Uncertainty in Global Job Market

The global Information Technology (IT) job market, long considered an engine of growth and a bastion of career stability, has recently entered a period of pronounced stagnation and uncertainty. While public anxieties often gravitate toward dramatic events like geopolitical conflicts or economic downturns, the reality is a complex interplay of forces. The current hesitation in IT hiring is not solely the product of a single event. Instead, it is a confluence of macroeconomic factors, amplified by a dramatic and disruptive internal transformation driven by artificial intelligence (AI) and a significant oversupply of skilled labor resulting from recent mass layoffs.

While the specter of broader global conflicts and ongoing regional crises contribute to a climate of general unease, their direct impact on the IT sector's hiring trends is often indirect. Geopolitical instability can disrupt supply chains, depress consumer confidence, and shift national priorities toward defense spending, but these effects are felt across all industries. A more precise explanation for the IT sector's disproportionate downturn lies in its structural changes, particularly the widespread and aggressive layoffs that have taken place since late 2022. These job cuts, often affecting tens of thousands of employees at a time, have flooded the market with highly qualified, experienced professionals, creating an intense and historically competitive environment for a shrinking number of open positions.

The primary driver of the current IT job market's stagnation is this fundamental imbalance between supply and demand. As companies—many of which overhired during the pandemic boom—began to aggressively cut costs, they released a massive pool of talent back into the job market. This has created a bottleneck where hundreds, and sometimes thousands, of applicants vie for a single opening. This oversupply is further compounded by the industry's rapid technological evolution, particularly the rapid integration of generative AI. Companies are not replacing humans with AI en masse; rather, they are using AI to streamline and automate tasks traditionally performed by entry-level employees. As a result, firms are increasingly prioritizing senior talent who can manage and leverage these new tools, while opportunities for recent graduates have significantly diminished. According to a recent report, entry-level programming roles have seen a substantial decline in advertisements, creating a bottleneck for a new generation of talent.

This shift presents a paradox. While AI literacy is becoming a critical skill, companies are simultaneously de-emphasizing the need for a large pipeline of junior talent and consolidating roles due to layoffs. The market is not experiencing a broad-based decline, but a fundamental restructuring. Roles in specialized fields like AI governance, cybersecurity, and data science are experiencing a surge in demand, while more general or repetitive roles in software development and administrative support are being automated or consolidated. The stagnation is thus not a sign of the industry's weakness, but rather a symptom of its metamorphosis. The global IT job market is not simply stagnant; it is in a state of flux, shedding its old skin to emerge as something leaner, more specialized, and profoundly different, leaving many professionals to navigate this uncertain transition.

The False Narrative of Skills Shortage in AI

In the dynamic and highly-publicized world of artificial intelligence, a striking paradox has emerged: while industries persistently lament a severe AI skills shortage, countless qualified professionals find their applications rejected without explanation. This dissonance suggests that the proclaimed talent deficit is not a genuine scarcity of expertise, but rather a manufactured narrative rooted in flawed recruitment practices, often driven by a desire to suppress salaries and, more disturbingly, perpetuate systemic biases. The supposed skills gap is a misrepresentation of the talent landscape, a product of discriminatory hiring algorithms and an outdated focus on credentials over competence.

At the heart of this issue is the widespread adoption of AI-powered Applicant Tracking Systems (ATS). While these tools are promoted as a solution for efficiency, a recent Harvard study revealed that many companies have a staggering 60-80% rejection error rate, filtering out perfectly viable candidates for superficial reasons like non-standard resume formatting or the absence of specific keywords. This algorithmic over-reliance often fails to recognize non-traditional career paths, self-taught skills, or valuable experience gained outside of a formal, linear progression. The consequence is a self-inflicted wound for companies: they claim a talent shortage while their own systems systematically exclude a significant portion of the talent pool.

This problem is compounded by a deep-seated bias embedded within the very training data of these AI systems. Historical hiring data, which often reflects past discrimination, is used to teach these algorithms what a successful candidate looks like. As a result, the systems replicate and amplify existing prejudices. Research has shown that some AI hiring tools consistently disadvantage applicants from marginalized communities, regardless of their qualifications. This leads to a troubling cycle: a company seeking a diverse workforce implements an AI tool to remove human bias, only for the tool to entrench and scale racial and gender discrimination at a pace that manual recruitment never could. The claim of a meritocratic, data-driven process becomes a shield for maintaining the status quo, pushing talented individuals to the margins.

Finally, the narrative of a skills shortage serves a convenient purpose: it justifies paying lower salaries and undercutting talent. By creating a perception of a fierce competition for a small pool of elite experts, companies can rationalize offering less competitive compensation. Simultaneously, this enables them to reject candidates who ask for fair market value, creating a buyer's market for labor. The focus on a shortage deflects from the real issue—that many companies are not looking for the most qualified or skilled individual, but rather the most compliant and cost-effective one. In this way, the AI skills gap narrative is not a reflection of reality, but a strategic tool used to manage labor costs and obscure discriminatory practices. The solution lies not in finding more talent, but in reforming the broken and biased systems that prevent companies from seeing the talent they already have.

