Introduction to Centric AI
The rapid advancement of technologies and the introduction of Industry 4.0 enable organizations to incorporate Artificial Intelligence into their workflows and empower organizational activities with automation.
Industrial AI helps with continuous improvement in the underlying infrastructure to enable the following:-
-
The Rapid Development of Artificial Intelligence Applications
-
The reduced Deployment cost of AI technologies
As Software and sensors become cheaper and exceptionally better, collecting and managing vast amounts of data becomes much easier, faster, and more affordable. Also, with high-performance computing systems, the training of models and algorithms is quick.
Information Systems (IS) make all these advancements possible. These systems are built using software, hardware, and telecommunications systems to collect, process, and distribute information for potential analysis and decision-making.
To make AI responsible and support technologies while designing, developing or managing systems that learn from data. Click to explore about our, Responsible AI Principles and Challenges
Let's look at some important aspects of information systems in industrial AI.
Industrial AI
As the name implies, the research, development, and general application of AI in Industrial settings are denoted by Industrial AI. For a more informative aspect, Industrial Artificial Intelligence is the implementation of its practices in industrial use cases like demand and supply chain management, report generation, analytics, and automation of processes for enhanced efficiency and to make more informed decisions. The Industry setting is associated with the research and development of industry-centric use cases, including manufacturing, retail, construction, transportation, utilities, etc.
Some recent research in Industrial Artificial Intelligence examines how these industry-centric applications differ and what their combination holds for the future of the Industrial Revolution. The introduction of industrial AI has caused disruptive changes in all industries. It enables the Industry 4.0 paradigms, such as Cybersecurity, Data Analytics, and Management, to combine with it to develop and change Industry Information Systems.
AI and data together come with patterns and help to make decisions. Click to explore about our, Ethics of Artificial Intelligence
How did Industrial AI benefit the current Industrial Revolution?
Artificial Intelligence is found to be a turning point in optimizing the current workflows and automating the processes to enable innovative initiatives for organizational growth and to drive business value. Let's see some of the benefits of AI in brief:
Research and Analytics
With the benefits of innovative and fast computing capabilities, AI-enabled systems and machine learning can analyze vast amounts of data. Industry Leaders can also integrate predictive models and algorithms to process data and help identify possible outcomes from various solutions.
Reduced Error Percentage
It helped improve the processes with an error-free approach. Humans cannot keep up with AI and computing systems' capabilities, and overexerting efforts sometimes lead to errors. This is where Artificial Intelligence Capabilities come into play.
It can provide a 24/7 working environment and offers effective and efficient work with fewer errors. Repetitive tasks are something humans have challenges with, and Artificial Intelligence can handle those tasks without getting tired.
Customer Experience
It is currently being implemented in consulting and customer-centric industries such as retail, hospitality, consumer technology, etc. The main reason behind this is that with the adoption of the internet and smart devices, the customer base for various sectors is increasing exponentially.
Handling queries and complaints is becoming more complex daily. With AI functionality in customer support, like chatbots, organizations can address issues accurately and provide quick replies to customers. They can provide a desired digital experience with a personalized touch.
Automation Purpose
The main objective of artificial intelligence, which has led to the massive growth of industries, is automating processes to reduce human effort and enable efficiency with room for innovation.
Another advantage is that it can free up resources that can be utilized in other places for greater efficiency.
A hassle to keep track of all that is going on, and it takes a lot of manpower to tackle it. Click to explore about our, AI-based Video Analytics
What are the challenges with Industrial AI?
Although being a lifesaver for many industries, it also has some disadvantages.
Algorithm Challenges
AI algorithms are designed for a specific model or function. They do not have a mix-and-match capability to be used in place of a whole different algorithm. For Example, they fit a circle in a triangle-shaped box. Here are some points to consider:
-
High precision Systems
-
The explainable result to satisfy real-world entities
-
Major Reliance on Data
Data Challenges
AI Models work with a lot of data, and a clean database is essential to operating with accurate results and providing efficiency at every step. Owning Data is considered more crucial than owning the algorithm, as Data is key to all cases.
What are the AI Applications in Industrial Settings?
Industrial AI is divided into three main categories:-
In-Process Applications
This includes incorporating AI to monitor processes to find errors or evaluate processes. These are the applications that are used to keep the processes in line. Some critical applications in this category are:-
-
Processes Monitoring
-
Quality Inspection
-
Fault Detection
Control and Optimization Applications
These applications are used indirectly rather than actively participating in the operations. Identifying or finding alternative sets of information or tasks is considered to optimize the processes and automate the approach. This category mainly includes-
-
Robotic Control
-
Optimal Control
-
Parameter Optimization
-
Predictive Analysis
-
Human Monitoring,
-
Scheduling
Support Application
These Applications do not directly influence the process but provide various support utilities to keep the process going without any disruptions. Applications that are included in the Support Application are:-
-
Cybersecurity
-
Data Processing
-
Decision Support System
The self-explanation capability of Explainable AI increases accountability. It also enhances the trust of customers and stakeholders. Click to explore about our, Explainable AI in Insurance Industry
Which are the industries most affected by Artificial Intelligence?
AI holds a high position in most industries, but some selections need AI more than others. Here are some of the industries that can use AI to modernize their operations for optimal productivity and efficiency:-
Finance
In the coming years, the finance industry will encounter AI-led digital advisors to provide an enhanced customer experience.
Bionic advisory practices with Machine learning capabilities and human insights could be considered the most effective customer support facility and can be more efficient than machines and humans alone.
Healthcare
According to McKinsey, AI applications in healthcare can include patient tracking, health checks, and symptom identification for personalized care and better health outcomes.
Marketing and Advertisements
With Enhanced customer experience and a tailored marketing approach, AI can track the content planning and distribution that is most likeable among the target audience.
More Ways to Explore Us
Artificial Intelligence (AI) Solutions on Edge
Responsible Artificial Intelligence in Government
Top 8 Real-Time AI Applications across Industries
