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Forbes
3 days ago
- Business
- Forbes
5 Reasons Why 'New-Collar Careers' Are On The Rise In 2025
new-collar careers are on the rise The term "new-collar careers" was first coined by IBM's former CEO Ginni Rometty to describe positions that prioritize skills and certifications over traditional four-year degrees. Unlike white-collar jobs that require a college education or blue-collar work involving physical labor, these roles focus on practical capabilities and technical competencies. Today, new-collar positions offer median salaries exceeding $159,000, according to research by Resume Genius, representing a fundamental shift in how the American workforce values human capital. Five documented forces are reshaping career advancement, creating opportunities that favor skills-based workers over traditionally credentialed candidates. Average student debt reaches $37,000 per graduate, according to federal data. Meanwhile, 41% of recent college graduates work in positions that never required a degree to begin with, creating a compelling economic case for alternative pathways. Information security analysts earn a median salary of $124,910, according to Bureau of Labor Statistics data. Workers entering this field early can accumulate substantial earnings while college-bound peers accumulate debt. According to Junior Achievement, 66% of teens aged 13-17 are likely to consider starting a business or becoming entrepreneurs, suggesting entrepreneurial thinking may prepare young people for skills-based career paths. Early exposure to real-world work experience and entrepreneurship programs provides significant advantages. Teenagers who participate in business mentorship programs, internships, or entrepreneurial education develop practical skills that directly translate to new-collar careers—such as problem-solving, communication, project management, and financial literacy. What this means for you: The traditional college track may no longer offer the best return on investment, especially in fields where practical skills are more valued than academic credentials. Starting skill development in high school through entrepreneurship programs, real-world jobs, or internship experience can provide a crucial head start. Labor market data reveals dramatic shifts in hiring practices. Information security analyst roles show 33% projected growth through 2033—nearly triple the average rate, according to Bureau of Labor Statistics projections. Computer network architects are projected to experience 13% growth. Health services managers are seeing a 29% expansion. Marketing manager roles look to grow 8% annually. Major employers, including IBM, Google, and Apple, have removed degree requirements for numerous positions, prioritizing demonstrated competencies over educational backgrounds. According to Resume Genius data, 65% of employers will prioritize skills and practical experience over formal education by 2025. Why this matters: The job market is actively rewarding practical capabilities over academic achievements. Workers who focus on building demonstrable skills in high-demand areas can access opportunities that were previously limited to college graduates. Online learning platforms, bootcamps, and industry certifications have made advanced skills accessible without traditional institutional barriers. Workers can acquire specialized knowledge in a matter of months rather than years. Professional certifications carry increasing weight with employers. Industry-specific credentials often signal more relevant expertise than broad academic degrees, particularly in rapidly changing technological fields. The speed advantage is significant: cybersecurity professionals can earn a CompTIA Security+ certification in three months, compared to the four years typically required for a traditional computer science education. What this means for career changers: You can pivot to high-paying fields in months, not years. A focused certification program can provide faster entry to lucrative careers than returning to school for another degree. For young people still in high school, combining entrepreneurship programs or business competitions with technical certifications creates an even stronger foundation for new-collar success. The remote work revolution fundamentally altered career accessibility. Every high-paying new-collar role identified in Resume Genius research offers remote or hybrid options. This geographic freedom reduces cost pressures that traditionally favored college graduates. Workers can maintain competitive salaries while living in affordable areas, maximizing purchasing power compared to peers tied to expensive metropolitan markets. Remote work capabilities particularly benefit younger workers who may lack the resources to relocate to expensive business centers for traditional career opportunities. Why this matters to you: Location no longer limits your earning potential. You can access six-figure salaries while living in affordable areas, dramatically improving your quality of life and financial position compared to traditional career paths that require expensive urban living. Artificial intelligence is on the rise, but it is increasing the demand for roles that require human judgment, creativity, and relationship management. Resume Genius excluded positions with automation risk above 50% from their analysis. The remaining roles require strategic thinking, empathy, and complex problem-solving that machines cannot easily replicate. These roles are rooted in judgment, empathy, and real-time decision-making—qualities that AI can't replicate. What this means for your future: Focusing on skills that complement rather than compete with AI provides job security. Roles requiring emotional intelligence, strategic thinking, and complex problem-solving will become increasingly valuable as automation handles routine tasks. All these forces feed off each other. Student debt pushes people away from college. Employers can't find the skills they need. Technology makes learning faster and cheaper. Remote work opens up geography. AI makes human skills more valuable. The result? A completely different job market. Resume Genius research shows this isn't temporary—it's how the economy will work going forward. Companies win, too. They can hire from a bigger pool of candidates, spend less on recruiting, and get workers who can start contributing immediately—no need to train someone for months when they already know what they're doing. Workers can now choose strategies that align with their learning styles, financial situations, and career goals. Success can be more readily attained in new-collar careers if workers focus on developing practical skills, engaging in continuous learning, and achieving demonstrable results. If you can prove your value through portfolios, certifications, and real-world achievements, you will thrive regardless of your educational background. The economic and technological forces driving new-collar careers show no signs of slowing. The question isn't whether these opportunities will continue growing—the data suggests they will. The question is how quickly traditional institutions will adapt to this documented reality.
