AI Career Landscape: Opportunities Beyond Coding

The International Monetary Fund (IMF) released its new projections related to the impact of AI technologies on employment. TThis IMF report is somewhat harsher compared to the employment outlook reported by the Organization for Economic Co-operation and Development (OECD). IMF predicts that 40 percent of global employment is at risk because of AI while OECD expects around 27 percent employment to be at risk due to AI.

In 2023, we saw how AI, such as code assistant tools, is becoming essentials to the developer experience and allowing developers to scale the development process. This trend is expected to increase in 2024, and we should anticipate more companies adopting AI beyond just software development work. At the same time, according to layoffs.fyi, more than 262,000 people were laid off in 2023 in the tech sector and in the last 15 days of this January 2024, more than 9,000 people have been laid off - many of them due to potential AI impact, as per Resume Builder survey.

While both the IMF and the OECD may be right in their own analyses, the bigger question is: How can we be prepared for the upcoming storm (or tsunami)? What can we do not just for ourselves but also for our loved ones who may be at risk among those 40 percent? The good news is that we now know AI is here to stay and isn't going away – in fact, more and more companies will embrace AI in the coming years. Let's dive into this article to understand how everyone can embrace AI, learn about it, and apply it in their current roles or get a head start in capturing future AI-led roles

The traditional roles of machine learning engineers, data scientists, and research scientists, who in the past focused on AI and ML, will continue to do so but with more rigorous timelines. Observing how AI is shaping up, it is highly likely that we will see some of the existing roles transform into newer AI-related roles:

