An engineer in a high-tech manufacturing facility interacts with a holographic projection of a mechanical component, surrounded by robotic arms and advanced machinery.
Engineers who learn to specialize in AI are increasingly sought after to leverage new technologies across various industries.

Artificial Intelligence, or AI, has been a popular topic of discussion in recent years, touching the field of engineering and multiple aspects of life around the world. From customer service chatbots to music recommendations to art and writing, AI has made monumental strides lately, with no signs of slowing down. 

What does artificial intelligence in engineering mean for professional engineers? Let’s take a look at how you might consider adapting AI to your current career – or making a career pivot into a more AI-focused role.

Understanding AI Technology 

At its most basic, AI technology encompasses various techniques that enable machines to simulate human-like intelligence. For those already working in engineering fields, knowledge of the technical advancements in AI can provide a valuable way to get ahead and stay relevant.

Machine Learning, or ML, focuses on developing algorithms that allow systems to learn from data and improve their performance over time without explicit programming. ML can perform tasks like predictive maintenance, optimization, and automation, freeing up the engineer’s time for creative problem-solving.

Neural networks are another subset of AI. They are designed to mimic the functioning of the human brain by processing data through interconnected nodes to recognize patterns and make decisions. Engineers apply neural networks for tasks such as image recognition, fault diagnosis, and control systems to make their work more efficient.

Data analytics involves analyzing vast amounts of data. AI-driven data analytics tools help engineers streamline tasks such as predictive modeling, risk assessment, and performance optimization. 

Let’s take a closer look at the role of AI in the field of engineering.

Applications of AI in Engineering

From predictive maintenance to design optimization and autonomous systems, AI applications are reshaping traditional engineering practices. But what does this mean for engineers?

Predictive Maintenance

Engineers have developed predictive maintenance programs for automated equipment usage. AI-driven predictive maintenance utilizes machine learning algorithms to analyze equipment performance data and predict potential failures before they occur. By monitoring variables like the machine’s temperature, vibration, and usage patterns, AI can optimize maintenance schedules and reduce downtime. Such significant pieces of equipment often last longer, thanks to predictive maintenance.

Design Optimization

For engineers working with design professionals, AI can use advanced algorithms and simulations to identify optimal configurations, enhance product performance, and minimize costs for complex designs. This approach is ideal for the automotive and aerospace industries, where improving performance and minimizing costs are top priorities for manufacturers and consumers.

Autonomous Systems

AI-powered autonomous systems are revolutionizing industries such as robotics, transportation, and energy. These complex systems leverage advanced machine learning and neural networks to make real-time decisions, navigate complex environments, and perform tasks without human intervention. Engineers use these autonomous systems to improve things like self-driving cars and aerial drones.

Robotics Automation

Thanks to ML algorithms in robotic systems, manufacturing processes are becoming more streamlined. Robots can increasingly adapt to changing working conditions, improve precision, and optimize production efficiency. AI robotics automation is popular in production industries like pharmaceuticals and electronics.

Effects of AI on the Engineering Field 

The symbiotic relationship between AI and engineering leads to enhanced problem-solving capabilities and innovation in engineering practices. Because of their technological knowledge, engineers are able to debunk certain myths surrounding this new technology.

The Role of Engineers in the Age of AI 

Engineers already play an increasingly pivotal role in harnessing AI to tackle evolving global challenges and foster advancements in science and technology. Their expertise in understanding complex systems and domain-specific knowledge enables them to leverage AI tools for problem-solving and process optimization. By integrating AI into workflows, engineers deliver solutions that align with evolving technological landscapes. They’re then able to lead innovation across any field where engineering is used.

Collaboration Between AI Systems and Engineers 

Engineers are constantly finding new ways to incorporate AI into their work. Working with AI leads to increased productivity, efficiency, and creativity within a broad spectrum of engineering subfields. AI handles many of the repetitive tasks that can take up an engineer’s time. Engineers can then focus on higher-level decision-making, innovation, and problem-solving. 


Engineering Careers in the AI Era 

In today’s AI-driven era, existing engineering careers are evolving rapidly, with new opportunities constantly emerging in specialized AI-related fields. Engineers who learn to specialize in AI are increasingly sought after to leverage new technologies across various industries.

Emerging Roles in AI Engineering

AI changes every day. There are constantly new roles for engineers to explore, whether they’ve worked with AI before or are brand-new to this specialty. Some of the most popular right now include:

  • Machine Learning Engineer: Their expertise lies in developing and implementing machine learning algorithms that analyze and interpret large datasets, driving insights and automating processes.
  • Data Scientist: Data scientists provide decision-making assistance by applying statistical analysis, machine learning techniques, and domain knowledge to complex data.
  • Robotics Specialist: A robotics specialist designs, engineers, and maintains robotic systems powered by artificial intelligence, enabling automation in a variety of industries.
  • AI Architect: An AI architect designs and oversees the implementation of AI systems to ensure they are aligned with business goals, technical specifications, and ethical standards.
  • Intelligent/Information Systems: Professionals in this role focus on designing systems that use AI to manage and process information efficiently so that the right data is available for decision-making and operational purposes.
  • Cybersecurity: Cybersecurity specialists leverage AI to boost security measures, detect and respond to cyber threats, and safeguard data against potential breaches.
  • Computer Science: This broad field includes roles such as software developers and researchers who advance AI technologies and integrate them into various applications.

Skills and Training for AI-Driven Engineering 

Like many other subfields of engineering, employers look for specific skills in potential AI-related job candidates, even those with extensive engineering experience. This is by no means an exhaustive list, but it’s a good starting point for current engineers considering a shift to AI-related fields.

  • Programming: Proficiency in programming languages such as Python, Java, or R is almost universally required for developing AI algorithms. These languages form the basis for ML models and large data-processing tasks.
  • Data Analysis: Engineers need strong analytical skills to extract insights from data, identify patterns, and make data-driven decisions. Engineers should have extensive experience using tools like SQL, Pandas, or Tableau.
  • Interdisciplinary Collaboration: One of the “soft skills” required in AI-focused jobs is the ability to work as part of a team. Engineers often collaborate with data scientists, domain experts, design professionals, and business stakeholders to develop comprehensive solutions that meet diverse needs and requirements. 

Gain Relevant Skills for a Changing Engineering Landscape with JHU EP 

If you’re a professional engineer looking to make your mark in AI, consider a master’s degree or graduate certificate from Johns Hopkins University Engineering for Professionals (JHU EP). Our online Artificial Intelligence Master’s Program is one of the nation’s first online artificial intelligence master’s programs designed for professional engineers like you. Find out more about earning your graduate certificate or master’s degree today and prepare for the career of the future!