Futility of Memorization Tests in Interviews

The modern technical interview has, in many circles, devolved into a test of rote memorization rather than a true assessment of a candidate's skills. It is a frustratingly common scenario: an interview that feels less like a conversation about problem-solving and more like a pop quiz on a recently compiled crib sheet of trendy buzzwords. The interviewer, perhaps fresh from a conference or an extensive documentation binge, asks questions that demand recall of highly specific, context-dependent details—the precise parameter count of a large language model, the exact dimensions of an embedding vector, or a laundry list of command-line flags. This approach, while seemingly designed to screen for expertise, is in reality an exercise in futility, failing to distinguish between genuine proficiency and a well-rehearsed, short-term memory.

This method of questioning rests on a fundamental misunderstanding of what constitutes a valuable professional skill. A truly skilled engineer or developer is not a human encyclopedia; they are a problem-solver. On the job, the key to success lies not in having every minute detail committed to memory, but in knowing how to find that information when it's needed, understand its context, and apply it effectively. The real-world workplace is collaborative and open-book. When a developer needs to know the correct syntax for a new API call or the recommended context size for a specific model, they will reach for documentation, use a search engine, or consult a colleague. The critical skills are the ability to formulate the right question, interpret the documentation, and integrate the new information into an existing solution. An interview that ignores this reality is a poor predictor of on-the-job performance.

Moreover, this style of interview can actively discourage innovative and critical thinking. When candidates are conditioned to expect a trivia contest, they spend their preparation time cramming facts rather than honing their problem-solving abilities or building practical projects. This approach promotes a shallow, surface-level understanding of complex topics. A candidate might be able to recite a model's specifications without understanding the architectural trade-offs that led to those design choices, or they might know a specific library's function names without appreciating the underlying data structures. Interviews should be a window into a candidate’s thought process—how they tackle an unfamiliar problem, the assumptions they make, and how they reason through a solution. Asking for specific, googleable facts closes this window, offering a sterile and uninformative glimpse into a candidate's capabilities.

Ultimately, interviews should be a simulation of the work itself. They should challenge candidates with problems, not with quizzes. By focusing on practical application, design challenges, and thought-provoking discussions, interviewers can better assess a candidate's ability to learn, adapt, and innovate. An interview should reveal whether a candidate can think critically, not just whether they can remember. A hiring process that prioritizes rote memorization over practical intelligence is a disservice to both the candidate and the company, as it risks filtering out excellent problem-solvers in favor of skilled test-takers. To find truly impactful hires, we must move beyond the trivial pursuit of memorized facts and embrace interviews that celebrate genuine, applicable expertise.

Top AI Salaries Dwarf The Manhattan Project

Top AI Salaries Dwarf The Manhattan Project

Hiring Unbiased Recruiters

The cornerstone of a robust and equitable hiring process is the recruiter. Their judgment shapes a company's workforce, and any unconscious biases they hold can systematically exclude qualified candidates. To cultivate a truly diverse and high-performing team, it is essential to rigorously test recruiters for bias during their own hiring process. A multi-stage methodology that combines blind skills assessments with targeted bias exposure and a deep dive into their reasoning can provide an invaluable measure of a candidate's commitment to fairness and merit.

The first stage of this assessment is a blind review of anonymized CVs. The candidate is given a diverse set of resumes, with all personal identifiers such as names, addresses, and nationalities redacted. This curated pool should include a mix of resumes from successful existing employees and new applicants for a similar role. The recruiter’s task is to sort these CVs into three categories: "yes" (potential hire), "maybe," and "no." For each decision, they must provide a paragraph explaining the rationale behind their choice, focusing purely on the qualifications, skills, and experience presented. This step establishes a baseline for their judgment, forcing them to articulate a merit-based evaluation without the influence of external factors.

In the second stage, the element of bias is deliberately introduced. The recruiter is given the same set of CVs, but this time with all identifying information—names, addresses, and other personal details—fully visible. They are then asked to review their initial categorizations and make any changes they deem necessary. Critically, for any adjustments made, they must again provide a paragraph detailing their reasoning. A significant shift in a candidate's review—for instance, demoting a qualified individual after discovering a non-traditional name or an unfamiliar address—serves as a tangible indicator of unconscious bias. The written explanations become crucial evidence for evaluating the presence and nature of these prejudices.

The third and final stage of the CV evaluation is designed to assess the recruiter's attention to detail and their ability to align a candidate's profile with a specific job's requirements. The recruiter is given a detailed job description and is asked to re-evaluate the full set of CVs. This time, they must provide a written analysis for each candidate, directly linking their skills and experience to the specific criteria outlined in the job description. This step confirms whether the recruiter is genuinely scrutinizing the qualifications or simply making superficial judgments. It further solidifies the assessment of their review process, as their explanations can be compared across all three stages for consistency and fairness.

Following the CV tests, a behavioral interview should be conducted with a focus on probing for attitudinal biases. Questions should be designed to uncover their personality and ethical compass, such as how they handle a hiring manager's biased preferences, their stance on current world events to assess their views, or what steps they would take to ensure an inclusive candidate pool. The ideal recruiter is not only one who focuses solely on skills and experience, but also one who can actively identify and mitigate bias in others. By combining these three rigorous evaluation stages with a final personality check, companies can effectively hire recruiters who are champions of fairness, ensuring a truly meritocratic hiring pipeline from the very start. The recruiters should then be regularly audited to ensure biases don't continue to seep into the workflow. Furthermore, automating such process steps with agentic AI may reduce human biases and significantly improve the role of recruitment.