1. Software engineer to AI engineer: As we embrace AI, most software engineering functions will require some interaction with AI. This could involve developing prompts, interacting with AI models, customizing functionality via Retrieval Augmented Generation (RAG), or even stretching to fine-tune models.Learning Path: Begin with a strong foundation in programming (Python, R, Java), an understanding of data structures, algorithms, and statistics. Gain familiarity with cloud-based AI platforms, such as using ChatGPT models or Amazon Bedrock, to develop functionality through prompt engineering, function calling/agents, and/or RAG mechanisms. Continuous learning is crucial, as AI technology evolves rapidly. Engaging with AI communities or professional groups is key to staying updated on AI industry trends and advancements.
2. Product Manager to AI Product Manager: It may be a bold prediction, but I have no hesitation in saying that most future products will incorporate a major AI component. If a product manager isn't AI savvy, they risk being replaced by someone with AI expertise. An AI Product Manager oversees the development of AI products from concept to launch, involving understanding customer needs, defining the vision for AI-based products, coordinating with engineering teams, and ensuring that the product meets market needs. They also need to be cognizant of the ethical implications and limitations of AI technologies.Learning path: A solid understanding of AI and machine learning concepts, experience in product management, skills in market analysis, and user experience design. Knowledge of the technical aspects of AI is essential for effective communication with engineering teams. Leadership and project management skills are also crucial. Engaging with AI communities or professional groups is important to stay updated on AI industry trends and advancements.
3. Compliance specialist to AI Ethics specialist: Many banks and regulatory-driven companies employ compliance specialists, whose sole responsibility is to ensure that the bank follows appropriate regulatory standards. With many of these functions being automated with AI, it's important to apply these skills in AI ethics. An AI Ethics Specialist focuses on developing frameworks and guidelines to ensure the ethical use of AI. This includes addressing biases in AI algorithms, ensuring transparency, and safeguarding privacy and data security.Learning path: Gain an understanding of AI technology basics, ethical and philosophical principles, legal aspects of AI, data governance, and bias detection and mitigation techniques. Engaging with AI communities or professional groups is crucial to stay updated on AI industry trends and advancements.
4. Customer support to Customer success: In the shift from Customer Support to Customer Success, chatbots have become widely used for addressing simple queries from customers. This change allows those in customer service or support roles to provide valuable insights about customers’ preferences, history, and past issues, thus enabling more personalized and efficient support. With AI handling repetitive and straightforward tasks, customer support staff can now focus on more challenging and rewarding aspects of customer service, such as solving complex problems and building long-term customer relationships.Learning path: Customer support personnel should be trained in using AI-based tools and understanding the basics of AI technology. Additionally, developing soft skills like empathy, problem-solving, and communication is crucial for effectively handling more complex customer interactions. Engaging with AI communities or professional groups to stay updated on AI industry trends and advancements is also important.
5. QA engineer to Human evaluator: QA Engineers transitioning to Human Evaluators face new challenges. Unlike traditional software, AI systems continuously learn and evolve. This change means that QA engineers must validate the code, the data used for training models, and the models themselves. Their role expands to ensuring AI algorithms perform as expected under various conditions and checking for biases in the data that could lead to skewed or unfair outcomes. They also have the responsibility of confirming that models make correct predictions and are resilient to changes in input data. In the AI world, QA engineers need to ensure that AI applications comply with ethical guidelines and regulatory standards, especially in sensitive industries like healthcare and finance.Learning path: Start by understanding the fundamentals of AI, machine learning, and data science. Enhance your skills in programming languages commonly used in AI, such as Python. Learn scripting for automated test cases and gain a basic understanding of how AI models and algorithms work, with a focus on areas like neural networks, NLP, and computer vision. Learn about data preparation, cleaning, and basic analysis, which are crucial for testing AI systems, potentially using AI-augmented software testing tools. Engaging with AI communities or professional groups to stay updated on AI industry trends and advancements is also important.
6. Technical writer to Content Strategy: In a world where AI can generate content typically produced by technical writers, these professionals can focus on curating, editing, and refining AI-generated first drafts or basic content. They ensure the content meets quality standards, is accurate, and aligns with the intended audience and purpose. As AI handles routine content generation, technical writers can shift their focus to more complex, creative, or strategic content that requires a deep understanding, critical thinking, and a human touch — areas where AI still lags. There is potential for technical writers to take a broader role in content strategy and management, overseeing how content is used and consumed across different platforms, and ensuring it aligns with business goals.Learning path: Develop an understanding of the fundamentals of AI, machine learning, and data science. Enhance skills in data handling, processing, and visualization. Familiarize yourself with AI writing tools that can be incorporated into your daily work. Learn the basics of prompt engineering to effectively extract information from models. Engaging with AI communities or professional groups to stay updated on AI industry trends and advancements is also crucial.
7. Project Manager to AI Project Manager: As AI is integrated in the daily lives of the enterprise users, most of the projects will have AI as a core component. Traditional project managers who are not exposed to AI, this evolution brings both new opportunities and demand for adaptation. AI projects are often data-centric, involving data collection, processing, and analysis. Project Managers need to ensure that data is handled efficiently, ethically, and in compliance with regulations, such as data privacy, bias in AI models, and transparency. AI projects can be more unpredictable than traditional software projects due to the exploratory nature of AI and machine learning. Project Managers must be adept at managing uncertainty and adjusting plans as projects evolve. Project managers are good change agents and AI project requires someone managing change, and ensuring stakeholders understand the benefits and limitations of AI technologies.Learning path: Understand the foundation of AI and ML, and learn how AI is used in the industry you operate in, including common use cases and potential benefits and challenges. Understand the basics of data management, including data collection, processing, and storage, given the importance of data in AI projects. Engaging with AI communities or professional groups to stay updated on AI industry trends and advancements is also crucial.
8. Sales: If the new generation of salespeople is not leveraging AI to identify opportunities, create personalized sales approaches, and use AI for sales forecasting, they are missing out on the competition. Utilizing AI to identify and prioritize potential leads based on their likelihood to convert can yield significantly different results. Employing AI to tailor sales pitches and communications, such as AI-generated emails, based on customer data, results in a more personalized approach. Using AI-powered CRM to enhance the customer relationships and insights. Additionally, leveraging AI to automate mundane tasks, such as setting up meetings and following up with customers, can be highly beneficial.Learning path: Understand the foundation of AI and ML and learn how AI is used and applies to sales. Develop data analytics skills to interpret customer data and sales metrics. Gain a deep understanding of AI-powered CRM tools and integrate AI insights into sales strategies. Engaging with AI communities or professional groups to stay updated on AI industry trends and advancements is also crucial.
9. Marketing: In marketing, while AI is capable of generating more content than humans can (including text, images, and videos) in a very short duration, marketing personnel must elevate their strategies. They should start leveraging AI for deep customer insights and predicting market trends. This includes creating highly targeted and personalized marketing campaigns based on AI-driven customer segmentation. While AI develops content, it's crucial to optimize this content for SEO - an area where AI can also be supportive. Additionally, leveraging AI for analyzing social media trends and customer engagement is beneficial.Learning path: Understand the foundation of AI and ML, and learn how AI impacts marketing and customer engagement. Develop knowledge of AI applications in digital marketing, including social media, content management, and SEO. Enhance skills in analyzing and interpreting market and customer data. Engage with AI communities or professional groups to stay updated on AI industry trends and advancements.
10. Teachers: Teachers play a noble role in educating the next generation on a variety of subjects. With advancements in AI, teachers can start leveraging AI for a multitude of tasks. This includes automating time-consuming tasks such as grading assignments and managing paperwork, which frees up more time to focus on teaching and interacting with students. AI provides teachers with advanced tools and resources, like interactive content, simulations, and educational games, making teaching more engaging and effective. AI systems also offer real-time feedback on student performance, helping teachers identify areas where students may need more support or advanced materials. Additionally, AI can predict future learning outcomes or identify potential learning difficulties, enabling early intervention to support student success.Learning path: Understand the foundation of AI and ML, and learn about specific AI applications relevant to education, such as adaptive learning systems and AI tutors. Familiarize yourself with AI tools and resources that can be integrated into the classroom, including learning management systems with AI capabilities, such as Blackboard Learn. Engage with AI communities or professional groups to stay updated on AI industry trends and advancements.

The impact of AI spans multiple industries and roles, making it a very extensive topic to cover all these roles in one article.

A common theme emerging from these diverse roles is our ability to adapt and embrace change. This includes the ability to learn new technologies, such as the fundamentals of AI/ML, and the importance of engaging in AI communities to stay updated on AI industry trends and advancements.

You may be wondering if there are any courses I recommend to learning AI fundamentals, well you are in luck:

1. AWS's AI ML Course
2. Google Cloud's ML Course
3. [bias alert ahead] While both of the above-mentioned courses are excellent, if you're looking for a vendor-neutral option, there's a new AI fundamentals course that was recently launched on Udemy. It has received a rating of 4.9 out of 5 and is primarily designed for individuals who may not have a deep technical understanding of AI/ML. If you need a discount voucher for the course, feel free to direct message (DM) the author of this article.

While a course can provide foundational learning, it's crucial to stay updated with the rapidly evolving AI field. This includes keeping abreast of industry trends, advancements, and understanding how these developments will impact your career. To address this need, an AI community platform is being developed. More details will be shared shortly – stay tuned.

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