- The human / robot collaboration trend will continue to grow for years to come.
- There is a growing demand for professionals specialized in artificial intelligence, among which are: machine learning engineer, robotic scientist, datascientist, research scientist or business intelligence developers.
Institute of Innovation by ESIC- has presented the report Innovation Series: “Innovation trends in Artificial Intelligence” . The study addresses the main trends and innovations that are being developed in Artificial Intelligence and how this technology is impacting businesses and companies.
During the presentation, María Albalá, director of the Innovation Hub at ICEMD - Institute of Innovation by ESIC , was accompanied by Juan Aguilar, director of the Master in Digital Marketing at ESIC and CMO at Shapelets.
APPLICATION OF ARTIFICIAL INTELLIGENCE
As the integration of these tools progresses in organizations, understanding the differences between these different types of AI-compatible tasks can help us determine the best tool for each job, figure out the best way to support that tool with human employees. and, ultimately, optimizing collaboration between humans and machines.
“ As the development of AI progresses, it will become democratized, as has happened with other technologies, however complex they may be. There will come a time when many of the tools we use every day will have an AI base that will give them much higher capabilities than they currently have and, in addition, will be transparent for the user ”, María Albalá has specified .
Although there are hundreds of AI tools that solve business problems, we can group them into four categories : simple tasks, simple tasks that require ethical decision making, creative tasks with limited ethical implications, and tasks that require both creativity and ethics.
With this simple framework, business leaders can begin to control the human capabilities they will need to invest in to take full advantage of these new tools.
1. Add intelligence to RPAs
Many companies are turning to RPA (Robotic Process Automation) to improve their workflows. An RPA can handle and automate repetitive tasks. However, the integration of AI with RPA can take automation and task control to the next level. The collaboration of these two technologies has the potential to address many problems in real time. This year we will see more innovative advancements in the automation industry with AI and RPA.
2. Intelligent Process Automation (IPA)
Intelligent Process Automation (IPA) is another use case for automating unstructured content processes in enterprises. This technology can also collaborate with other technologies such as Cognitive Automation, Machine Learning, RPA, and Computer Vision for robust results. Also, IPA is serving industries like retail, banking, finance, etc., even investment bankers use IPA to identify inconsistencies in research data, which is almost impossible for humans to identify.
3. AI for cybersecurity and data privacy
As technologies grow, so do security threats. Data theft and phishing will continue to be a problem for years to come. With enhanced cybersecurity measures, AI will prevent cybercrime by detecting fake digital activities and transactions by following patterns to detect criminal activity. We will see how more and more organizations implement AI to manage their cybersecurity tasks.
4. AI with Internet of Things
Artificial Intelligence is an extraordinary technology that, together with the power of the Internet of Things (IoT), provides a very powerful solution for companies. The combination of these two technologies will bring different changes in the automation industry. In the future, smart home devices like Google Nest, Smart Plugs, smart locks, etc. they will predict and serve human needs. Currently, devices only work on command, but by connecting with AI technology, these devices can automatically predict human needs and initiate other devices and processes without human intervention.
5. Machine Learning for Hobbyists
Machine learning will allow non-experts to understand and use machine learning (ML) algorithms. So we will see an increase in the number of data scientists. Tools like Google Cloud AutoML will be more popular in the future. These tools help companies add customization without having to know the complex ML development process.
6. Advances in computer vision
Computer Vision can monitor whether safety procedures (masks, protective equipment) are being followed to ensure safety in the workplace. This technique helps companies in different sectors (health, aviation, retail ...) to track their employees, identify them, etc.
7. AI-based chatbots
These chatbots are capable of providing better customer service automation. Conversational AI chatbots will continue to learn and improve in terms of understanding and communicating with customers. These chatbots use Machine Learning (ML) and Natural Language Processing (NLP) to understand commands, providing natural communication mimicking human conversation with users.
8. Towards a hybrid workforce with AI
- The workplace is evolving into a hybrid workforce, where the human workforce will collaborate and work with bots to do their jobs more efficiently. In recent years, we have noticed the emergence of digital assistants like Siri, Alexa, and VERA. This trend of human / robot collaboration will continue to grow.
" The next generation of Big Data Analytics and Artificial Intelligence platforms should allow us to work with a greater volume of data sources and with information in real time and at an affordable price ," said Juan Aguilar .
WHAT PROFESSIONAL PROFILES ARE COMPANIES LOOKING FOR?
The job opportunities available from the advent of artificial intelligence are only going to grow as technology continues to innovate. Gartner experts predict that Artificial Intelligence will create more jobs than it eliminates. Each role, however, requires education and training to meet the needs of the industry.
Artificial intelligence is highly scientific. After all, mimicking the human brain using machines is a very difficult problem to solve. The skills you'll need to pursue AI as a career are varied, but they all require a great deal of education, training, and focus. With that said, there are a wide variety of career types available in AI and machine learning, ranging from higher-level research to low-level programming and implementation.
Most careers in artificial intelligence require training work and experience in a variety of subjects related to mathematics and science.
There is a growing demand for professionals specialized in artificial intelligence. Companies need specific profiles that they cannot find, among which stand out machine learning engineer, robotic scientist, data scientist, research scientist or business intelligence developers.
“ Every time we see more, in eminently technical or technological professions, that knowledge of the business, how its processes are, knowledge of the sector in which the applications you develop will move, what our clients demand, as well as interpersonal and communication skills. communication, they are a rising value ”, comments María Albalá, director of the Innovation Hub of ICEMD - Institute of Innovation by ESIC
In this sense, Juan Aguilar, director of the Master in Digital Marketing at ESIC and CMO at Shapelets , adds that “ AI will represent the fourth leap in digital ecosystems and to take advantage of its full power, new profiles will be necessary, such as Data Scientists and new tools that allow them to extract all the value of the data . "
“ In the field of AI, hybrid profiles are increasingly in demand that are capable of understanding business needs and not only speaking to them in their language, but also explaining the technology in a way that is understandable to a non-technologist. AI is based on data and processes, but you also have to know the context, both the relationship between them, as well as the meaning and implications. In the same way, business profiles need to know the capabilities and potential of the technology, to be able to evaluate its possible use for the business. The boundaries between business and IT are blurred to generate maximum value ”, adds Albalá.
Discover in the report more than 50 examples of Artificial Intelligence tools applied to the different areas of the company: business intelligence, consumer marketing, finance, security, human resources, engineering or new technologies, among others.
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