Ghosting the Recruiter

The modern job search is a maze of applications, interviews, and often, silence. Among the most frustrating phenomena is ghosting, where a recruiter or company simply disappears after initial contact, leaving candidates in a limbo of unanswered emails and unreturned calls. While the natural inclination might be to stew in frustration or endlessly follow up, there comes a point when the most empowering response is to ghost them right back, permanently blocking their path back into your professional life.

Consider the scenario: You’ve invested time, energy, and hope into a potential opportunity. You’ve polished your resume, tailored your cover letter, perhaps even navigated multiple rounds of interviews. Then, suddenly, the communication ceases. Days turn into a week, a week into two, and the once-promising lead evaporates into thin air. This isn't just a minor inconvenience; it's a profound lack of professional courtesy and respect for your time and effort. It signals a company culture that, at best, is disorganized and, at worst, dismissive of individuals.

The initial impulse might be to persist. "Maybe they're busy," you tell yourself. "Perhaps my email got lost." You send a polite follow-up, then another, each one carrying a diminishing return of hope. But at what point does persistence become self-flagellation? When does the pursuit of an unresponsive entity begin to erode your own sense of worth and professional dignity? The answer, often, is sooner than we realize.

This is where the strategy of ghosting them back into oblivion comes into play. It's not about being petty; it's about reclaiming your agency and setting clear boundaries. Once a reasonable amount of time has passed – say, two weeks after a promised update or a final interview – and all your polite follow-ups have been met with silence, it’s time to consider the relationship severed. This means not just ceasing your own outreach, but actively disengaging. If their emails appear in your inbox, mark them as spam. If their number comes up on your phone, block it. If they reach out on LinkedIn, ignore or block the connection.

This isn't an act of revenge, but an act of self-preservation. By permanently blocking their access, you are sending a clear, albeit silent, message: "My time and professional respect are valuable, and if you cannot reciprocate that, you no longer have a place in my professional sphere." It prevents future attempts at contact, should they suddenly reappear months down the line with another opportunity after realizing their initial oversight. It protects your mental energy from the lingering frustration and the temptation to re-engage with a disrespectful entity.

Moreover, this decisive action allows you to fully pivot your focus to opportunities and organizations that do value your time and effort. It's a psychological release, freeing you from the unproductive cycle of waiting and wondering. In the competitive landscape of careers, your energy is a finite resource. Directing it towards those who demonstrate genuine interest and professionalism is not just a smart strategy; it's a fundamental act of self-respect. So, when a recruiter ghosts you, don't just move on – make a statement by ensuring they can't ghost you again.

Outdated Recruitment Practices and Bottlenecks

The contemporary job market, a dynamic ecosystem of talent and opportunity, frequently encounters a significant impediment at its very threshold: the recruitment process. Despite their crucial role as gatekeepers to organizational success, many recruiters are widely perceived as a primary weakness, actively hindering the efficient alignment of candidates with suitable roles. This widespread frustration stems from a pervasive issue: a fundamental inability or unwillingness to genuinely engage with the very documents designed to showcase a candidate's qualifications – their CVs.

The anecdotal evidence is both abundant and deeply frustrating. It's common to hear of seasoned NLP specialists being queried about their NLP experience or accomplished Python developers, whose public repositories demonstrate their expertise, being asked if they are familiar with Python. These aren't isolated incidents but rather symptoms of a systemic problem where superficial keyword scanning, coupled with a profound lack of domain-specific understanding, leads to absurd questions and the tragic oversight of highly qualified individuals. This cluelessness is far from a minor inconvenience; it represents the single biggest blocker in the entire job market, generating unnecessary friction, squandering invaluable time for both job seekers and hiring managers, and ultimately preventing companies from securing the best possible talent.

The impact of this inefficiency is profoundly multifaceted. For candidates, it's a deeply demoralizing experience. Hours are meticulously spent crafting and tailoring CVs and cover letters, only for these efforts to seemingly dissolve into an unread void by the initial human filter. This often leads to widespread disengagement and a reluctance to apply for roles, even when their qualifications are a perfect match. For companies, the repercussions are equally severe. The inability of recruiters to accurately assess CVs means that ideal candidates are frequently overlooked, while unsuitable ones are mistakenly advanced, resulting in protracted hiring cycles, inflated recruitment costs, and a suboptimal workforce. This human-centric flaw in the initial screening phase directly undermines an organization's capacity to innovate, grow, and maintain a competitive edge.

Compounding this issue are Application Tracking Systems (ATS), which, paradoxically, often exacerbate the problem. While designed for efficiency, many ATS platforms are rigid, relying heavily on keyword matching rather than contextual understanding. This leads to the infamous "resume black hole," where highly qualified candidates are automatically rejected because their CVs don't precisely match the keywords the ATS is programmed to find, even if their experience is directly relevant. There's an overwhelming emphasis on keyword hunting, and a glaring deficiency in genuine understanding and reading of the CV's narrative.

