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Redesigning Work & Cultivating Human Potential by Integrating the Goodness of AI

Updated: 6 days ago


In today's complex, interdependent, and ever-evolving world, the profound impact of artificial intelligence (AI) on job structures has become a focal point of discussion. This article aims to provide insights into the dynamics of this unprecedented change and some of its implications on the job market. Over the past few decades, the accumulation of science-based knowledge and advanced tools has raised our awareness and accelerated human development alongside impressive technology systems and tools. But also, the intensive use of modern technology has raised some ethical and health-related concerns.


The primary goal of this article is to examine the specific influence of artificial intelligence on job structures and its role in organisational challenges and results. By doing so, we hope to share some insights toward a more sustainable and humane future, emphasising the pivotal role of technology in serving humanity's well-being and shaping the quality of our collective evolution.

The impact of Artificial Intelligence (AI) on job structures

Technological advances have been a consistent part of human history. While we've grown used to these changes, our natural survival instincts often kick in when we perceive threats. Fear, a powerful emotion, acts as a signal, preparing us to confront challenges. Fear is not an enemy but rather a survival mechanism that has propelled human evolution. However, in modern life, we face both tangible threats (like physical danger) and perceived threats (such as potential job loss). Uncontrolled fear can lead to resistance against change, negatively impacting our health, progress, and development (Purves, et al., 2001). It can also blind us to opportunities and magnify collective fears. When dealing with perceived threats, one effective strategy is to confront them by seeking information that can help us better understand the situation. 


In the present day, technology has become an integral part of our lives, with many people unable to imagine existence without the internet, Google, or social media. Over time, technology has continually brought systemic changes, altering how we work, communicate, and learn. Each wave of technological innovation has displaced certain jobs while simultaneously creating new ones. Let’s recall some historical examples:

  • The introduction of assembly line production techniques in manufacturing during the early 1900s that displaced certain skilled craft jobs but created new roles in manufacturing, increasing product availability.

  • The widespread adoption of electricity and household appliances in the 1920s and 1930s that displaced jobs in traditional trades yet led to new opportunities in manufacturing and service within the electrical and appliance industries.

  • The rise of automation and computer technology in the 1950s and 1960s that automated manual labour jobs but generated new roles in programming and hardware manufacturing.

  • The proliferation of personal computers and the software industry in the 1970s and 1980s that computerised clerical and administrative jobs while creating new positions in software development, IT support, and related fields.

  • The advent of the internet and e-commerce in the 1990s and 2000s that impacted traditional retail jobs due to online shopping, fostering growth in web development, online marketing, and e-commerce.

  • The rise of artificial intelligence (AI) and automation in various industries since the 2010s has affected jobs in manufacturing, customer service, and data analysis through automation. Simultaneously, it brought significant job growth in new fields like cybersecurity, data science, AI research, telecommunication, education, content creation, and medicine, among others.

What distinguishes today's technological advances from previous generations is the rapid pace of change and the widespread integration of technology into every facet of human life. This transformation raises significant concerns, particularly in the realms of human rights. Effective regulation is essential, specifically regarding issues like data privacy, discrimination bias, malicious use, and security. This accelerated pace of change also has a more profound and well-researched impact on current generations. While previous generations didn't have easy access to the vast information available today, their brain development and overall well-being were not as significantly affected by technology's intensive use. This modern phenomenon impacts our brains, personalities, behaviours, and overall performance (Perlmutter & Perlmutter, 2020).

AI: Threat or Opportunity?

The way humans perceive the source of their fear significantly influences our relationship with it and our path forward. Technology has always had a dark side when used against humanity's best interests (e.g., the atomic bomb). This stresses the importance of ethics and responsible development when designing and using technology. Regulations must prioritise humanity's best interests, ensuring that AI routines and algorithms strike for a balance between fostering innovation and ensuring safety and ethical use. AI tools, like past technological advances, can indeed have both positive and negative impacts on a broader scale. 

