In this article, I will delve into whether artificial intelligence (AI), particularly the emergence of tools like generative AI (GenAI), will replace classical software outsourcing as we know it.
This discussion aims to provide insight into the potential implications, challenges, and opportunities that lie ahead for the IT outsourcing industry, traditionally being chosen by businesses as a cost-effective alternative to closing tech gaps locally. Also, I’ll touch on the importance of adapting to AI technology and the need for specialists who can use it effectively.
Where AI is going and how to live with it
First of all, many of us are worried about what if AI becomes too smart making its own decisions, starts to consider itself a human being, and stops being impartial. Being in the kitchen of software development for a quarter of a century, I have to say that the issue of ethics in usage is controlled directly by the developers of this AI with the help of algorithms. If AI is limited, it will not do any harm. I think AI should be approved by people or controlled at the algorithm level anyway. In addition, there is always a development bar for AI. To jump over it, new ideas and improvements need to be developed.
However, popular solutions have certain drawbacks. For example, in the field of data security and copyright. Currently, there is no state regulation of AI. I hear from our customers that businesses are still not ready to use them to their fullest potential immediately and will take a wait-and-see attitude until the market is regulated.
An Italian data breach case of leakage of the ChatGPT users’ personal data vividly illustrates a lack of legal framework that would justify the mass collection and storage of personal data for the purpose of “training” the algorithms underlying the chatbot.
To ensure the safe use of AI, not only should laws be implemented, but also supervisory and controlling bodies to form morality when interacting with the new norm that AI is becoming should be established globally and locally. That is another reason traditional partnerships with an outsourcing vendor are still in demand.
Demand for new abilities
Speaking of generative AI, humans are expected not only to perform work but also to be able to set tasks. In other words, when interacting with AI, each of us becomes a customer expecting work to be performed. But simultaneously, we must understand what we want as clearly as possible. Not all people have these skills.
Stepping into the path of interacting with GenAI demands from users the ability to set tasks. Critical thinking is also important. In this case, there is a need to be able to set tasks correctly to get the expected deliverables. This is the quality of the next order, and in new conditions, it should be like the soft skill of a software developer. At the same time, the ability to set tasks for the AI as a subordinate does not mean that the result will meet expectations because it needs to be checked by a specialist.
Let’s be honest, even now few people know how to use ChatGPT to its full potential.
The growth of AI will contribute to creating new jobs instead of taking work away from outsourcing vendors. It means an increase in vacancies for AI specialists in various industries. Therefore, there will be a need for specialists who can use AI rather than create it. For example, a new profession has already emerged today – prompt engineer – a specialist in rapidly implementing AI in an organisation, which is quite relevant.
Programmers or bots: Who is better?
As AI becomes more widespread, the question is whether programmers write code themselves or have chatbots write it.
Customers usually expect quality. If AI can help deliver this quality faster, why not? Look, everyone knows that there is a programming language called Java. There are Apache Commons libraries. You can Google it, but can you do something with it? Can you bring value to the business? This is the point. Large language models (LLMs) are a tool, just like a library or a framework. However, it has other capabilities that need to be mastered and used to bring value.
It will be a long time before AI can replace developers because there will always be something that needs to be fixed. Either it’s an error in the code or something wrong with the configuration. For example, if a bot has already written code that seems to work, but an error appears. The developer can spend little time writing the code but later spends more time looking for the error.
Let’s take GitHub Copilot. Programmers note that the acceptance rate of suggestions from Copilot is up to 40%. Almost half of programmers agree with AI. But the point is that all code suggestions should be tested thoroughly because the responsibility is on the programmer and, as a result, on the vendor.
We are still very far from where the code is written entirely by AI and is high quality. At this stage, full outsourcing of AI code writing can turn into the cultivation of low-quality code and software solutions.
That’s why AI chatbots like ChatGPT can enhance programmers’ abilities and transform how they work. Such tools allow specialists to increase their productivity and creativity, making them more competitive in the labour market and the companies they work for.
Navigating collaboration with GenAI
The code generated by a chatbot will be from a database of codes that programmers have written. That is, using chatbots and code means using humanity’s previous experience. A good example is theorems or research results. Of course, you can look at a human cell from scratch, create and improve a microscope, or use the acquired knowledge of a particular field and build on it. This is what evolution is all about.
Theoretically, you can outsource lots to artificial intelligence. But think about it: what remains under your control? Will you be 100% sure that artificial intelligence is helping you instead of outsourcing your business to someone else? The situation is different with a software provider, who is contractually obligated to fulfil its duties to you. AI cannot do this at the moment. Until AI becomes regulated, it is playing with fire.
Lastly, AI tends to cooperate with programmers, extend their capabilities, allow them to work more productively, decrease the number of manual operations, and help focus on creative, exciting tasks and thinking. There will always be work for outsourcing programmers, and the only thing left to do is to keep on being inventive, to be on the lookout for and meet the market’s needs.
In summary, I’d like to emphasise the necessity of adapting to AI while considering the implications of IT outsourcing as a business. AI is not a threat to traditional software outsourcing but rather a transformative force that can augment and enhance the capabilities of outsourcing vendors. AI is still evolving, and its full potential is yet to be realised. While AI tools can automate certain aspects of software development, the human element remains critical in areas that require creativity, problem-solving, and critical thinking.
Maxim Ivanov is CEO and co-founder of Ukrainian IT services supplier Aimprosoft.