Time of India
02-06-2025
- Business
- Time of India
The rise of new-collar jobs: 6 skill-based careers for the modern workforce
6 skill-based careers for the modern workforce In today's rapidly evolving job market, the traditional path of earning a four-year college degree before entering a well-paying career is no longer the only route to success. A growing number of industries are embracing 'new-collar jobs'—positions that require specific skills but not necessarily a university diploma. These roles offer attractive salaries, job stability, and opportunities for advancement, making them especially appealing to career changers, high school graduates, and lifelong learners. What are new-collar jobs ? New-collar jobs are skilled positions that typically require education and training beyond high school, but not necessarily a bachelor's degree. Instead of traditional academic credentials, employers prioritize practical skills, certifications, and hands-on experience. These roles often exist in tech-driven or rapidly changing industries where adaptability, problem-solving, and specific technical expertise are valued over formal education. The term was popularised by IBM CEO Ginni Rometty in the mid-2010s to describe a new category of jobs emerging in fields such as cybersecurity, data analytics, and cloud computing. Since then, the concept has expanded across sectors including healthcare, manufacturing, finance, and green energy. Who is eligible for new-collar jobs? The good news is: almost anyone. Eligibility largely depends on skills, mindset, and willingness to learn rather than academic background. New-collar roles are accessible to: High school graduates seeking career paths without a degree. Career switchers from traditional industries. Workers displaced by automation or layoffs. Veterans or individuals returning to the workforce. Learners who complete bootcamps, certificate programs, or apprenticeships. Soft skills—like communication, teamwork, adaptability—and a readiness to upskill are often just as important as technical know-how. Here are six such new-collar jobs anyone can take up. Cybersecurity Analyst Cybersecurity analysts protect systems from data breaches, malware, and cyberattacks. With threats rising worldwide, demand is growing fast. Many professionals enter the field with certifications like CompTIA Security+ or after completing IT bootcamps. Salaries typically range from $95,000 to $120,000 depending on experience and specialisation. Cloud Support Specialist These professionals help organisations manage cloud infrastructure using platforms like AWS, Microsoft Azure, or Google Cloud. Cloud support specialists often start with entry-level certifications such as AWS Certified Cloud Practitioner. This role can earn between $85,000 and $110,000 per year and serves as a stepping stone to more advanced cloud engineering positions. UX/UI Designer UX/UI designers are responsible for creating intuitive and visually appealing interfaces for websites, apps, and other digital products. While formal education in design helps, many break into the field through UX bootcamps and strong portfolios. Annual salaries range from $80,000 to $110,000, particularly in tech-forward industries and startups. Data Analyst Data analysts help organisations make informed decisions by interpreting data and identifying trends. While a degree in statistics or economics can be helpful, many analysts today come from nontraditional backgrounds and complete short courses in tools like SQL, Python, or Tableau. Entry-level analysts can expect salaries ranging from $75,000 to $100,000 annually. Medical Coding Specialist Medical coding specialists play a vital role in the healthcare ecosystem, ensuring accurate records for insurance and billing purposes. Most employers require a certification such as the CPC (Certified Professional Coder). After training, coders generally earn between $55,000 and $75,000 per year. Industrial Automation Technician In high-tech manufacturing environments, industrial automation technicians install, maintain, and troubleshoot robotics and automated machinery. Many enter the field through associate degrees or certifications in mechatronics or industrial systems. These technicians can earn between $70,000 and $95,000, depending on industry and location. New-collar jobs represent a significant shift in how we think about career success. As employers continue to prioritize real-world skills and experience over formal degrees, opportunities are opening up for individuals across a wide range of backgrounds. Whether you're just starting out, considering a career change, or looking to reskill in a growing industry, new-collar roles provide a flexible, affordable, and future-proof path to success. Ready to navigate global policies? Secure your overseas future. Get expert guidance now!
