ChatGPT impact on cybersecurity field

Disclaimer

This post was mostly a test, to learn to write using ChatGPT. The post was written entirely by ChatGPT, although I prompted it strongly, for example to use the formula for productivity and the changes in productivity.

Introduction

The world of cybersecurity is constantly changing, and Artificial Intelligence (AI) is shaking things up even more. It's helping organizations tackle threats more effectively, and as a result, it's crucial to understand how AI might change the cybersecurity workforce landscape. Most people talk about factors like task complexity, social and emotional intelligence, and the balance between routine and non-routine tasks in different job roles when they try to estimate the likelihood of productivity improvements from technology. While these aspects are important in predicting the potential for technology to have an impact, they might not provide a complete understanding of the actual impact once the technology already exists.

In this blog post, we're going to take a different approach to analyze AI's impact on the cybersecurity workforce. Instead of looking at the usual factors, we'll dive into the fundamental relationship between productivity, workforce size, and demand. By focusing on this simple formula, we can get a better idea of how AI-driven productivity improvements could shape the future of the cybersecurity workforce.

The Formula:

Productivity x Workforce = Demand

This straightforward equation highlights the core relationship between productivity (output per worker), the size of the workforce, and the overall demand for a particular job or industry. By exploring how AI-driven productivity improvements and changing demand influence this relationship, we can gain valuable insights into the potential effects of AI on the cybersecurity workforce.

Of course, using this formula the evolution of workforce can be estimated by the evolution of demand and the evolution of productivity.

Impact on Productivity of a General Technology: ChatGPT

ChatGPT stands out from other technologies due to its ability to enhance the productivity of all knowledge workers, including cybersecurity professionals. This versatile AI-driven language model can assist with various tasks, such as research, drafting documents, providing suggestions, and even automating certain processes.

Estimating Productivity Improvement with ChatGPT

To estimate the productivity improvement brought by ChatGPT, we'll consider its current capabilities without additional plugins or enhancements. Based on personal experience and observations, using ChatGPT and other LLM (Large Language Model) based technologies can lead to productivity improvements ranging from 30% to 100%. For our analysis, we will take a conservative estimation of 65%.

Estimating Demand

Estimating the demand for cybersecurity is a challenging task. On one hand, software security is becoming more mature, leading to a reduced likelihood of cyberattacks. However, as software takes on increasingly critical tasks, the potential impact of cyberattacks grows. Additionally, new threats and attack vectors are continuously emerging, which could counterbalance the maturation of software security. To simplify the estimation, we will assume that cybersecurity demand is proportional to the amount of software written.

Estimating Software Production Capacity

As software remains crucial for advancements in automation, AI tools, and other emerging technologies, the current demand for software is likely not met. According to a report by the US Labor Department, the global shortage of software engineers may reach 85.2 million by 2030. Furthermore, around 40 million technical jobs go unfulfilled due to a lack of skilled talent. This unmet demand suggests that the amount of software written is constrained by software production capacity, which depends on the size of the programmer workforce and their productivity.

Impact of ChatGPT on Software Output

With the productivity improvements brought by ChatGPT, the amount of software written is expected to increase by approximately 65%.

Estimating the Overall Impact of ChatGPT on the Cybersecurity Workforce

To estimate the total impact of ChatGPT on the cybersecurity workforce, we can use the following equation:

Cybersecurity_workforce = Demand / Productivity
= Amount_of_software_written / Productivity_of_cybersecurity

For this analysis, we have chosen to bundle the entire cybersecurity workforce together, rather than analyzing the impact on specific job roles within the field. The reason for this approach is the belief that cybersecurity professionals possess a high degree of adaptability and transferable skills, allowing them to change job roles relatively easily within the field. This flexibility is an important factor to consider when assessing the overall impact of AI-driven productivity improvements on the cybersecurity workforce.

Plugging in our values, we get:

Cybersecurity_workforce_change
= Amount_of_software_written_change / Productivity_of_cybersecurity_change
= Developer_workforce_change * Productivity_of_developer_change / Productivity_of_cybersecurity_change
= (Developer_workforce_change * 1.65) / 1.65
= Developer_workforce_change

Based on our estimations, ChatGPT should not have a significant impact on cybersecurity jobs. This conclusion assumes that the demand for cybersecurity will increase proportionally with the growth in software output, without factoring in potential changes in the threat landscape, technology adoption rates, or cybersecurity maturity. However, it is essential to consider these additional factors when evaluating the true impact of ChatGPT and other productivity-enhancing technologies on the cybersecurity workforce.

Closing Thoughts: Emphasizing Adaptability for Professionals

In conclusion, although our analysis suggests that ChatGPT technology may not significantly affect the overall number of cybersecurity jobs, it will have a profound impact on the nature of these jobs. As productivity-enhancing technologies like ChatGPT continue to evolve, they are likely to reshape the roles and responsibilities of cybersecurity professionals.

Moreover, we must remain cautious about more specialized AI applications that focus solely on improving the productivity of cybersecurity professionals. These specialized tools could potentially reduce the demand for cybersecurity jobs, as they enable fewer professionals to handle the same workload.

It is crucial for cybersecurity professionals and other workers in niche fields to develop a strong sense of adaptability in response to AI-driven productivity improvements. By continuously educating themselves, staying informed about industry trends, and embracing the changing landscape, these professionals can better position themselves for success in a rapidly evolving job market. This proactive approach can help ensure that advancements in AI and automation contribute positively to the workforce, giving skilled professionals more agency and control over their careers in the face of disruptive technological changes.

Ultimately, adaptability will be the key for professionals in the cybersecurity field, as well as other niche fields, to successfully navigate the challenges and opportunities that AI-driven productivity improvements bring.