Home Data Science and GovernanceArtificial Intelligence This time is different: the impact of ChatGPT on the future of jobs and the advent of real time self-coding applications

This time is different: the impact of ChatGPT on the future of jobs and the advent of real time self-coding applications

by Massimo

Vision on the impact of ChatGPT on Society and Workforce. The shift from software development to real time self-coding applications and the advent of intelligent chatbots

Generative AI, especially large language models (LLMs), marks a transformative change in the way we interact with information and conduct work. Powered by advanced machine learning and natural language processing, these technologies can produce original content, distill insights from massive datasets, offer near-human translation, and even facilitate intricate decision-making. Their far-reaching capabilities present both remarkable opportunities and challenges for employment and the future of work. 

The deployment of LLMs can catalyze significant productivity enhancements and spawn novel job categories. However, it also poses the risk of making current roles obsolete, thereby widening socioeconomic gaps and instigating job uncertainty among the global labor force. The integration of AI into the workplace thus necessitates a nuanced equilibrium between leveraging benefits and mitigating potential disruptions.

Public discourse surrounding the impact of generative AI on employment tends to be divided and ambiguous. This article concentrates specifically on the capabilities of LLMs and aims to provide a structured analysis of their direct effects on distinct job roles. Such an analytical framework empowers stakeholders—from business executives and policymakers to workers and the general public—to make well-informed choices concerning skills development, workforce strategy, and key investments.

As generative AI redefines industries through innovative operational models and novel products and services, organizations can harness LLMs to boost productivity and unveil fresh opportunities, all while facilitating a seamless workforce transition. Moreover, the methodology outlined in this article for assessing the immediate job impact serves as a valuable reference for navigating future technological shifts across various sectors.

Impact of ChatGPT

The impact of ChatGPT and other similar technologies on society and the workforce is not a question of IF, but HOW.

This AI tool has learned how humans work behind a computer and is continuously learning from billions of content pages and sheets, Microsoft tools, online interactions, and new inputs that upgrade its knowledge base.

As a result, all people working behind a computer can be deeply affected by ChatGPT.

The digital disruption brought about by ChatGPT is likely to reduce the salaries of knowledge workers, and there are several examples of how this could happen.

 Here’s a breakdown of how AI is expected to impact several different professions:

  • Developers: According to experts, AI tools will enable developers to create products with 80% less time and more accuracy. This will result in the displacement of millions of developers and a reduction in their average salaries.
  • Dieticians and other knowledge-based workers: It’s not difficult to build an AI-powered dietician that can accurately support our diet with just a few prompts. This will reduce the number of clients for dieticians and other similar professions.
  • Marketers and digital marketers: AI tools like ChatGPT can replace marketers by doing their job entirely and empower them. This will lead to the lowering of average salaries for marketers and will force millions to seek more lucrative fields.
  • Journalists: AI tools like ChatGPT can write high-quality articles quickly, which will replace many journalists. The new journalist will be someone who gathers facts on the field, and their salaries will be higher, but they will spend less time in front of a computer. This will also lead to the decline of printed journals, as AI can create new editions in seconds.
  • Graphic designers and photographers: Midjourney and other AI tools can easily replace these workers in media-related fields, and the average salary will collapse as there is no need to fine-tune photos or create designs manually.
  • Content creators: While AI can generate great texts in seconds, content creators like copywriters, editors, and screenwriters will initially benefit, but will eventually lose their jobs as AI tools continue to advance.
  • Analytical scientists: While labs will benefit significantly from AI, automation will axe profiles that make routines that can be automated. Data governance will play a pivotal role in the future.
  • Lawyers: When blockchain came out, the technology promised to revolutionize banks and real estate. In particular, real estate attorneys, also known as property lawyers, were expected to have a counterpart in the blockchain in terms of function and role. This shift did not occur, as humans were hesitant to fully trust technology.  No laws were enacted to replace lawyers with blockchain technology. Similarly, there is a possibility that ChatGPT could fully replace lawyers in interpreting cases based on laws and policies. However, it will be challenging to convince people to replace human lawyers with a chat robot.
  • Entrepreneurs, startups, little Companies: they will extremely benefit from ChatGPT. Many employees will be replaced by this tool. In order to start a new company, the entrepreneur will focus on automate many tasks behind the management, focusing on the real business. Microsoft is indeed investing huge resources in his tool Microsoft Automate linked with ChatGPT. How new companies will look like? The entrepreneur, high qualified focused business manager/s, a prompt engineer, ChatGPT, automation tools. No secretary, no digital expert, no web agency, low qualified developers, low qualified sale and marketing profiles. 

