The human/robot collaboration trend will continue to grow in the coming years.
There is a growing demand for professionals specialized in artificial intelligence, among which are: machine learning engineers, robotic scientists, data scientists, research scientists or business intelligence developers.
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.
Although hundreds of AI tools 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.
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.
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 serves industries like retail, banking, finance, etc., even investment bankers use IPA to identify inconsistencies in research data, which is almost impossible for humans to remember.
As technologies grow, so make security threats. Data theft and phishing will continue to be a problem for years to come. AI will prevent cybercrime with enhanced cybersecurity measures 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.
Artificial Intelligence is a unique technology that, together with the power of the Internet of Things (IoT), provides a compelling 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, intelligent 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 anticipate human needs and initiate other machines and processes without human intervention.
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 prevalent in the future. These tools help companies add customization without having to know the complex ML development process.
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) track their employees, identify them, etc.
These chatbots are capable of providing better customer service automation. Conversational AI chatbots will continue to learn and improve in terms of understanding and to communicate with customers. These chatbots use Machine Learning (ML) and Natural Language Processing (NLP) to understand commands, providing natural communication mimicking human conversation with users.
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 digital assistants like Siri, Alexa, and VERA. This trend of human/robot collaboration will continue to grow.
The job opportunities available from the advent of artificial intelligence will only 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 complicated 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 many 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 various 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 are machine learning engineers, robotic scientists, data scientists, research scientists, or business intelligence developers.
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