Forbes
22-05-2025
- Business
- Forbes
Leading Change In The AI Era: Familiar Rules, New Realities
Change has always been hard. Today it feels even harder. But for all the noise surrounding generative AI, it's easy to forget something fundamental: Generative AI–related transformation is still just change. It follows the same human patterns leaders have navigated for decades. The difference now? The velocity, the visibility, and the stakes. Executives and investors are confronting a dual challenge: They must apply time-tested change principles and wrestle with unfamiliar questions about trust, experimentation, and scaling. Understanding this duality is the key to leading effectively in the AI era. At its foundation, change remains a behavioral discipline. Successful change requires human beings to understand it, accept it, and adopt new ways of working. After all, organizations don't change—people do. Core truths still apply: With the advent of generative AI, these truths only become more important. Change fatigue, ambiguity, and fear of displacement require even stronger storytelling, deeper trust-building, and faster learning loops. Encouraging adoption is a critical responsibility of leaders today. As Ginni Rometty, former CEO of IBM, has said: 'AI will not replace humans, but those who use AI will replace those who don't.' Despite its familiar patterns, generative AI introduces new dynamics that leaders can't ignore: This makes generative AI change feel different than past tech shifts. Acceptance is earned through doing, not announcing. Discovery and experimentation are not phases; they are the change. With generative AI, old change playbooks need new questions. Leaders must reframe how they plan, lead, and scale change across five dimensions: accelerating value, leading change, customization, engaging people, and governing wisely. Accelerating value: Leading change: Customization: Engaging people: Governing wisely: These aren't just operational concerns; they are leadership imperatives. In the AI era, leadership is less about overseeing projects and more about modeling belief. Leaders must become narrators, shaping an inspiring vision for how generative AI fits into the organization's future and how team members can contribute. They must become architects, designing systems that support experimentation while protecting trust. And they must become sponsors, lending credibility and confidence to teams navigating uncertainty. AI literacy is now part of leadership literacy. Without it, leaders can't ask the right questions, much less sponsor the right answers. Forward-thinking CEOs are stepping up to the challenge. In Japan, it's the rare executive conversation in which this topic does not come up. Digital natives are all in. Duolingo CEO Luis von Ahn, for example, has declared that not only his technology but his whole company is going to be 'AI-first.' To that end, he is instituting what he calls 'constructive constraints,' such as including AI use as part of everyone's performance review. AI may be the catalyst, the augmentation tool, but humans drive change. The excitement and anxiety around generative AI are both justified. But amid the hype, the real differentiator won't be who builds the minimal viable product for a particular use case fastest; it will be who leads the organizational change most effectively. Change is still about humans. Trust still matters. Clarity still wins. But the questions are sharper now, and the pace is faster. Leaders who embrace both the known and the novel will not only navigate this era—they'll shape it.
