance tools. Using NoCode platforms such as make up or N8N allows you to create effective connections without the complexity of traditional development.

By the way, if you want to experience in practice how to integrate financial flows with AI, No-Code Start-Up provides a free N8N course with full video on YouTube. It's a great opportunity to explore real automations and understand how to structure secure and intelligent integrations in an accessible way.

With this approach, banks and fintechs can activate intelligent flows based on real data, such as automatic sending of alerts, personalized segmentations and recommendations based on consumer behavior.

Challenges in AI Development for the Financial Sector

Despite the enormous potential, there are challenges that need to be considered. Among the most relevant are:

  • Data quality: models are only effective if fed by clean and organized data.
  • Explainability: It is essential to understand how the AI arrived at a particular recommendation.
  • Cultural resistance: Traditional teams may resist adopting automation and algorithm-based decisions.

As highlighted by Deloitte, the combination of data governance, team training and ethical monitoring of AI is essential to mitigate risks and generate consistent results.

Security and Regulatory Compliance

The financial sector is one of the most regulated in the world. Therefore, all AI applications must comply with standards such as LGPD, GDPR and Central Bank regulations.

The adoption of good practices Data Privacy by Design, end-to-end encryption and role-based access control are just some of the basic requirements. Platforms such as Xano offer robust infrastructure with a focus on security for those who want to develop financial backends with AI.

Digital security illustration with padlock and financial data, symbolizing protection and compliance in AI application

Software Scalability and Resilience

As AI becomes a critical part of operations, it is necessary to ensure that systems are scalable and resilient. This means being able to grow as demand dictates, without compromising performance or security. Cloud computing and the adoption of microservices are essential strategies in this journey.

Companies like Goldman Sachs and Bank of Brazil have already demonstrated, in different contexts, how AI models can be deployed gradually, safely testing hypotheses before scaling to the entire operation.

AI Agents for Finance: Use Cases and Applications in the Financial Sector

1. Automated credit analysis

Companies like Credits use AI to evaluate hundreds of variables — including banking history, spending habits, and public data — to offer personalized credit. This reduces default rates and expands access to credit in a fairer way. According to McKinsey, automation can reduce analysis time by up to 70%.

2. Fraud prevention

O Bradesco and other institutions have implemented machine learning models that detect fraud based on behavioral patterns. When a transaction deviates from the pattern, the system triggers an automatic block or sends an additional verification to the user. According to Visa, the use of artificial intelligence helps prevent fraud totaling approximately US$14T25 billion.

3. Automated investment management

Robo-advisors like the ones from XP Investments use algorithms that analyze investor profiles, financial goals and market conditions to assemble and rebalance portfolios autonomously. CB Insights highlights that these systems are democratizing access to quality financial services, previously restricted to large investors.

4. AI-powered customer service

O Itau has incorporated AI into its digital channels, allowing customers to renegotiate debts, request second copies of bills or consult invoices using natural language. This reduces response time, improves customer experience and frees up human teams for more complex cases. According to Accenture, up to 80% of first-level banking interactions can now be automated using artificial intelligence.

5. Cash flow forecast

Financial management startups use AI agents for finance that integrate data on accounts payable and receivable, seasonality and market trends to predict cash flow for the coming months with high accuracy. Based on this information, more assertive decisions can be made. Harvard Business Review reinforces that this approach reduces the margin of error in financial projections and improves strategic planning.

The Role of AI Agents for Finance

Among all the applications, the AI agents for finance stand out for their versatility and accessibility. They function as intelligent “copilots”, performing tasks such as:

  • Automatic generation of financial reports
  • Sending alerts about targets or deviations
  • Predictive profitability analysis

Using platforms such as Dify and OpenAI, it is possible to configure these agents with natural language, making them easier to use even for those without technical training. This expands access to data intelligence in the financial sector.

The Future of AI in the Financial Sector

Artificial intelligence in the financial sector is no longer a distant promise — it is present in strategic decisions, customer service, and risk management. The adoption of technologies like AI agents for finance represents a leap forward in digital maturity. As technical challenges are overcome and platforms become more accessible, companies of all sizes will be able to use AI not only to automate, but to evolve.

Organizations that master the use of AI ethically, safely, and strategically will be ahead in delivering value and conquering the market. The future of finance is predictive, integrated, and data-driven — and it starts now. Want to learn how to build your own AI-powered financial agents without coding? Access the AI Agent Manager Training and discover the most practical way to apply all this in your context.

