Will AI Take My Tech Job?

It took Chat GPT four days to reach one million users, and less than two months to grow to 100 million. While it might not have broken the record for fastest adoption, the speed of its growth was certainly an outlier — especially for an innovation so poised to change the fabric of our daily lives.

Almost 90 years ago, at the tail end (but still the depths) of the Great Depression, America was in the midst of a technological revolution poised to forever alter the employment landscape. New machinery was transforming jobs everywhere from farms to factories. The question then, as today, was whether these advancements — simplifying life for many — were simultaneously making many thousands of jobs obsolete.

An essay by Karl T. Compton, a renowned scientist of the time, addressed this issue with much of the same wisdom we might apply to the boom of AI and learning language models of the last year:

How, he questioned, should we think about “the loss of work due to obsolescence of industry or use of machines to replace workmen or increase their per capita production? Are machines the genii that spring from Aladdin’s Lamp of Science to supply every need and desire of man, or are they Frankenstein monsters that will destroy the man who created them?”

(Read more about Compton and his essay in MIT’s technology review).

Knowing that these questions have concerned humankind for almost a century — or, almost every time there is a major disruption in the way things are done — we’ll discuss how AI represents another revolution in the cycle of technology; which tech jobs will be most and least affected; and how to prepare yourself to emerge from this important moment with the skills and perspective to excel.

Engineering and Other “Maker” Jobs Will Change Most

While there may be short-term negative impacts on human jobs, in the long term, such technologies lead to value creation, wealth generation, and overall improvements in quality of life, drawing parallels with the industrial revolution.

The impact of AI on software development is notably significant. Tools like Github Copilot or AWS Code Whisperer can perform sixty to seventy percent of coding tasks. AWS even claims that developers can complete their tasks 57% faster with AI assistance.

This efficiency is due to the logical and mathematical structure of programming languages, which aligns well with the functionality of large language models. The patterns in structured coding languages are more predictable than in natural languages, making it possible for AI to generate a significant portion of your code, given the appropriate prompts.

However, the solution's structure and architecture must still be crafted by the software developer. The majority of the underlying code can be generated, but the overall design and direction still require human input. This means that the nature of software development will likely change:

• Productivity Boost: Developers can focus more on architecting solutions and less on writing code, significantly cutting down development time.
• Improved Code Quality: Generative AI can optimize code efficiency and facilitate writing better test cases, leading to higher-quality systems.
• Increased Importance of Testing Skills: As a large portion of code is generated by AI, developers will need to enhance their code comprehension and testing abilities.

Trends to Expect Tech-Industry-Wide

1. Increased Productivity for Software Development: The automation of basic coding tasks by AI, far from rendering the software developer obsolete, significantly augments their capabilities. It introduces a shift towards more complex and creative aspects of software development, such as solution architecture and prompt engineering. The emphasis moves from mundane tasks to strategic thinking and problem-solving, acknowledging that the skills required in the tech industry are ever-evolving.
2. Empowerment of Non-Developers: Generative AI and no-code tools are breaking down the barriers to software creation, enabling those without traditional coding skills to build applications. This democratization suggests a redefinition of what it means to be a software developer, with a growing industry around no-code platforms. Tools like Scratch and open-source frameworks mean that starting a project doesn't always require building from the ground up. This lowers the entry barrier for innovation and allows more people to bring their ideas to life.
3. Agents, Copilots, and Pair Programming with AI: The emergence of AI agents and copilots in software development is akin to the transition from writing to editing. These tools can generate code, suggest improvements, and automate repetitive tasks, allowing developers to focus on the more nuanced aspects of their work. It's a partnership where AI handles the legwork, and humans guide the creative and strategic direction.

Roles to Consider

Skills and Jobs at Risk

• Commoditization of Basic Coding Skills: The value of vanilla coding skills — basic syntax for popular languages like Python or R; identifying well-documented bugs; HTML for standard webpage layouts; and more — may decrease, affecting wages and job availability in software development.
• Routine and Repetitive Tasks: Jobs that involve routine, repetitive tasks are more likely to be automated by AI. This includes roles focused on data entry, basic coding tasks, and even some aspects of software testing that don't require complex decision-making or creative thinking.
• Simple Decision-Making Roles: Positions that involve making decisions based on simple, clear-cut rules can also be automated, as AI systems can quickly analyze data and apply predefined rules at scale. This might include QA support roles, Data analysts, IT helpdesks, and others.

Jobs Likely to Grow or Evolve

• Creative and Strategic Roles: Jobs that require creativity, strategic thinking, and complex problem-solving are less likely to be replaced by AI. AI can augment these roles by automating the more mundane aspects of the work, allowing professionals to focus on higher-level tasks.
• AI Development and Maintenance: The rise of AI creates demand for new roles, such as AI specialists, data scientists, machine learning engineers, and AI ethics officers. These positions involve developing, implementing, and managing AI technologies, as well as addressing ethical considerations associated with AI use.
• Interdisciplinary Roles: Roles that require a combination of technical skills, domain-specific knowledge, and soft skills (such as communication and empathy) are less likely to be automated. This includes positions where you need to interpret AI results, interact with stakeholders, or manage teams working on AI projects.

Check out this list, which includes forthcoming AI roles with job descriptions and salary predictions.

AI's impact on tech jobs unfolds as a narrative of transformation, where innovation not only shifts the nature of work but also redefines roles, enhances creativity, and allows more people to create, ultimately putting the emphasis on strategic and original thinking versus actual execution.

How to Future-proof Your Tech Career from AI

1. Learn AI Technologies: Embrace lifelong learning to stay ahead of AI advancements. This includes learning about AI and machine learning, understanding how these technologies can be applied in your field, and acquiring new skills that are in demand. (Some relevant new skills and tools might include deploying and monitoring AI models with tools like Docker or Kubernetes; understanding how to clean, preprocess, and analyze data in data libraries; and more.) It is also important to diversify your skillset to include areas less likely to be automated, such as creative thinking, problem-solving, leadership, and communication.
2. Invest in Strategic Leadership Skills: Focus on developing skills that are uniquely human and more difficult for AI to replicate, such as empathy, emotional intelligence, and the ability to navigate complex social situations. Check out this article about the importance of soft skills for getting you to the next stage of your career.
3. Work with AI Every Day: Learn to work alongside AI technologies every day as part of your job function. Understanding how to leverage AI tools for productivity, creativity, and innovation can make you an invaluable asset to any organization.

Further, future-proof your career with suggestions from this LinkedIn article.

Looking Forward: The Future of Tech Jobs in an AI-Native World

As we navigate this period of massive transformation, the future of tech jobs seems poised for a renaissance rather than a reduction. The focus shifts from fearing job displacement to embracing the potential for AI to enhance human creativity, efficiency, and problem-solving capabilities. Education and continuous learning emerge as critical components, ensuring that the workforce remains adaptable and skilled in leveraging AI technologies.

The implications for the tech industry are profound: roles will evolve, new skills will be in demand, and the nature of what it means to "create" will be fundamentally altered. Far from making human skills obsolete, AI acts as a catalyst for innovation, pushing us to redefine our roles and the value we bring to the tech industry.

Much like Compton insisted in the 1930s, the short term may prove rocky — but it will be in service to the promise of more opportunity to come.

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