Milit Thattamparambil Ranjith
Their feathers are pristine, sleek, and white. Yours are ruffled, discolored, and out of place. In the lab, during code reviews, or while scrolling through LinkedIn, technical jargon rolls off people’s tongues. It sounds foreign, almost alien. Should you be able to understand it? You remind yourself that you’ve earned your place here. This is your field. Yet in this ever expanding technological pond, you can’t help but feel like the ugly duckling.
Imposter syndrome affects up to 75% of professionals, with those in STEM fields particularly at risk [1]. Traditionally, research attributes these feelings to sociodemographic and psychosocial factors such as gender, ethnicity, and socioeconomic background. But what if part of the issue isn’t just psychological? What if the pond itself is changing faster than you can swim? In a decade defined by relentless innovation, self-doubt may not be a delusion but a diagnosis.
Classic Imposter Syndrome
In preschool, I used to fake colds to skip swimming class, not because I couldn’t swim, but because I dreaded thrashing awkwardly while my classmates sliced through the pool with ease. Years later, I’ve realized that same sinking feeling follows many of us into labs, offices, and lecture halls.
Figure 1: Annual scholarly publications on imposter syndrome
First identified in highly successful professional women, imposter syndrome is the persistent belief that one’s success is undeserved or achieved by chance. From seasoned male professionals to students, subsequent research has shown that self-doubt is universal. Approaches such as self-reflective metacognition and cognitive behavioral therapy have been developed to help individuals reframe their thinking, rediscover self-worth, and suppress these pervasive feelings of unbelonging [2].
However, in today’s professional landscape, knowledge is doubling every few months, and AI is automating responsibilities once considered “human-only.” Figure 1 shows a steep rise in annual publications on imposter syndrome, paralleling major advances in automation. This suggests growing recognition that imposterism may stem not only from personal insecurity but also from structural technological change. The boundary between expertise and automation is blurring so quickly that confidence alone may no longer be enough to stay afloat.
Swim or Sink: The Acceleration of Knowledge
In 2019, the Organization for Economic Co-operation and Development (OECD) predicted that automation technologies would replace 15% of existing job roles and significantly alter another 32%. The boom of AI and intelligent agents has since accelerated this transformation, with skills once considered disruption-proof (coding, writing, and research) now increasingly being catered for and enhanced by these technologies.
AI and digital automation tools are redefining not only which skills matter but also how quickly they expire. According to a Harvard Business Review report, the half-life of technical skills in tech roles is now a mere 2.5 years [3]. For organizations, this has made reskilling and upskilling essential strategies to remain competitive. This places candidates who actively update their skill sets at a clear advantage over those who must be retrained to meet evolving organizational needs.
Where traditional imposter syndrome once stemmed from perceived inadequacy, today’s engineers face the sobering reality that competence itself is perishable. As the navigable space for engineers grows from a pond into a lake of knowledge, it becomes all the more important to learn the concepts and terminology that feel unfamiliar instead of avoiding them.
AI: The Ultimate Imposter?
There’s a good chance that a future MEng student, drafting their own “Engineer’s Perspective” essay, will feed this very essay into a large language model to analyze its strengths and pitfalls. Generative AI has become both the study partner and the silent competitor of our age.
A common experience today is the duality of gratitude and guilt. Gratitude for the amplification of our capabilities thanks to our new AI companions, and guilt over the legitimacy of our own efforts. When an AI generates complex code, I often find myself typing it out manually, deluding myself into believing I fully grasp the tokenized syntax that’s just been spat out at me. Has the overuse of AI made us intellectually complacent, widening the skill disparity between those who openly rely on it and those who seemingly don’t? Perhaps the growing sense of imposterism isn’t irrational at all. It may be a rational response of a mind uncertain as to whether its thoughts are still entirely its own.
Figure 2: Capacity of generative-AI systems to substitute human skills by skill group (Indeed Analysis: World Economic Forum)
A recent MIT Media Lab study explored this question by asking 54 participants to write SAT essays using either ChatGPT, a search engine, or no assistance at all [4]. Concerningly, or perhaps expectedly, participants who used the LLM “consistently underperformed at neural, linguistic, and behavioral levels.” Diving deeper, Figure 2 reveals a stark reality: AI exhibits high capacity to substitute programming, mathematics, and writing, which form the foundation of technical work. Meanwhile, human-centric skills such as empathy and active listening remain largely irreplaceable.
AI is automating the same tasks that overreliance on it is dulling. While keeping up technically with your peers is vital, it will be what makes us uniquely human that truly separates us from the new digital imposters in our ecosystem.
The “Career Fair” Problem
As you sit applying for jobs, your phone vibrates. The first few lines read, “I am thrilled to announce…” Another LinkedIn post, another polished success story, another duck in the pond. But behind the glamour of digital self-promotion lies a quieter competition, one not of skill, but of presentation.
Impression management has become the new soft skill, a curated performance designed to appear competent enough to be chosen. Standing in line at a career fair, in a sea of suits and resumes riddled with buzzwords, it’s easy to feel outmatched. Yet a closer look at many glittering LinkedIn profiles reveals a different story: the “serial start-up founder” is often a participant in a few short-lived projects, and the “prestigious university association” may have been a weekend workshop [5]. In this hyper-competitive job market, the skills and personas we envy may be little more than carefully polished facades, reflections of the same insecurities we try so hard to conceal.
As Applicant Tracking Systems (ATS) scan AI-generated job applications, the line between authenticity and automation blurs; in their eyes, is anyone truly an imposter, or are we all versions of the same digital persona?
Adaptation and Authenticity
So yes, in this digital age, the longer you go without learning new strokes, the further you may drift behind. But it is equally important to question the waters you’re swimming in and discern between genuine mastery and surface-level confidence.
If my words fall short, take them instead from an undeniably smart man, Stephen Hawking: “Intelligence is the ability to adapt to change.” Perhaps that’s the real lesson for the modern engineer: to learn, adapt, and remain buoyant amidst technological churn.
In a world filled with artificial imposters, curated personas, and disappearing skill relevance, maybe authenticity itself is the rarest skill of all. You’re not alone in feeling out of place. The pond is changing, but so are you. And if you find yourself the ugly duckling again, remember, even if you are a beautiful swan amongst ducks, it never hurts to learn to quack, to adapt, and to keep learning.
Figure 3: An excerpt from Hans Christian Andersen’s The Ugly Duckling
References
[1] N. Salari, S. H. Hashemian, A. Hosseinian-Far, A. Fallahi, P. Heidarian, S. Rasoulpoor and M. Mohammadi, “Global prevalence of imposter syndrome in health service providers: a systematic review and meta-analysis,” BMC Psychology , vol. 13, no. 571, 2025.
[2] H. MR, S. J, M. PT and D. D, “Imposter Phenomenon,” in StatPearls [Internet], Treasure Island, FL, StatPearls Publishing, 2023.
[3] J. Tamayo, L. Doumi, S. Goel, O. Kovács-Ondrejkovic and R. Sadun, “Reskilling in the Age of AI,” Harvard Business Review, no. September-October 2023, 2023.
[4] N. Kosmyna, E. Hauptmann, Y. T. Yuan, J. Situ, X.-H. Liao, A. V. Beresnitzky, I. Braunstein and P. Maes, “our Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task,” arXiv, 2025.
[5] M. Kumar, “The Fine Line Between Self-Promotion and Misleading Claims,” LinkedIn, 2024.