Large technology companies are introducing their own generative AI tools in order to compete in the lucrative AI market. This development poses a significant threat to many jobs, including those of software engineers.

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According to a recent study, it is predicted that artificial intelligence could potentially replace 25% of current tasks in the workforce, particularly in the engineering field where 37% of tasks could be fully automated.

However, the question remains whether AI will completely take over tech jobs or if it will simply enhance and streamline existing roles.

To shed light on this issue, we turned to the experts working directly with AI technology, Codepro engineers.

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AI continues to require oversight from a human supervisor

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“In my role as a data engineer, I deal with large amounts of data every day. I have found that tools like ChatGPT and other AI agents can be useful for generating code snippets and sample files. However, AI technologies like these can make errors and inaccuracies due to a lack of context and specific data knowledge. This means that significant time and effort are needed to write and refine prompts for these systems.

Additionally, real-world datasets used in AI and machine learning are often complex and varied. While machines can help with data cleaning, data engineers are essential for overseeing the entire data process and identifying potential issues.

Furthermore, even if AI outputs are satisfactory, understanding the logic behind their decisions can be difficult, making debugging and customization challenging tasks."

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— Tina Powell, Senior Data Engineer

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The emergence of the 'prompt engineer'

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“AI technologies have the potential to liberate developers from routine tasks and enable them to focus on higher-level problem-solving and solution designing. Similar to how calculators assist mathematicians in handling complex computations, AI could serve as a valuable tool for engineers.

The progress of AI is anticipated to be primarily powered by advancements in natural language processing (NLP) and computer vision. Prompt engineering, which involves improving AI instructions, will play a crucial role in shaping the future of AI.”

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— Martin Mitchell, ML Engineer

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ChatGPT with computer vision capabilities is coming soon

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“I specialize in assisting businesses in automating specific, repetitive tasks within their operations. Unfortunately, the capabilities of AI in computer vision for automation are currently limited. It is difficult to automate the gathering of high-quality visual datasets as it requires input from human experts and a vast amount of knowledge. Additionally, processing high-dimensional images for image-based models requires significant computational power and memory.

Although there are advancements in developing visual models for computer-driven image recognition similar to ChatGPT, existing visual datasets are not diverse enough for effective training. However, the possibility of a ChatGPT equivalent for computer vision emerging in the near future could usher in a new era of true artificial intelligence.”

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— Carolyn King, ML Engineer

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Do you experience anxiety about AI? Instead of seeing it as a threat, view it as a positive opportunity.

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AI is often compared to the Industrial Revolution because, like machines freed humans from manual labor, AI helps uncover hidden patterns, simulate scenarios, and predict outcomes in major engineering disciplines. This can lead to groundbreaking discoveries in the future.

While the automation of code-writing and faster delivery lead to increased productivity, they also come with technical debt. This requires developers to adapt their methods to work alongside AI tools effectively.

AI will raise the bar for engineers' expertise. As AI takes on routine tasks, engineers must continue to expand their knowledge to work harmoniously with AI solutions. Remember, we created AI, so treat it as a valuable partner rather than an enemy.