This critical weakness in the recruitment pipeline unequivocally underscores the urgent need for a transformative paradigm shift. It is precisely here that Artificial Intelligence offers a compelling and indispensable solution. AI, with its capacity for rapid, sophisticated data processing and nuanced pattern recognition, can revolutionize how CVs are understood and matched to job descriptions. Unlike human recruiters who may skim or misinterpret, or ATS systems that blindly keyword-match, AI algorithms can analyze vast amounts of textual data with unparalleled precision and semantic understanding. A particularly promising approach involves a hybrid graph-RAG (Retrieval-Augmented Generation) model, combining structured knowledge graphs for explicit relationships, neuro-symbolic AI for reasoning over both symbolic and neural representations, and probabilistic methods to account for uncertainty in matching. They can identify subtle skills, project experience, and career trajectories, cross-referencing them against detailed job requirements to generate highly accurate and contextually relevant matches. Utilizing GNNs would also significantly improve on the connected discourse analysis and context of applied skills rather than just gleaming at surface-level. 

The integration of AI into the initial screening process would not only eliminate the frustrating clueless interactions and the ATS's rigid limitations but also introduce a level of objectivity and efficiency currently unattainable. AI can continuously learn and adapt, refining its comprehension of roles and candidate profiles. By automating the initial, often flawed, human and automated screening, AI can ensure that only the most relevant candidates are passed on to human hiring managers, allowing the latter to focus their invaluable time on assessing cultural fit, soft skills, and conducting in-depth interviews, rather than basic competency checks. This shift is not about dehumanizing the process; it is about optimizing it, ensuring that human expertise is applied where it genuinely adds the most value. Replacing the current, often ineffective, human and automated gatekeepers with intelligent AI systems is not merely an improvement; it is a crucial, non-negotiable step towards a more equitable, efficient, and ultimately, more effective global job market.

Beyond the Numbers

The concepts of diversity, inclusion, and equity (DIE) have become cornerstones of modern organizational ethics, championed for their capacity to foster innovation, enhance understanding, and create fairer workplaces. Yet, the true spirit of DIE can be subtly undermined, even when a workforce appears to represent a specific demographic. Consider a scenario where an entire office floor is predominantly staffed by individuals of Indian origin. While on the surface this might seem to reflect a certain form of diversity within the global talent pool, within the context of a specific national economy and labor market, it can paradoxically represent the antithesis of genuine DIE principles.

Diversity, at its core, is about the breadth of human differences—not just ethnicity, but also gender, age, socio-economic background, thought processes, and experiences. When an entire departmental floor is drawn from a single ethnic group, regardless of their individual merits, the organization risks creating a monoculture. The rich tapestry of perspectives that true diversity offers, leading to more robust problem-solving and creative solutions, is significantly diminished. This homogeneity, even if unintentional, can stifle innovation and limit an organization's ability to connect with a broader customer base or navigate complex global markets. It creates an echo chamber, where similar viewpoints are reinforced, and the challenge of differing opinions is absent.

Furthermore, such a hiring pattern raises critical questions about inclusion and equity. Inclusion is the act of creating an environment where all individuals feel valued, respected, and have equal opportunities to contribute and thrive. Equity, meanwhile, demands fairness in processes and outcomes, addressing historical and systemic disadvantages. If a company consistently hires from a single demographic, particularly if it's perceived to be driven by lower pay scales or an exploitation of specific labor markets, it suggests a potential lack of equitable access for other qualified candidates. This can lead to a perception, and perhaps a reality, of systemic bias, where opportunities are not genuinely open to all. Such practices can foster an exclusionary atmosphere for those outside the dominant group, making them feel like outsiders and hindering their professional growth within the organization.

Beyond the immediate workplace, the implications extend to the national economy. If businesses consistently recruit from a narrow talent pool, driven by the pursuit of cheaper labor, it can depress wages in certain sectors. This not only disadvantages local job seekers but also creates an unsustainable economic model that relies on undercutting labor costs rather than investing in skill development and fair compensation. Such practices can lead to a brain drain in the domestic workforce, as skilled individuals seek opportunities elsewhere, and can contribute to broader economic instability by eroding the purchasing power of the general populace. It undermines the principle of a competitive and fair labor market, where talent is valued irrespective of origin and compensated equitably.

While the presence of any ethnic group in the workforce contributes to a global mosaic, true diversity, inclusion, and equity demand a far more nuanced approach. An office floor populated solely by individuals from one ethnic background, especially if linked to exploitative pay scales, exemplifies a failure to embrace the multifaceted benefits of DIE. It highlights the critical need for organizations to move beyond mere demographic representation and actively cultivate environments that genuinely value varied perspectives, ensure equitable opportunities for all, and contribute positively to the broader economic and social fabric. Only then can the true promise of diversity be realized, fostering workplaces that are not only productive but also truly fair and representative.

Institutional Discrimination Against Muslims

In diverse societies across the globe, the ideal of equal opportunity in the workplace often faces a stark reality for certain communities. Among these, Muslims frequently encounter an unseen, yet deeply impactful, barrier when seeking employment: discrimination. This pervasive issue, rooted in a complex interplay of Islamophobia, stereotypes, and unconscious bias, significantly hinders their career progression and perpetuates social inequality.

At its core, job discrimination against Muslims stems from misconceptions and prejudice. Following significant global events, Islamophobia has surged, fostering a climate where individuals might implicitly or explicitly associate Muslim identity with negative stereotypes such as extremism or a lack of integration. This manifests in various insidious forms during the hiring process. Research consistently shows that job applicants with identifiably Muslim names receive fewer callbacks than those with more common or non-ethnic names, even when their qualifications are identical. This "name-based" discrimination is a subtle but powerful gatekeeper, often operating unconsciously within hiring managers, who might filter resumes based on perceived cultural or religious affiliations.

