Can AI help me do my job better?

August 2, 2022
Blog Cogniflow How Artificial Intelligence Is Changing Business

The answer is yes, absolutely. The only thing that can stop that from happening is the inability to create a vision around it that can feed from you or your company’s creativity. In other words, it is you who can enable the adoption of AI into your job. With this article, you will discover  or take inspiration from some examples on how to adopt AI in your professional life and perform more tasks faster and more accurately than before.

We’ll introduce you to one of the most exciting tools to start this journey: our very own, Cogniflow. This is a blog about leveraging the power of AI, especially the no-code AI for many different professions and use cases. How to get more done and with better performance by adopting no code machine learning software. How the future of work and many jobs go hand in hand with the adoption of AI in every profession.

How and where to start with AI?

This is a question often asked but, ironically, it is not directed to the right people. Usually, we ask people in our network who, most of the time, are limited to their field of expertise and can't provide insight on what may be possible with Artificial Intelligence. Thus we miss a large part of the opportunities it has to offer us since we fail to see that the approach and adoption of AI might be easier and more practical than we think.

We live in exciting times. You see, the AI behind many IT tools is improving at a fast speed, and with it, the solutions to problems you may have, are increasing exponentially.

You might have heard about AI's potential for HR, marketing, logistics, manufacturing, or many other professional disciplines. You’re intrigued and want to know more about this new digital frontier, but where do you start?

With business leaders, scientists, and technology developers predicting a future of AI-driven innovations in every sector, how can you get ahead of the competition by looking into the capabilities of Artificial Intelligence?

Can AI be built and used by other than developers?

We know the many applications of AI all feed from the same fuel: Data. We also know it comes in different forms, but for now, we’ll keep it simple, and focus on data that originated from text, images, videos, and audio, this also come in many different forms once you go deep inside each of them.

We understand that there are some people who might be hesitant about anything artificial, or the concept of getting replaced in the workplace, but the truth is that the quality of new products, services, and solutions in AI, combined with easy-to-adopt frameworks like No-code are now setting the pace for innovation and the democratization of software development, meaning is not just a developers-only matter, but a paradigm change that empowers any type of professional to is able to focus on gathering data from even the most business process sensitive cases.

Let's start by taking a look at some recent and exciting use cases for different disciplines and industries to get a general idea of its benefits.

AI in Life-Sciences

The Life Science industry is one area where big data can have a significant impact for the better. The industry includes sectors such as biotechnology and pharmaceuticals, among others. Recent years have seen an explosion of new discoveries and findings in this field thanks to new technologies like artificial intelligence (AI), predictive analytics, and genomics. This means a large quantity of data to track, store, and analyze.

One major example comes in genetic testing which has grown at an incredible rate since its inception in 2003: from testing 834 genes in 2004 to 133,000 genes in 2017, AI has played a major role in providing faster and more reliable identification and classification. AI is also getting smarter by the day and the frequency that is used in different challenges.

Artificial intelligence can be used to make better, faster, or more efficient processes in scientific research such as:

Microscopic image classification

Pathology diagnosis and mapping

Drug manufacturing

Scientific Imaging

X-ray Analysis

Clinical trials

Cancer treatment

Radiological tests

Disease treatment

Another compelling use case can be found in the detection of electroreceptor cells in animals, recently a team of scientists from a reputable research institute in Latam has proven expertise in studying, classifying, and perfecting an AI model capable of doing this without having to write one single line of any programming language.

AI in Finance and Fintech

In finance, AI is being used as an alternative to human financial advisors—helping people manage their money better by analyzing their spending habits and recommending specific actions that will lead to better long-term returns. It can also be used for fraud detection and prevention, which can help banks save money on staffing costs while improving security for customers who use online banking services.

An example of most will know use cases are:

Credit scoring

Financial advisory

Check identification and classification

Document ID, processing, and classification

Risk management

Transaction security

Manual validation processes enhancement


Successful cases are part of our daily interaction with banks, insurance companies, and other players. The fintech industry can also attest to successful implementations of no-code AI such as this one from MiFiananzas, a South American company that managed to do the complex process of visual validation of checks using object detection and computer vision.

AI in Manufacturing

The use of AI in manufacturing is one of the most promising applications of this technology. There are many instances where AIs have been used to enhance the efficiency of factories and production lines as well as improve quality control by using robots to perform tasks such as assembly line inspection with high accuracy levels. In fact, it is estimated that by 2025 nearly half of all American jobs will be replaced by automation according to a report from the World Economic Forum which means that there will be an increased demand for automated workers who can do these tasks with less margin of error, continuity or bias which will require an influx of workers with these skill sets over time.