These impacts are contingent on various factors, including the intentions of their designers and programmers, the nature of the data or information they generate unsupervised, and the technical capacity of AI systems and tools to explain themselves to knowledgeable users who could assess the quality of its outcomes and related impacts on the different areas of people and the society at large. In this article, our focus is on AI on the job market.

By analysing more than 2000 work activities across more than 800 occupations worldwide, MGI1 (2017) shared some insights regarding this impact of AI on job structures.

  • The easier automated job tasks relate to physical activities, in highly predictable and structured environments, as well as data collection and processing, representing 50% of the activities that people do across all sectors.

  • The least susceptible job categories for automation include managing others, providing expertise, and interfacing with stakeholders.

  • About 5% of occupations could be fully automated by proven AI technologies, though nearly all occupations will be affected by automation.

  • About 30% of the activities in 60% of all analysed occupations could be automated, opening the possibility of people working closely with AI tools in their job context.

  • 15% of the global workforce could be displaced by automation in the period 2016–2030.

  • In a slowest pace and scope AI adoption scenario, the estimated impact on changing jobs was 0% whereas in the fastest one, the estimates went up to 30% of work (not jobs) that could be potentially displaced by automation.

  • 14% of the global workforce could need to change their occupational category.


As cited by Schleiger, et al, (2023, May), organisations investing in AI-human collaboration are expected to boost revenues by 38% within five years. Moreover, executives are seeing AI tools adoption as a way to further value creation and productivity growth, a key driver of economic growth (MG2, 2023). 

In this way, they expect to offset the influence of global demographic trends (ageing and declining birth rates) and the market’s skill gaps on their organisational performance. This organisational expectation is driving AI adoption, making it mainstream, which is a pressing need to keep their external and internal fits adjusted to be a competitive “force of good” in their industry.

These adjusted organisational fits are key for adaptability and performance because adjustments require updating their internal structures, processes and systems, as well as managing their culture. In change processes, human-centred cultures play a role in engaging leaders as well as people, giving values as a reference for behaviours. Moreover, a more human-centred culture helps organisations better deal with the normal fear that arises during change processes, since unmanaged fear can compromise the success of any change initiative running in their organisational context. And this consequently affects the success implementation rates. 

For instance, as reported by WT (2022, October 31), about 66% of change initiatives fail, and only 34% succeed. Organisational change is common nowadays since 96% of firms are undergoing some transformation right now, and within the past 24 months, half have finished at least one transformation journey. That is why, it is required now more than ever the build supportive work contexts as a competitive advantage to achieve expected performance levels towards a more regenerative way while respecting people’s rights and wellbeing and also assisting their development.

This AI-driven transformation represents a collective challenge, and how we perceive AI, as a threat or as an opportunity, largely depends on how we consciously design and use them. For this to happen, conscious systems design should consider the initial definition of sustainability.

As cited by Ceschin & Gaziulusoy (2016, November), sustainability is …” development that meets the needs of the present without compromising the ability of future generations to meet their own needs. This should be at the heart of the organisational internal fit since, in line with the pioneering work of figures such as Buckminster Fuller and Victor Papanek in the 1960s, the concept of sustainability is a system property and not the property of individual elements of the system.

Hence, the crucial point here is that to manage sustainability, as a socio-technical construct, organisations should create an internal space to facilitate "design for sustainability", as organisational value and design criteria in their research, development and production processes. This should consider the environmental, social, and economic aspects of the design solutions, including AI tools and systems. Thus, this orientation would emphasise the need for holistic solutions that encompass people, technology, processes, and their interdependencies not only with the socio-technical aspects of organisations and societies but also with a vision for a better future for humanity and the planet: more sustainable, ethical and humane (Ceschin & Gaziulusoy, 2016, November).

To better understand this need for designing holistic solutions, in previous research on internal fit for e-learning, it was proposed a conceptual model that interested readers can look at (and extend into this larger context) to get some ideas in analysing this internal fit and their key issues (strategic goals, process-based roles, user-system interaction and task analysis) with a more systemic perspective (see Rentroia-Bonito et al., 2008). 