Business Mayor
11-05-2025
- Business
- Business Mayor
From silicon to sentience: The legacy guiding AI's next frontier and human cognitive migration
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Humans have always migrated, not only across physical landscapes, but through ways of working and thinking. Every major technological revolution has demanded some kind of migration: From field to factory, from muscle to machine, from analog habits to digital reflexes. These shifts did not simply change what we did for work; they reshaped how we defined ourselves and what we believed made us valuable. One vivid example of technological displacement comes from the early 20th century. In 1890, more than 13,000 companies in the U.S. built horse-drawn carriages. By 1920, fewer than 100 remained. In the span of a single generation, an entire industry collapsed. As Microsoft's blog The Day the Horse Lost Its Job recounts, this was not just about transportation, it was about the displacement of millions of workers, the demise of trades, the reorientation of city life and the mass enablement of continental mobility. Technological progress, when it comes, does not ask for permission. Today, as AI grows more capable, we are entering a time of cognitive migration when humans must move again. This time, however, the displacement is less physical and more mental: Away from tasks machines are rapidly mastering, and toward domains where human creativity, ethical judgment and emotional insight remain essential. From the Industrial Revolution to the digital office, history is full of migrations triggered by machinery. Each required new skills, new institutions and new narratives about what it means to contribute. Each created new winners and left others behind. In October 2015 at a Gartner industry conference, IBM CEO Ginni Rometty publicly declared the beginning of what the company called the Cognitive Era . It was more than a clever marketing campaign; it was a redefinition of strategic direction and, arguably, a signal flare to the rest of the tech industry that a new phase of computing had arrived. Where previous decades had been shaped by programmable systems based on rules written by human software engineers, the Cognitive Era would be defined by systems that could learn, adapt and improve over time. These systems, powered by machine learning (ML) and natural language processing (NLP), would not be explicitly told what to do. They would infer, synthesize and interact. At the center of this vision was IBM's Watson, which had already made headlines in 2011 for defeating human champions on Jeopardy! But the real promise of Watson was not about winning quiz shows. Instead, it was helping doctors sort through thousands of clinical trials to suggest treatments, or to assist lawyers analyzing vast corpuses of case law. IBM pitched Watson not as a replacement for experts, but as an amplifier of human intelligence, the first cognitive co-pilot. This framing change was significant. Unlike earlier tech eras that emphasized automation and efficiency, the Cognitive Era emphasized partnership. IBM spoke of 'augmented intelligence' rather than 'artificial intelligence,' positioning these new systems as collaborators, not competitors. But implicit in this vision was something deeper: A recognition that cognitive labor, long the hallmark of the white-collar professional class, was no longer safe from automation. Just as the steam engine displaced physical labor, cognitive computing would begin to encroach on domains once thought exclusively human: language, diagnosis and judgment. IBM's declaration was both optimistic and sobering. It imagined a future where humans could do ever more with the help of machines. It also hinted at a future where value would need to migrate once again, this time into domains where machines still struggled — such as meaning-making, emotional resonance and ethical reasoning. The declaration of a Cognitive Era was seen as significant at the time, yet few then realized its long-term implications. It was, in essence, the formal announcement of the next great migration; one not of bodies, but of minds. It signaled a shift in terrain, and a new journey that would test not just our skills, but our identity. To understand the great cognitive migration now underway and how it is qualitatively unique in human history, we must first briefly consider the migrations that came before it. From the rise of factories in the Industrial Revolution to the digitization of the modern workplace, every major innovation has demanded a shift in skills, institutions and our assumptions about what it means to contribute. The Industrial Revolution, beginning in the late 18th century, marked the first great migration of human labor on a mass scale into entirely new ways of working. Steam power, mechanization and the rise of factory systems pulled millions of people from rural agrarian life into crowded, industrializing cities. What had once been local, seasonal and physical labor became regimented, specialized and disciplined, with productivity as the driving force. This transition did not just change where people worked; it changed who they were. The village blacksmith or cobbler moved to new roles and became cogs in a vast industrial machine. Time clocks, shift work and the logic of efficiency began to redefine human contribution. Entire generations had to learn new skills, embrace new routines and accept new hierarchies. It was not just labor that migrated, it was identity. Just as importantly, institutions had to migrate