Some popular use cases are:

Machine predictive maintenance

Enhancing safety measures and reduction of human injuries

Personal Protective Equipment detection

Precision in quantity and quality visual control (fluids and solids)

Data anomaly detection

Object counting

Defect detection

AI in Marketing

AI is being used in all sorts of ways to help marketers, from helping them plan their advertising strategies to analyzing the effectiveness of their campaigns. With it, marketers have access to a new set of tools for collecting and analyzing data about customers' behaviors and preferences. AI can help you identify patterns in your customer base that would have been difficult or impossible to see before.

Another way AI can be used for marketing purposes is through natural language processing (NLP). NLP allows computers to understand human language as it's written or spoken by humans. This means that a computer can read emails or tweets and learn from them—for example: if someone says "I love your product" online, then an NLP algorithm might recognize this statement as positive feedback about the company's products or services; thus, it could use this information as part of its learning process from here on out when responding back to that person's messages online via email or Twitter.

Some other exciting examples of the use of AI in marketing are:

Personalized communication and advertising

Sentiment analysis

Automated decision making

Content generation

Audience targeting and hypersegmentation

Lead generation and nurturing

Customer behavior analysis

Competitor Analysis

AI in HR, talent attraction

AI is changing the way we work. It's a game-changer that will affect every single industry, and it's already made its mark on the HR industry. With AI-based tools, you can automate many of your recruiting processes—no matter what level a person is at in their career.

AI can help you attract and possibly retain talent by using data to identify key trends and patterns in your hiring process and candidates’ information. It can help recruiters and talent acquisition specialists make smarter hiring decisions, screen candidates more effectively, and manage employee performance more consistently.

AI can help with the following use cases in HR and talent attraction:

Identifying candidates who are a good fit for open positions

Identifying best practices for employee retention

Making recommendations about which employees should be promoted

Suggesting ways to improve the employee work-experience

CV/Resumé parsing

Document ID, processing, and classification

Personalized performance management

Talent engagement

Career training & development

According to a recent study by Korn Ferry Institute and IBM Watson, 35% of respondents said they were actively using AI-driven recruiting tools, while 47% said they planned to implement an AI tool in the next two years.

The possibilities are vast, but the purpose of AI in talent attraction is to make it easier for companies to find and hire the best-matching employees for the roles they will be taking, hence improving the chances for people to find jobs in companies that match with their culture, behavior and long term vision.

AI in logistics and supply chain

AI has a lot of potential to streamline logistics and supply chain management. AI can be used to improve the quality and speed of operations, optimize inventory, and reduce costs.

One of the most common uses of AI in logistics and supply chain management is unstructured data collection, recognition, and classification. AI can gather data from a variety of sources, including real-time sensor data from vehicles or equipment, satellite images, weather reports, and more. This data can then be used for predictive modeling, which helps companies better plan their operations by predicting future needs and alerting them if there is an issue that could cause problems down the road.

Other interesting and proven examples of AI adoption in logistics and supply chain management are:

Visual business-rules validation

Document ID, processing, and classification

Resource planning and management

Demand forecasting

Damage detection/Visual Inspection

Safety measures enhancement

Predictive machine/equipment maintenance

Route optimization/Freight management

Customer service or chatbot improvement

Ok, we get it, AI can help me do my job better, now what?

Now that we covered some examples in which AI can help some industries, nurture and make better their own operations, we certainly hope you can get an insight or inspiration on how this new paradigm can be useful to your own specific job.

Remember that AI is here to be an advantage for professionals of many different disciplines, not a threat. It's up to you to take the leap of faith into a new framework that's eager to welcome bold and adventurous people that want to be hands-on and not outside of the creativity-made-reality cycle.

AI, AutoML, and no-code tools are three of the hottest trends in the business-tech world right now. No-code development simply means that you don't need to be a developer to build an app or website…or an AI model/experiment. You just need a template that you can customize using pre-made templates, which can then be deployed or integrated on any device or platform.

No-code AI allows you to build apps with little or no coding experience. The difference is that instead of using pre-made templates, your app will use artificial intelligence (AI) so it can learn how to do things on its own, and perform tasks and processes on its own.

We have built an AI-powered builder with pre-trained models and also customized models that allow anyone to build and deploy your ideal AI feature and then integrate it into an app or website in one hour or less. Make sure to give it a try. If you are not certain that your use case or experiment can be done with Cogniflow’s No-code AI you can always reach out for a demo or a schedule a personalized call with one of our team members that will clear your doubts and guide you to the best possible path of adoption.

Marcelo Martinez CEO co-founder Cogniflow
Santiago Jaramillo
Head of Growth

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