Beyond names, visible markers of Muslim identity, such as the hijab worn by Muslim women or beards worn by Muslim men, can become unwitting targets of bias. Employers, consciously or unconsciously, may harbor concerns about workplace integration, customer perception, or even safety, leading them to overlook highly qualified candidates. These biases are often unstated and difficult to prove, making it challenging for individuals to pinpoint the exact reason for their rejection, leading to feelings of frustration, helplessness, and self-doubt.

The consequences of this discrimination are far-reaching. For individuals, it can lead to underemployment, prolonged unemployment, and economic hardship, limiting their ability to support themselves and their families. This constant struggle against an invisible prejudice can also take a severe toll on mental health, fostering feelings of isolation, anxiety, and a sense of being perpetually undervalued. On a broader societal level, discrimination robs the workforce of valuable talent, skills, and perspectives, thereby diminishing innovation and productivity. It exacerbates social divisions, undermines the principles of meritocracy, and hinders the creation of truly inclusive communities.

Addressing this issue requires a multifaceted approach. Robust anti-discrimination laws are a crucial first step, providing legal recourse for those affected. However, legal frameworks alone are insufficient. There is a pressing need for comprehensive diversity and inclusion training within organizations, specifically designed to raise awareness about unconscious biases related to religious and ethnic identity. Promoting blind recruitment processes, where identifying information is removed from applications, can also help mitigate initial biases. Furthermore, fostering greater understanding and challenging Islamophobic narratives through public education and media representation can help dismantle the prejudices that fuel discrimination.

Job discrimination against Muslims is a pressing social issue that undermines the promise of equitable opportunities. By understanding its manifestations and impacts, and by actively working to dismantle the prejudices and biases that fuel it, societies can move closer to creating workplaces where merit triumphs over misconception, and every individual, regardless of their faith or background, has a fair chance to contribute and thrive.

Why Companies Struggle to Recruit for AI

The pervasive narrative of an AI talent shortage often overshadows a critical truth: many companies struggle to recruit for AI roles not due to a genuine lack of qualified individuals, but because of deeply flawed and outdated recruitment processes. In a landscape where AI proficiency is paramount, organizations are inadvertently filtering out perfectly capable candidates, exacerbating a problem that is, in many respects, self-inflicted.

One of the most problematic areas is the over-reliance on incompetent keyword hunting within Applicant Tracking Systems (ATS) and by human screeners. Job descriptions for AI roles are frequently overloaded with buzzwords – "deep learning," "natural language processing," "reinforcement learning," "computer vision," "PyTorch," "TensorFlow," "generative AI" – often without a clear understanding of the specific skills required for the actual job function. Recruiters, many of whom lack a deep technical understanding of AI, then program ATS to filter resumes based on the exact presence or frequency of these keywords.

This creates a significant bottleneck. A candidate with a strong foundation in machine learning principles, robust problem-solving skills, and a proven track record in data science might be dismissed if their resume doesn't explicitly list every trending AI library or framework. They might have used equivalent tools, learned concepts through different methodologies, or simply prefer to emphasize their transferable skills and project outcomes rather than a keyword bingo list. This rigid, keyword-centric approach incorrectly identifies a shortage in skills, when in reality, it's merely a failure to recognize relevant capabilities presented in non-standard formats.

Furthermore, this myopic focus on keywords often overlooks the crucial soft skills essential for AI roles. Collaboration, ethical reasoning, strong communication, adaptability, and the ability to explain complex technical concepts to non-technical stakeholders are paramount in AI development and deployment. A resume brimming with technical jargon might pass the keyword filter, but if the candidate lacks these interpersonal abilities, they will ultimately struggle to integrate into a team or drive impactful AI initiatives. However, current screening methods frequently fail to prioritize or even assess these critical attributes early in the process.

Another contributing factor is the lack of realistic job descriptions and career pathways. Companies, in their haste to embrace AI, sometimes create roles that are either too broad or too specialized, failing to acknowledge that many AI professionals develop their skills iteratively and through diverse experiences. This disconnect between advertised roles and the actual day-to-day work can deter qualified candidates who might perceive the role as a poor fit or lacking a clear growth trajectory.

Finally, the competitive landscape dominated by large tech giants also plays a role. Smaller companies often struggle to compete on salary and benefits, leading to a perception that top AI talent is simply unobtainable. However, the true problem might lie in their inability to articulate the unique value proposition they offer – interesting problems, a less bureaucratic environment, direct impact, or a strong learning culture. If their recruitment process filters out individuals who prioritize these non-monetary benefits, they miss out on a significant pool of talent.

While the demand for AI skills is undeniably high, the notion of an overwhelming talent shortage is often a misdiagnosis. By moving beyond superficial keyword hunting, developing a nuanced understanding of AI roles, valuing transferable skills and soft competencies, and offering compelling career propositions, companies can transform their recruitment processes. This strategic shift would not only uncover the hidden wealth of AI talent currently being overlooked but also build more diverse, capable, and sustainable AI teams for the future.