How AI is changing the market can be observed in practically all sectors of the economy, and this change is intensifying every day. Artificial intelligence (AI) is being recognized as a disruptive force that is profoundly reshaping the global market. From simple tasks to complex decisions, it has been integrated into processes in various sectors, transforming the way people work, consume and manage businesses.

Furthermore, when observing the effects of this transformation, it becomes clear how much the job market is being reconfigured: new opportunities arise, some professions lose ground and others adapt or are reborn with the support of technology, which demonstrates how AI is changing the market in a broad and profound way.

How AI is changing the job market

AI is accelerating the automation of repetitive and operational tasks. AI systems are already being used to efficiently perform:

  • Customer service with chatbots.
  • Predictive data analysis for sales and marketing.
  • Automated financial and audit processes.
  • Inventory control and logistics.

These changes not only reduce operational costs, they also require the workforce to be retrained for new roles, which reinforces how AI is changing the job market with great intensity.

Representation of people and artificial intelligence collaborating in different professions

Professions affected by artificial intelligence

According to PwC's report on the future of work (source), it is estimated that up to 30% of human tasks could be automated by the mid-2030s. This data shows, in practice, how AI is changing the job market and skills requirements.

Some of the roles most impacted by AI include:

  • Telemarketing operators
  • Administrative assistants
  • Data Analysts (some tasks being replaced by generative AI)

On the other hand, new functions emerge, such as:

  • Prompt Engineers
  • Automation experts with NoCode
  • Conversational Experience Designers
  • Intelligent Agent Managers

Those AI agents, for example, have been increasingly used in companies seeking to automate decisions and perform tasks with minimal human intervention. According to an analysis of the The Verge, large companies such as OpenAI, Google and DeepMind are investing heavily in the development of these systems, which can already act independently in complex corporate processes. They are designed to operate autonomously, learn continuously and integrate with other technologies — which makes them key players in the ongoing digital transformation.

What's Happening Now: How AI is Changing the Marketplace in Numbers

The AI market is experiencing exponential growth. The sector is estimated to surpass US$ 500 billion in value by 2027. There is a global race for innovation, with startups, large companies and governments investing heavily in:

  • Generative models (like ChatGPT)
  • Robotic Process Automation (RPA)
  • Artificial intelligence applied to health, education, law and agribusiness

This movement demonstrates how AI is being positioned as a strategic asset for growth and competitiveness.

Suggested reading:

AI Agent and Automation Manager Training

What are the negative aspects of AI in the job market?

Despite promising advances, important challenges also arise:

  • Structural unemployment: functions terminated without sufficient time for requalification
  • Digital inequality: not everyone has access to technological education
  • Technological dependence: companies become hostages of platforms and algorithms
  • Ethical and privacy issues: inappropriate use of data and biased automated decisions

These factors require public policies, business leaders and civil society to debate limits, transparency and responsibilities in the use of technology.

People using AI tools in a modern workplace

Opportunities and the future of work with AI

The key is in the conscious adaptation. The future of work will be driven by:

  • Continuous learning and professional requalification
  • Mastery of AI tools and NoCode platforms
  • Creating new business models based on data and automation
  • Development and management of autonomous AI agents

Increasingly, professionals and companies will need to adopt a stance proactive and experimental, turning AI into an ally.

Recommended courses:

AI and entrepreneurship: new market frontiers

Artificial intelligence is not only transforming the traditional job market, it is also paving the way for new business models. Digital entrepreneurs are using AI to create scalable products such as intelligent assistants, recommendation systems, and data-driven SaaS platforms. No-code tools combined with AI agents are enabling the emergence of lean, highly automated, and highly personalized startups.

A great example is the AI-based micro-SaaS, which solve very specific problems and can be created by a single person. Platforms like Bubble, FlutterFlow and Make, integrated with OpenAI models, make this scenario not only possible, but accessible.

For those who wish to explore this new territory, we recommend SaaS IA NoCode Training, designed to transform ideas into digital products using the power of artificial intelligence.

How AI is changing the market and shaping the future

Artificial intelligence is changing the market in an irreversible way. It is not only a technological revolution, but also a social, professional and economic transformation. The question is no longer “if” AI will impact your work, but “how will you position yourself in this new era”.

The good news is that there have never been so many accessible tools for those who want to learn AI in practice.

See all No Code Start Up training and courses

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