too. Public education systems expanded to produce a literate industrial workforce. Governments adapted labor laws to new economic conditions. Unions emerged. Cities grew rapidly, often without infrastructure to match. It was messy, uneven and traumatic. It also marked the beginning of a modern world shaped by — and increasingly for — machines. This migration created a repeated pattern: Modern technology displaces, and people and society need to adapt. This adaptation could happen gradually — or sometimes violently — until eventually, a new equilibrium emerged. But every wave has asked more of us. The Industrial Revolution required our bodies. The next would require our minds. If the Industrial Revolution demanded our bodies, the Digital Revolution demanded new minds. Beginning in the mid-20th century and accelerating through the 1980s and '90s, computing technologies transformed human work once again. This time, repetitive mechanical tasks were increasingly replaced with information processing and symbolic manipulation. In what is sometimes called the Information Age, clerks became data analysts and designers became digital architects. Administrators, engineers and even artists began working with pixels and code instead of paper and pen. Work moved from the factory floor to the office tower, and eventually to the screen in our pocket. Knowledge work became not just dominant, but aspirational. The computer and the spreadsheet became the picks and shovels of a new economic order. I saw this first-hand early in my career when working as a software engineer at Hewlett Packard. Several newly-minted MBA graduates arrived with HP-branded Vectra PCs and Lotus 1-2-3 spreadsheet software. It was seemingly at that moment when data analysts began proffering cost-benefit analyses, transforming enterprise operational efficiency. This migration was less visibly traumatic than the one from farm to factory, but no less significant. It redefined productivity in cognitive terms: memory, organization, abstraction. It also brought new forms of inequality between those who could master digital systems and those who were left behind. And, once again, institutions scrambled to keep pace. Schools retooled for '21st-century skills.' Companies reorganized information flows using techniques like 'business process reengineering.' Identity shifted again too, this time from laborer to knowledge worker. Now, midway through the third decade of the 21st century, even knowledge work is becoming automated, and white-collar workers can feel the climate shifting. The next migration has already begun. We have migrated our labor across fields, factorie, and fiber optics. Each time, we have adapted. This has often been uneven and sometimes painful, but we have transitioned to a new normalcy, a new equilibrium. However, the cognitive migration now underway is unlike those before it. It does not just change how we work; it challenges what we have long believed makes us irreplaceable: Our rational mind. As AI grows more capable, we must shift once more. Not toward harder skills, but toward deeper ones that remain human strengths, including creativity, ethics, empathy, meaning and even spirituality. This is the most profound migration yet because this time, it is not just about surviving the shift. It is about discovering who we are beyond what we produce and understanding the true nature of our value. The timeline for each technological migration has also accelerated dramatically. The Industrial Revolution unfolded over a century, allowing generational adaptation. The Digital Revolution compressed that timeline into a few decades. Some workers began their careers with paper files and retired managing cloud databases. Now, the next migration is occurring in mere years. For example, large language models (LLMs) went from academic projects to workplace tools in less than five years. William Bridges noted in the 2003 revision of 'Managing Transitions:' 'It is the acceleration of the pace of change in the past several decades that we are having trouble assimilating and that throws us into transition.' The pace of change is far faster now than it was in 2003, which makes this even more urgent. This acceleration is reflected not only in AI software but also in the underlying hardware. In the Digital Revolution, the predominant computing element was the CPU that executed instructions serially based on rules coded explicitly by a software engineer. Now, the dominant computing element is the GPU, which executes instructions in parallel and learns from data rather than rules. The parallel execution of tasks provides an implicit acceleration of computing. It is no coincidence that Nvidia, the leading developer of GPUs, refers to this as 'accelerated computing.' Transitions that once evolved across generations are now occurring within a single career, or even a single decade. This particular shift demands not just new skills, but a fundamental reassessment of what makes us human. Unlike previous technological shifts, we cannot simply learn new tools or adopt new routines. We must migrate to terrain where our uniquely human qualities of creativity, ethical judgment and meaning-making become our defining strengths. The challenge before us is not merely technological adaptation but existential redefinition. As AI systems master what we once thought as uniquely human tasks, we find ourselves on an accelerated journey to discover what truly lies beyond automation: The essence of being human in an age where intelligence alone is no longer our exclusive domain.