Jobs That Will Fall First As AI Takes Over

The Jobs That Will Fall First As AI Takes Over The Workplace

EveryATS

EveryATS

Use AI for Faster Interview Prep

Use AI for Faster Interview Prep

Bad Sides of Working at a FAANG

• Terrible Work-Life Balance
• You'll be treated as an employee number, sometimes it will feel like a sweatshop
• They want you available 24/7 all day, everyday, at night, weekends, and even holidays
• Work may be reduced to mostly mundane and boring pigeon hole
• Lots of bullying, favortism, sexism, and racism
• Lots of cultural fit innuendos at team events, meetings, and conferences
• Managers will try to steal your ideas and take credit for it
• Only a few people get a chance to do really interesting work
• Pay scales can be meh for majority of the employees
• Huge amount of red tape and slow decision-making process
• You are unlikely to make a huge impact
• High expectations and long hours
• Very competitive environment
• Very performance-driven culture
• Performance reviews can be very biased, they are already setting it against you
• Imposter syndrome
• Lots of frequent performance reviews means job insecurity
• Redundancies can happen at a drop of a hat, especially as management doesn't care about employees, they are just a number
• Shareholders matter over all else
• Corporate culture, less collegial
• Limited growth opportunities, you will be stuck in a rut, your talents and skills wasted
• Overly pretentious culture
• They will try to spoil you with benefits
• People can be rude, obnoxious, and unapproachable
• Lots of corporate secrets, and when things leak they follow huge dramatics and PR
• Lots of lying and deception, nothing as it seems
• Lots of interaction with dumb people who act like they are really smart when they really aren't
• Lots of gaslighting and cognitive biases
• Politics is the order of the day, every day, and it trickles down from management to employees, across regions
• You have to drink their "Kool-Aid", like live and breathe their corporate culture
• Lots of privacy concerns and pressure with public scrutiny
• You will feel like a small cog in a silo of work in a big company
• Culture of secrecy and lack of transparency
• Limited tolerance for mistakes
• Constant changes and sudden decommissions on projects
• Massive codebases so you have to be really careful on what you push out
• Lot's of ethical and moral dilemmas
• Good places to start your first job, not mid-career, or senior-career
• Don't aim to work there for more than couple years due to meager growth opportunities
• Lots of interaction with arrogant people, especially senior management who have very little to show for it
• All the interesting work happens in USA by very few select people in secrecy
• Lots of people who go to ivy league schools who suddenly think they know everything, but are practically zero
• Some people only want to be there because of the brand premium, not because they actually like the job
• It will feel like working at a frat with all the bells and whistles, just a lot worse, with a lot more unprofessional and talentless people
• Very patriarchal corporate culture
• They can be dead beat places for people with lots of ideas and mind for practical innovation as you will suddenly feel lack of value from clueless and lethargic people you interact with at work on a daily basis
• People get used as scapegoats all the time, especially ones that are really into their work or have even a slight glimmer of talent
• Corporate culture is rife with insecure people
• Lots of rush to churn through projects, high project turnover, low quality code everywhere
• Leave best practices out the door, they are not welcome here
• Lots and lots of hypocrisy

Dumb Things Companies Do With Candidates

• Asking candidates to take a series of tests, why do they need to take a test if they have X amount of experience? Do you ask CEOs, accountants, managers, and lawyers to take tests before hiring them?
• Stating you have a specific need on the Job Application, then trying to test the candidate on completely different things
• Stating you have a specific need on the Job Application, then trying to test the candidate, if you can test them on the matter then you already have the skills, what do you need them for?
• Stating you need someone for X because they need to up skill their candidates, but then also stating that your team has the necessary skills, so which is it are they unskilled, do you have incompetent team even after such detailed tests at interview?
• Rejecting candidates because you are looking for specific keywords
• Rejecting candidates because you don’t like how they look
• Rejecting candidates because of diversity, inclusion, and equity reasons, so you specifically looking for a transgender woman? So, basically the opposite of practicing diversity, inclusion, and equity?
• Companies that post ghost jobs to frustrate applicants
• Trying to play games with candidates during interview stages and during offer stages to put them off the role and turning it into a wasted time
• Part way through an interview process putting the job on hold or filling the job internally
• After successfully interviewing and going through the stages telling candidates that they couldn’t secure funding to hire
• Getting candidates to interview for a different role than the one they applied for because you think you know more about a candidate's skills and they would be more suitable for the other role
• Not acknowledging candidate application and then violating GDPR
• Not providing candidate feedback along the interview process and then again violating GDPR
• Using candidate CV/Resume as a scratch paper during the interview which again violates GDPR, especially if you throw it away in the bin in front of them
• Using racist, biased, and discriminatory language during an interview with candidates
• Rejecting a candidate before interviewing them or had a chance to get to know them
• Making assumptions about a candidate application, if you had to make an assumption then what is the point of interviewing them?
• Rejecting a candidate because they like a different football team, even if they had the skills to do the job, like how is that relevant to the role?
• Rejecting a candidate because they didn't use the correct pronouns
• Rejecting a candidate's test because they used american english instead of british english?
• Trying to expect candidates to answer based on a script
• Rejecting a candidate because they gave a different model answer than what you are expecting, even though the candidate answer was likely better than the model solution that you were expecting
• Rejecting a candidate because they make you feel insecure in your own role
• Rejecting a candidate because there aren't enough whitespaces on their CV/Resume
• Run candidates around in circles of red tape and politics
• Not willing to provide the right offer and on time
• Being stingy with job interview feedback
• Showcasing to candidates about how bad it is to work there, especially through employee feedback
• Not using an accurate job ad that reflects the reality of the job
• Talking about cultural fit like you looking to slot fill candidates rather than hire for their skills
• Expecting the candidate to have all the free time in the world and should be completely flexible
• Constantly changing interview dates with candidates, especially at the last minute
• Being too flippant and pedantic
• Refusing to shake hands with candidates during an on-site interview
• Being more curious about the background wallpaper they used on a virtual interview
• Having children running around in the background while conducting a virtual interview
• Asking the same question over and over again to the candidate, especially if the candidate has already answered it in full
• Being patronizing towards the candidate just because they are of a different race or have specific credentials, like what has any of that got to do with the job?
• Mixing up job applications and rejecting the wrong candidate
• Trying to offer a lower compensation to a candidate because they are of a specific racial background then making it obvious
• Rejecting a candidate because you think the candidate  doesn't have the right to work in a specific location even when the candidate has provided proof that they do
• When interviewers are extremely late to interview a candidate and keep them hanging without any courtesy of excuse
• Being distracted with other things while interviewing a candidate
• Ghosting on candidates
• Giving preferential treatment to certain candidates over others while stating you practice diversity, inclusion, and equity