Where are we in this paradigm shift?

In assessing our collective position in the ongoing paradigm shift towards AI adoption, it's essential to understand the current technological stability and the changing skill requirements. Regarding the former, according to a recent survey by McKinsey (MG2, 2023), the percentage of organisations implementing AI tools has shown relative stability since 2022, also suggesting that the initial phase of AI adoption is largely concentrated within specific business functions.

Regarding the changing skill requirements, the dynamics of the job market are also indicative of this position. A recent LinkedIn post (Bessalel, 2023, September 11) highlights an upcoming significant shift in the required skill sets, which have already changed by 25% since 2015 and are projected to increase to 65% by 2030.

These observations collectively point towards a transitional phase in the adoption of AI. On one front, organisations could be developing internal supporting processes and IT guidelines to shape the development of their data-driven and AI-based systems and tools in order to harness the full potential of AI on bottom-line results, better grasp the reasoning behind its generative capabilities, and ensure ethical and responsible development. 

This may be managed by internal high-level knowledgeable human teams with a mission to monitor AI practices, ESG compliance, and also commitment to respect human rights within their supply chains, in alignment with current guidelines and recommendations coming from the international entities working on the legal regulation of this multidisciplinary space, such as the European  AI Act, Ethics Guidelines for Trustworthy AI, Data Protection Regulations, Corporate Sustainability Reporting Directive, Action Plan on Sustainable Finance, Due Diligence legislation, among others, including regulations developed or being developed at national levels. 

On the other front, people are faced with the need to understand the specific impacts on their job tasks, engage in continuously learning to adjust their skills sets and adapt to these new job demands. Furthermore, it is also important for people explore new career opportunities, while managing their current workloads, physical, mental and emotional states within this rapidly evolving job market.

Closing Thoughts

AI adoption is rapidly becoming the norm, and as we've seen throughout history, it is having an impact on job structures, their contents, and the related skill sets across business functions and industries. Continuous learning supported by more human-centred cultures is an essential toward achieving greater resilience and stability, both at the individual and organisational levels.  Ultimately, this joint effort will lead to a new equilibrium at the systemic level.

In shaping a more sustainable and human future, there are AI-related challenges ahead, since it presents immense potential, delivers specific results in terms of productivity gains, and introduces risks while also posing unresolved ethical dilemmas. At this moment, understanding these facets is key for effective adaptation and thriving. 


To conclude, many years ago, during a challenging time in our lives, my grandmother illuminated our path with these timeless words of wisdom: "Both happiness and hardships are short-lived. Keep an open mind, persist in your search for knowledge, focus on your tasks, and hold on to faith and hope for a brighter future”.

Some questions to reflect on are:

  • Do you intend to adopt AI into your business operations in the upcoming months?

  • If your organisation already adopted AI into their operations, what is your take on that: Productivity gains? Jobs changed? Usage of AI tools as people’ assistant that translate into more creativity, productivity and business outcomes?

  • If you would like to share your experiences and insights, they are welcome in the comments below!


Ceschin, F., & Gaziulusoy, I. (2016, November). Evolution of design for sustainability: From product design to design for system innovations and transitions. Design Studies, 47, 118-126.


McKinsey Global Institute, (MGI2). (2023), The state of AI in 2023: Generative Ai’s breakout year.

Purves, D., Augustine, G. J., Fitzpatrick, D., Hall, W. C., LaMantia, A. S., McNamara, J. O., & White, L. E. (2001). Neuroscience (2nd edition). Sinauer Associates.


Rentroia-Bonito, M. A., Jorge, J., & Ghaoui, C. (2008). Motivation to E-Learn Within Organizational Settings. International Journal of Distance Education Technologies, 4(3), 24-35.

Schleiger, E. C. Manson, C. Naughtin, A. Reeson & C. Paris (2023, May). Collaborative Intelligence: A scoping review of current applications. 


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