Hi Dubai
27-01-2025
- Business
- Hi Dubai
Key Insights on the Future of Jobs from Davos 2025
The 2025 World Economic Forum (WEF) in Davos, Switzerland, held from January 20 to 24, brought together global leaders to address one of the most pressing issues of our time: the future of work. Under the theme "Investing in People," the discussions centered on navigating the profound shifts in careers and the workforce driven by technological advancements, demographic changes, and the urgent need for sustainability. The Future of Jobs Report 2025 provided a stark yet hopeful outlook. By 2030, nearly 25% of current jobs will undergo significant structural changes, with 170 million new roles emerging and 92 million being displaced. This transformation, while daunting, presents an opportunity for individuals and organizations to adapt and thrive. Emerging sectors such as engineering, electric vehicle technology, and the green economy are poised for growth, while traditional roles face decline due to automation and artificial intelligence (AI). Ivanka Trump, a prominent voice at the forum, emphasized the need for a skills-based approach to learning. "We have to think about skills-based learning, as opposed to purely credentials... Employers care about the skills," she stated. This sentiment was echoed throughout the discussions, highlighting the importance of resilience, flexibility, and technological literacy in the workforce of tomorrow. The Role of AI: Augmentation, Not Destruction AI took center stage in many conversations, with leaders challenging the narrative of AI as a job destroyer. Instead, they framed it as a powerful tool for augmentation. Ginni Rometty, Chairman and CEO of IBM, stressed the need for new education models and pathways to retrain workers. "You have to value skills and not just degrees. You have to have new education models and new pathways to get people retrained and back into the workforce," she said. Robert E. Moritz, Global Chairman of PwC, underscored the importance of continuous learning. "The mindset of continuous learning is really important as the number one skill set—for our teachers learning how to teach and for our students learning how to learn," he remarked. This focus on lifelong learning is critical as the pace of technological change accelerates. Demographic Shifts and Global Challenges Demographic changes emerged as another key topic. High-income countries are grappling with an aging population, driving demand for healthcare roles. In contrast, low-income nations must expand education-related professions to support their growing working-age populations. Saadia Zahidi, Managing Director of WEF, highlighted the dual challenge: "How do we ensure that people have pathways to social mobility? One of the most important ways to do that is to ensure that people have the right education, the right skills, and the right jobs." Diversity and Gender Equality as Economic Drivers The forum also emphasized the importance of diversity and gender equality in driving economic success. The Gender Parity Sprint initiative aims to close the gender gap in economic participation by 2030. Studies presented at Davos revealed that diverse teams perform better both organizationally and financially. Nobel Laureate Professor Muhammad Yunus articulated a compelling perspective on the role of women in economic development: "If the goals of economic development include improving the general standard of living, reducing poverty, creating dignified employment opportunities, and reducing inequality, then it is natural to work through women." His remarks underscored the necessity of addressing gender inequality to achieve comprehensive economic progress. The Green Skills Imperative As sustainability transitions from aspiration to necessity, the demand for "green skills" is surging. However, the current supply of talent with these skills falls short. Workforce development initiatives must urgently bridge this gap to prepare workers for roles in clean energy, conservation, and sustainable practices. For professionals in countries like Bangladesh, this represents a global opportunity to build careers in less-explored but rapidly growing domains. A Call to Action The discussions at Davos 2025 served as a clarion call for governments and businesses to prioritize sustainability, diversity, and reskilling. Marc Benioff, Chairman and CEO of Salesforce, issued a direct challenge to attendees: "If you are attending this conference, you need to commit to job training. If you are attending this conference, you need to commit to reskilling." The overarching message from Davos was clear: adapting to the future of work is not just about surviving change but seizing the opportunities it presents. Whether through reshaping education systems, fostering continuous learning, or championing inclusivity, success will require collaboration across all sectors and communities. As Benioff aptly concluded, "Reskilling is not optional; it is essential." News Source: International Publications Limited
