How AI Impacts Engineering Careers

By Oleksii Popov

As the world becomes increasingly digitized, the role of software development has become more important than ever before. With the rise of artificial intelligence (AI), software development is undergoing a transformation that is changing the way we think about programming. 

For example, AI can be used to automate repetitive tasks, such as testing and debugging, freeing up developers to focus on more complex tasks. AI can also be used to analyze large amounts of data, helping developers to identify patterns and make more informed decisions.  

However, as with any new technology, there are also potential drawbacks and ethical concerns associated with the use of AI in software development. For example, there is a risk that AI could be used to automate jobs that were previously done by humans, leading to job losses and economic disruption. Code generation AI might look like a threat to software development as a career.

Will AI kill software developer jobs? 

These tasks cannot be replaced with AI: 

• Complex problem-solving 
• Adaptability and customization 
• Collaboration and communication 
• Ethical considerations and decision-making 
• Maintenance and updates  

Rather than eliminating software developer jobs, AI is more likely to augment and enhance the work of developers. It can automate certain tasks, increase productivity, and provide tools for more efficient development processes.

By leveraging AI technologies, software developers can focus on higher-level tasks, problem solving, and innovation. The role of developers may evolve, requiring them to acquire new skills and adapt to the changing landscape of technology.

The more productive the engineer, the more complex tasks they can handle, so the demand for highly skilled professionals will always be high.

Less skilled specialists, or those who haven’t made an effort to embrace change and strive for excellence will be in danger. They can be replaced by more productive engineers with AI toolsets or with generative products.

In light of the considerable demand for high-quality software solutions globally, I think there will be a increasing need for human engineers in the future, even with the help of AI. As a result, salaries will increase because the skills and knowledge that human engineers offer are still critical for creating top-notch software products.

I will add that software engineers need to adapt and change in order to meet the expectations of the market. Improve your soft skills and understanding of the concepts, business, and architecture needed to be successful, or you will be replaced – not with AI, but with better engineers.

Will AI kill quality assurance engineer jobs? 

These tasks cannot be done by AI:

• Test design and strategy 
• Complex and exploratory testing 
• Contextual understanding 
• Non-functional testing 
• Collaboration and communication 
• Ethical considerations 

While AI can enhance certain aspects of testing and quality assurance, it’s more likely to be used as a tool to assist and augment the work of QA engineers. AI can automate repetitive tasks, analyze test data, and help identify patterns, but it cannot replace the critical thinking, domain expertise, and human judgement that QA engineers bring to the table.

Instead, AI can enable QA engineers to focus on high-value activities like test strategy, test planning, and results analysis.

QA engineers who are able to handle end-to-end verification of a software product, NFR, governance & compliance, and communication will win the game. 

To remain in-demand in today’s tech landscape, software specialists should: 

• Continuously enhance their technical skills and maintain a high-level understanding of emerging technologies and frameworks. Low-level work can be done by AI or by a cheap workforce. 
• Cultivate strong soft skills, including effective communication, collaboration, and problem-solving abilities to be a nice person to work with 
• Understand architectural principles such as scalability, security, and performance to contribute to complex, scalable solutions  
• Foster a deep understanding of the business requirements that applications are created for 
• Continuously improve their understanding of the complete software development lifecycle, from requirements gathering to deployment, maintenance, evolution, and substitution of software systems 

What can we expect in the future?

As we move forward, I expect that:

• Engineering/Programming/Coding will be done on a higher level with more tools, frameworks, and AI assistance. It means that we can implement more and in less time. 
• AI will take over all the monotonous work. At some point, the tasks regularly handled by mid/senior level engineers will be done by machines on a better level. 

We are living in exciting times!