As AI continues to progress, it will lead to a concentration of the market around companies that integrate AI into their operations. Salaries for highly specialized jobs will generally collapse, while jobs that require on-field skills will be in higher demand. 

Workers must adapt to these changes to survive in the job market of the future.

It is clear that the increasing use of artificial intelligence (AI) is changing the way we work and interact with technology. 

In recent interviews and articles, three key factors were identified by AI evangelists as being significant in understanding the impact of AI on the future of work: automation, prediction, and personalization

Over the next five years, AI will understand the way people work and provide insights into work preferences. It will enable individuals to anticipate trends and release them from performing repetitive and mundane tasks, allowing them to focus on more creative endeavours.

The positive aspects of AI include its ability to free employees from mundane and repetitive work. Tools such as ChatGPT offer a more natural and engaging experience than traditional search engines. However, there are concerns about the visibility and transparency of AI systems, with the majority of AI remaining opaque and difficult to understand. Additionally, AI is content with providing the correct answer, regardless of whether it is completely inaccurate or not, highlighting the need for continued human oversight. There is a growing concern that the increased use of AI in education will leave students less competent when entering the workforce. However, it is believed that AI will become a tool for students to use, in the same way that previous generations have used search engines like Google. Thus, acquiring these skills during education is not necessarily detrimental.

The future of work will be different as a result of AI, but it is not entirely clear how. Like any technological revolution, it will change the way we work and the types of jobs available. For instance, the service industry is already being divided into different roles. Some companies are using the same staff to provide service to customers and meet the needs of employees.

There are still limitations to AI, such as its inability to create from scratch, its poor performance in activities requiring common sense, and its struggle to adapt to new situations. Furthermore, AI is still unable to effectively combat misinformation, as it may not be able to recognize sarcasm or detect subtle nuances that humans can.

Opportunities and threats


  • Economic Growth: Generative AI could add $2.6 trillion to $4.4 trillion annually to the global economy, comparable to the entire GDP of the UK in 2021.
  • Business Function Transformation: Generative AI could significantly impact most business functions, particularly in customer operations, marketing and sales, software engineering, and R&D, accounting for approximately 75% of the total annual value from generative AI use cases.
  • Augmentation of Work: Generative AI is expected to augment human capabilities in the workplace, affecting a variety of activities and occupations differently than past technologies.
  • Acceleration in Automation Potential: Advances in generative AI are expected to match and even surpass median human performance earlier than previously estimated, particularly in natural-language understanding.
  • Impact on Higher-Wage Occupations: Generative AI is most likely to transform the work of higher-wage knowledge workers due to advances in the technical automation potential of their activities.
  • Skill-Biased Impact: Generative AI focuses on a more granular set of skills that are more likely to be replaced rather than complemented by machines, affecting more-educated workers the most.
  • Global Adoption Scenarios: While technology adoption at scale takes time, generative AI is expected to spread across the global economy, influenced by decisions on investments, deployment, and regulation.
  • Challenging Traditional Credentials: Generative AI could advocate for a more skills-based approach to workforce development, challenging the value of multiyear degree credentials.


  • Job Loss for Women: The International Labour Organization (ILO) and McKinsey Global Institute predict that 80% of women may lose their jobs due to automation.
  • Skills Disruption: 44% of workers’ skills are expected to be disrupted in the next five years, with generative AI representing a skill-biased technological change.
  • Office Work Automation: 87% of office work is expected to be automated, and generative AI has the potential to automate 60 to 70% of employees’ time.
  • Knowledge Work Impact: Generative AI is expected to significantly affect knowledge workers, particularly in decision-making and collaboration activities, which previously had low automation potential.
  • Economic Feasibility: Even if a technological solution for automation is developed, it may not be economically viable if its costs exceed those of human labor.
  • Reliability and Failure: The reliability of AI projects remains a concern, affecting the pace of solution development and adoption.
  • Long-Term Impact: The potential of lab capabilities does not guarantee immediate integration into work activities; developing such solutions is time-consuming.
  • Cost Considerations: The cost of integrating generative AI technologies is compared with that of human labor across different occupations and countries, affecting its adoption rate.
  • Time for Technology Diffusion: The time it has historically taken for technologies to diffuse across the economy could slow down the adoption of generative AI.
  • Range of Outcomes: The scenarios analyzed, from several sources of research on generative AI, encompass a wide range of outcomes, reflecting the uncertainty and variability in the rate of adoption of generative AI.

The advent of real-time self-coding applications

The world of coding and software development is evolving rapidly, and new tools are emerging that promise to revolutionize the way we create software applications. 

