By Stavros Angelidis
Artificial intelligence (AI) has become an integral part of our daily lives, bringing significant changes to the way we work, as well as a remarkable increase in productivity and efficiency when used properly.
However, it has also raised concerns whether certain jobs will remain relevant in the coming years or whether we will face serious challenges in the workforce.
Every major technological shift brings challenges, as well as new opportunities.
To better understand the transition to AI, let’s look at the introduction of computers in the 1980s and 1990s.
Computers into the workplace had a significant impact on employment, increasing demand for skilled workers and widening wage disparities.
According to the study “Computing Inequality: Have Computers Changed the Labor Market?” by the National Bureau of Economic Research (NBER), the adoption of computing technology accounted for 30-50% of the increase in demand for skilled workers between 1970 and 1995, as many businesses invested in technology to enhance productivity (Autor, Katz & Krueger, 1998).
Furthermore, technological advancement led to increased wage disparities between workers with higher education and those with lower skill levels.
Notably, the high-tech services sector experienced significant growth, with jobs in management, public relations, IT and data processing increasing by 46% between 1988-1996, according to the study “High-technology employment: a broader view” by the U.S. Bureau of Labor Statistics (Hecker, 1999).
The introduction of computers also led to an increase in the average duration of unemployment, as many workers needed time to adapt to the new technological requirements.
Early studies on AI
Initial research highlights that integrating AI into the workplace has a significant impact on productivity and efficiency. According to McKinsey & Company, generative AI could contribute between $2.6 trln and $4.4 trln annually to the global economy, affecting various industries and underscoring its substantial economic potential.
In the IT sector, EY India suggested that adopting generative AI could increase productivity by up to 45% over the next five years, particularly in software development, business process outsourcing and IT consulting.
Moreover, research focused on customer service environments found that AI tools could lead to a 14% increase in issues resolved per hour, with less experienced employees benefiting the most.
However, AI adoption does not necessarily lead to a reduction in workload. According to Upwork, 77% of employees reported an increase in workload after adopting AI, mainly due to the additional time required to review AI-generated content and learn new tools.
Transitioning to the new era
As a professional consultant in efficiency and process optimisation, I have invested significant time in studying and using artificial intelligence. Through extensive practical applications and collaborations with my team, I have arrived at several key conclusions, the most important of which is the undeniable value of knowledge and the critical role of theoretical expertise in any field.
For AI to be used effectively, the user must be able to guide the AI model (ChatGPT, Claude, Gemini, etc.) with precision and detail through the “thinking” process it should follow.
Specifically, without adequate knowledge of any AI model, the results will be limited, approximately 2-4 out of 10 in effectiveness. Conversely, with deep knowledge of the subject, you can achieve results at a level of 8-10 out of 10.
Moreover, without sufficient expertise, you will not be able to evaluate whether you have reached the best possible results, while also spending significantly more time compared to an industry expert.
This raises the critical question: when does artificial intelligence truly enhance productivity and efficiency in an organisation, and when does it potentially have the opposite effect?
Unfortunately, those who believe they have discovered a tool that eliminates the need for expertise or specialists in critical operational matters are likely to experience outcomes contrary to their expectations. This will place them at a competitive disadvantage compared to businesses that systematically invest in knowledge.
Learning, and especially theoretical expertise as the foundation of subject mastery, is becoming even more important in this new era. This stands in contrast to those who argue that knowledge is losing its value. They may be confusing the ability to access information quickly via AI with genuine expertise and specialisation, which will only become more critical over time.
Conclusions for Businesses
When discussing AI integration into the workplace, it is essential to clarify that we are not simply referring to content generation with ChatGPT. We are talking about meaningful integration into the organisation’s operations and processes. For this reason, businesses must approach AI adoption strategically to gain real competitive advantages.
First and foremost, businesses must deeply understand their processes. Many employers manage their businesses daily without having an in-depth knowledge of their workflows or ways to optimise them. Transitioning to AI requires first identifying problems in the existing structure and understanding precisely where AI can provide substantial benefits.
Second, at an organisational level, companies must map out the knowledge base of their employees and their areas of expertise, both generally and specifically in relation to the business’s key operations. Additionally, they must analyse knowledge gaps that may impact their services or products.
Equally important is including employees in this transition and supporting them in upgrading their skills so they remain valuable and capable while feeling part of the change rather than an obstacle to the organisation’s evolution.
Ultimately, the most critical factor is managing this transition methodically and thoughtfully so that it benefits both businesses and employees. The goal is to harness new technology to strengthen competitiveness without creating problems that counteract the true purpose of technological advancement.
This article is the result of personal research and experience, based on my professional expertise. Artificial intelligence was used solely as a supplementary tool for research and for improving the clarity of the text while ensuring the integrity of the content and opinions expressed.