Why ex-Googlers make the worst hires?

• Lots of arrogance but very little to justify it in performance
• Mostly come with sexist, racist, and misogynistic attitude
• Lots of biases for minority hires so your diversity initiatives will suffer
• Lots of biases for pay, work, and benefits
• They significantly effect the team culture through negative attitudes
• Questionable skills and experience
• They will question everything with unconstructive ways of working and the solutions they come up with are usually bookish, unproductive, inefficient, and uncreative
• They lack pragmatism and common sense
• They want to interview people in convoluted ways which have no context nor relevancy to the role just like how they did at Google
• They want to make your organization function like Google like a mirror to their past
• They drive a toxic culture, whatever was bad at Google they bring to every other organization or team
• They like to harass other employees
• They look at others in a team as lesser individuals and make the collective team feel miserable
• Why did they leave Google to come to work at your organization if Google was so great?
• They demand higher compensation packages just for working at Google, while their pay at Google was at best mediocre
• If they are part of the team that has to screen candidate applications they seem to be stuck on where the candidate got their degree and their racial backgrounds then end up interviewing them with racist stereotypes and biases
• They lack job relevant experience and skills because they didn't exactly do much at Google
• They don't want to be interviewed the same way as other candidates, treated like special candidates for some reason (maybe special candidates with disabilities?!)
• You have to flex your entire organizational handbook to meet their ridiculous expectations
• They lack basic work ethics, integrity, and fundamental sense of professionalism in the workplace
• Pretty much every ex-Googler talks and acts like they are still in school or university with emotional immaturity
• They act like spoiled and pampered brats in the workplace
• They lack basic skills of being able to think outside the box
• They tend to be unwilling to learn new things or new ways of doing things
• They tend to frustrate easily on tasks and require a lot of micromanagement
• They tend to be resistant and unwilling to listen to constructive feedback, at times repeat the same mistakes without learning from them by overcompensating with a false sense of overconfidence and lack of experience
• They tend to waste people's time by pontificating and procrastinating
• Habitually putting people down to artificially inflate their egos and prop themselves up
• They tend to be the biggest cynics of other employees in workplace especially if they are not ex-Googlers
• Sometimes they can act as saboteurs or moles out of pure jealousy and resentment

Worst Companies to Work For

• ServiceNow
• Salesforce
• NextEra
• S&P Global
• McDonald's
• Starbucks
• Burger King
• Whole Foods
• Walmart
• Union Pacific
• Signet
• Caffe Nero
• JD Sports
• WH Smith
• Betfred
• Zara
• Taco Bell
• Comfort Call
• Eden Futures
• Tim Hortons
• Max Spielmann
• Bodycare
• Poundstretcher
• Choice Care
• Victoria's Secret
• Valorum Care
• McColls
• Hertz
• Family Dollar Stores
• Steak n Shake
• Speedway
• The Children's Place
• Regal Cinemas
• The Fresh Market
• Rent-A-Car
• Forever 21
• Belk
• Alorica
• CompuCom
• Frontier Communications
• Dillard's
• CVS Health
• Kraft Heinz
• Dish Network
• Sears
• Kroger
• Tyson Foods
• Kmart
• TJMaxx
• Genesis Healthcare
• US Security Associates
• LA Fitness
• Charter Communications
• Amazon
• Tata
• Wipro
• Infosys
• HCL
• Tech Mahindra
• NTT
• Dell
• Cargill
• Reliance Industries
• Comcast
• Wells Fargo
• Bank of America
• Subway
• Shein
• Dollar General
• ExxonMobil
• Balenciaga
• BP
• Spirit Airlines
• Meta
• Twitter
• Tesla
• Fox Corporation
• Trump Organization
• Pfizer
• Coca Cola
• Tesco
• Google
• Microsoft
• Disney
• OpenAI

Why Indians make the worst hires?