In the past, coding required a lot of planning and project management, and developers had to follow approaches like Agile or Waterfall to build robust applications. However, with the introduction of tools like ChatGPT, Github Colab, Ghostwrite Replit, etc. the industry is moving towards applications that can self deploy in real time. Let’s explore together what it means.

Traditionally, applications were built as interconnected composite services, where a single software includes several contextual services. Try to imagine a software for accounting: it often includes components like management of costs, accounting modules, user management, etc. 

With the advent of AI, the paradigm to plan and implement software is shifting, and we are moving towards personalized applications that are developed on demand, in real time, by the software itself.  In the future, we may see a world where smartphones, like iPhone, no longer are mostly app-based, but provide applications invented in real-time by the OS, with user interfaces coded when needed, based on the context where the user is and the operation the user intends to do.

Imagine a scenario where you need to book a flight. With the help of Siri, iOS will create a new application optimized for that specific user, with interfaces and code written and executed at that time. If the user wants to rent a car after purchasing the flight, a new interface will be coded in real-time to facilitate this task. This is possible because AI tools can generate code in real-time, and the advances in deploying code will soon enable applications to generate the code they need and execute it on their own.

Currently, ChatGPT can generate a JavaScript game and execute it in an HTML page in few seconds, showing that auto-coding is already possible to some extent. In the future, we may see IT systems shifting towards this technology, where software is deployed in real-time only when needed. This would move the market from app-based to experience-based business. Indeed, that behaviour is similar to the personalized advertisement in digital marketing today, where the advertisement ban of a website is customized, in real-time, based on the user’s browsing behaviour.

The biggest problem of ChatGPT is the computing power required to let it run: it would not run in smartphones or desktop computers, but it will do it soon. There are similar tools aka “LLM Chatbots” that can run in desktop computer easily (LLAMA from Meta or Vicuna 13B (an open source Chatbot with ~90% ChatGPT quality). One day these models will be trained in huge cloud computing environment, but run in small devices.

Probably a new market will be created soon with LLM Chatbots specialized in specific field like accounting or law or chemistry science.

How to face the disruption of ChatGPT

The revolutionary artificial intelligence language model ChatGPT is predicted to disrupt every major industry and replace more than 300 million jobs. Unfortunately, a lot of people will fail to adapt. 

In the age of AI, it is crucial to save your career and keep up with emerging technology.
Here are some tips on how to do it:

First, understand how AI works. 

Take a basic AI or machine learning course, read the best AI books, and listen to the top AI podcasts.
Here’s a list of top free Al courses:
– CS50’s Introduction to Al with Python (Harvard)
– Data Science: Machine Learning (Harvard)
– Artificial Intelligence (MIT)
– Machine Learning (MIT)
– Machine Vision (MIT)
– Advanced Natural Language Processing (MIT)
– Advanced Natural Language Processing from MIT.

Forbes has also compiled a list of top AI books including
– Al 2041: 10 Visions for Our Future
– A World Without Work
– The Alignment Problem
– 2084: Al and the Future of Humanity
– A Brief History of Artificial Intelligence
– Artificial Unintelligence

Additionally, check out the top 10 AI podcasts, such as
– The TWIML Al Podcast
– Data Skeptic The Al Podcast
– Eye on Al
– Practical Al
– Adventures in Machine Learning
– Learning Machines 101
– Voices in Al
– DeepMind: The Podcast
– Lex Fridman Podcast

Second, use the new product as soon as possible. 

Read research papers, get familiar with the product, start experimenting, and learn how to prompt. The best way to learn how to use ChatGPT is by practising and interacting with it regularly. Follow these steps to make the most of your experience:
1. Familiarize yourself with the basics.
2. Access ChatGPT.
3. Start with simple queries.
4. Experiment with various topics.
5. Refine your prompts.
6. Learn from the community.

Third, study the potential impact on your job and career.

OpenAI’s researchers found that the influence of ChatGPT technology spans all wage levels, with higher-income jobs potentially facing greater exposure. The most affected professions include interpreters and translators, poets, lyricists, and creative writers, PR specialists, writers, authors, and journalists, mathematicians, tax preparers, blockchain engineers, accountants and auditors.

Fourth, incorporate the new tech in your day-to-day work.

Writing a really great prompt for a chatbot persona is an amazingly high-leverage skill and an early example of programming in a little bit of natural language.
Aim to be a master AI prompter for your specific industry or role, and find ways to apply the technology in your space.
Check out the top ChatGPT prompt guide and The Art of ChatGPT Prompting for more information. 

Lastly, get involved in AI and emerging tech communities.

Meet new people, connect with thought leaders, and start writing and sharing about what you’re learning.

This will help you learn more about the AI threats and opportunities, discover job opportunities, and find mentors or collaborators.

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