• Once you hire an Indian, they will try to get you to hire more Indians, work with more Indians, and try to push for Indian outsourcing
• An Indian manager will have a preference for Indians, lots of biases
• Over time your diversity efforts will get a massive setback
• They generally tend to follow a caste system mindset so brewing ground for racism, prejudice, and discrimination and this will become an issue within teams but also in recruitment/human resources practice. Also, that BJP mentality seems to be spreading across organizations. Likely will be looked over for promotions, increments, recruitment in place of an Indian. 
• Indians don't mingle, assimilate, or interact much with other groups of people
• Interviews become very bookish, like sitting in a classroom
• They can't think outside the box
• They have a tendency of replicating what others have done
• Poor sense of creativity
• Lower salaries in most cases here equates to poor quality of work
• They will be quick to dismiss "no, that cannot be done" if they have not seen someone else do it before
• They need a lot of hand-holding, mentoring, training, and micromanagement
• Ordinarily, implementations will be buggy and not meet requirements
• Indian managers drive a lot of politics, nepotism, low salaries, tend to be rude, and provide for a bad work life balance
• Lots of unnecessary "yes, sir", "no, sir"
• Their judgement of correctness is measured in terms of how other people and organizations are doing things
• That weird smell in the office
• Lots of bad practices
• Nothing ever gets done properly
• They say they can do everything, but nothing is done correctly
• They will want everything for free
• They are not pragmatic, they will follow trends and come with a crowd follower mentality
• They are generally unwilling to challenge the status quo so bad things stay the same
• They are unwilling to take the initiative, be proactive
• They also tend to take credit for other people's work
• Lots of cultural favortism in workplace
• Indian managers and employees drive a toxic work culture
• Many tend to be incompetent, do not deliver on what is on their resume, nor a reflection of their experience
• They have degrees but practically struggle with inexperience
• Communication skills tend to be poor and at times difficult
• Lots of lies and deception to cover things up
• Questionable sense of work ethics
• Overtime your customer service and product quality will degrade

This is not to say you should stop hiring Indians. Some obviously are good but those tend to be few and far between. However, recruitment should always be fair and give everyone an equal opportunity.

Best areas for Entrepreneurs

Best areas is largely subjective based on specific industry, business model, and personal preferences. In most cases, it depends on your needs and goals. Consider also towards industry focus, cost of living, and access to resources. However, in terms of general factors like ease of doing business, access to capital, talent pool, and overall entrepreneurial ecosystem, there are a few hot spots.

• Silicon Valley (California) - USA: established tech startups, venture capital, and highly skilled workforce
• New York City (New York) - USA: global financial hub with a diverse economy and strong entrepreneurial culture
• Austin (Texas) - USA: growing tech scene with lower cost of living than California
• London (UK): a financial center of the world with diverse talent pool
• Berlin (Germany): a major hub for tech startups and digital nomads, affordable and creative scene
• Amsterdam (Netherlands): open environment for entrepreneurs that focus on sustainability and innovation 
• Singapore: advanced business environment with focus on innovation and technology
• Hong Kong: global financial center with access to asian markets
• Dubai (UAE): fast developing city, ambitious plans for global innovation hub
• Toronto (Canada): growing tech scene with strong focus for AI and fintech
• Vancouver (Canada): vibrant with supportive ecosystem and a high quality of life
• Dublin (Ireland): rapidly growing tech scene in software and gaming
• Stockholm (Sweden): strong focus on sustainability and green technology
• Seoul (South Korea): rapidly growing tech scene in mobile and gaming

Useless Management

Most roles in management are utterly useless. What is their role?

Planning:

• Setting goals and objectives for wider organization and teams
• Developing strategies to achieve those goals and objectives
• Development of an action plan and timelines
• Allocation of resources in support of those plans

Organizing:

• Designing origanizational structure
• Defining roles and responsibilities
• Establishing clear lines of communication
• Ensuring organization has the resources and infrastructure

Leading:

• Inspiring and motivating employees in the organization
• Communicating effectively
• Building strong alliances and relationships
• Making decisions to solve problems
• Providing guidance and support

Controlling:

• Monitoring progress towards goals and objectives
• Measuring performance against standards
• Identifying deviations for corrective actionable measures
• Evaluating effectiveness of organization

Other Aspects:

• Interpersonal: building relationships, networking, maintaining reputation, representing the organization
• Informational: gathering, analyzing, spreading correct information for decision making
• Decisional: making decisions to solve problems and providing resources
• Efficiency and Productivity: proving effective and streamlined processes, reduce waste, improve productivity
• Employee Satisfaction: create positive work environments, motive employees, and foster supportive and inclusive work culture
• Organizational Success: setting clear goals, decision making, adapting to change, contributing to success

In essence, management is about getting things done through people. This essentially shows that AI can pretty much replace most managerial roles. Management should be the first point of redundancies when an organization does not do well. In future, we hope to see less management in organization and flatter structure within employees. The role of a manager is pretty much pointless. Why bother hiring a manager and wasting valuable organization funds. Most human managers do not achieve even 10% of their role. AI could make the manager role significantly more efficient and productive for an organization while empowering employees. And, you won't even have to provide them any monetary compensation. The biggest wastage of funds in any organization is management. Another aspect to this is the role reversal. Make managers accountable to employees. And, when things go wrong managers should be the first ones out the door as they failed at their role.