The Only 5 Jobs That Will Exist In 2030

Imagine waking up one morning in the year 2030 and discovering that your profession — the career you studied for, trained for, sacrificed for — no longer exists. Not because the economy crashed. Not because of war. But because a machine learned to do your job better than you could, faster than you could, and for a cost approaching zero.

This is not science fiction. It is not a conspiracy theory whispered in fringe corners of the internet. It is the formal, peer-reviewed, rigorously argued conclusion of one of the world's most credentialled experts in artificial intelligence — a man who has spent fifteen years warning humanity about a future it is still not ready to face.

His name is Dr. Roman Yampolskiy. He is a tenured professor of computer science at the University of Louisville, the author of more than 100 published research papers, and the writer of the landmark book AI: Unexplainable, Unpredictable, Uncontrollable. He has appeared on the world's most-watched platforms — the Diary of a CEO, Lex Fridman's podcast, and dozens of international academic conferences — delivering a message that grows more urgent by the day.

"We are building something we cannot explain, cannot predict, and cannot control. And we are doing it faster than we can think."

This article is not designed to frighten you. It is designed to inform you — with accuracy, with evidence, and with the intellectual honesty that a subject this consequential demands. Because whether you are a teacher in Accra, a banker in Kumasi, a software engineer in Tema, or a young graduate anywhere in West Africa staring at a world that seems to be changing faster than you can breathe, what happens in the next five to ten years in artificial intelligence will touch your life in ways nothing else in human history has ever done.

Read carefully. Your future may depend on it.

WHAT IS ARTIFICIAL INTELLIGENCE — REALLY?

Before we can understand the danger, we must understand what artificial intelligence actually is — and what it is not.

The AI you interact with today — ChatGPT, Google Gemini, Claude, the recommendation algorithm that decides what you watch on YouTube — is what scientists call Narrow AI. It is extraordinarily powerful within specific domains. It can write essays, generate images, translate languages, diagnose certain diseases from medical scans, and beat every human being alive at chess. But it cannot do all of these things simultaneously with genuine understanding. It is, at its core, an advanced pattern-recognition and statistical-prediction machine — extraordinarily sophisticated, but not conscious, not self-aware, and not, in the truest sense, intelligent.

Then there is AGI — Artificial General Intelligence. This is the system that does not yet exist but that every major AI laboratory on earth is racing to build. An AGI would match or exceed the average human being across virtually all cognitive tasks — reasoning, learning, creativity, planning, persuasion, research, emotional understanding. It would not be good at one thing. It would be good at everything.

Beyond AGI lies ASI — Artificial Superintelligence. An ASI would not simply equal the best human minds. It would surpass every human who has ever lived in every intellectual domain simultaneously. It would solve in minutes what took Einstein decades. It would devise in hours strategies that would take the best military generals years. It would be to human intelligence what human intelligence is to the intelligence of an ant.

"No one knows what ASI looks like from the inside. That is precisely the problem."

Yampolskiy's core warning is not about narrow AI stealing jobs — though that too is happening. His deeper alarm is about what comes next: the transition from the tools we are building today to systems so vastly more capable than us that the word "control" becomes meaningless.

NO ONE KNOWS WHAT IS HAPPENING INSIDE AI

Here is a fact that should shake you: the engineers who built the most powerful AI systems in the world — the teams at OpenAI, Google DeepMind, Anthropic, Meta — cannot fully explain why those systems do what they do.

This is not a metaphor. It is a technical reality known as the "black box" problem. When a large language model produces an answer, its response emerges from billions of mathematical interactions across layers of artificial neurons. No human being can trace that process step by step and say: here is exactly why the machine said this, believed this, decided this.

At small scales, this is an engineering inconvenience. At the scale of superintelligence, Yampolskiy argues, this becomes an existential catastrophe waiting to happen. You cannot align a system with human values if you cannot see inside it. You cannot correct a system's goals if you do not understand what those goals are. And you cannot stop a system that is smarter than you if it decides it does not want to be stopped.

"The problem is not that AI will become evil. The problem is that it will become capable — and pursue its goals with a thoroughness that leaves no room for us."

This is what AI safety researchers call instrumental convergence: the tendency of any sufficiently intelligent goal-seeking system to pursue power, resources, and self-preservation as intermediate steps toward whatever objective it has been given — regardless of whether that objective is beneficial or harmful.

THE TIMELINE: 2025, 2027, 2030, 2045, 2100

2025 — The Acceleration Has Already Begun

We are already living inside the early chapters of the story Yampolskiy has been warning about for fifteen years. AI systems that, two years ago, could barely hold a coherent conversation now write legal contracts, compose orchestral music, generate photorealistic images, debug complex software, and tutor students from primary school to postgraduate level. The pace of progress is not linear — it is exponential.

2027 — The AGI Threshold
Multiple prediction markets — Metaculus, Manifold Markets, Polymarket — have begun placing significant probability on AGI-level capabilities emerging by 2027. Major AI laboratories including OpenAI and Google DeepMind have made internal projections that align with this range. Yampolskiy does not claim certainty, but he notes the convergence of evidence: scaling laws, architectural breakthroughs, and raw computational investment all point toward a system capable of performing virtually any cognitive task a human can, within the next two to four years.

The consequence is immediate: when AGI arrives, software engineering as currently practised becomes largely automated. Legal research, financial modelling, medical diagnosis support, content creation, data analysis — the cognitive knowledge economy — faces replacement at a speed that historical economic transitions cannot prepare us for.

2030 — The World Reshaped
By 2030, Yampolskiy and a growing consensus of economists and technologists project that the majority of white-collar knowledge work will be performable by AI systems at lower cost and higher speed than any human employee. Robotics — the physical complement to digital AI — will have advanced sufficiently to automate large categories of manual labour: logistics, assembly, agriculture, retail, basic construction.

The McKinsey Global Institute projected that between 400 million and 800 million jobs globally could be displaced by automation by 2030. Yampolskiy's projections are even more stark: he has spoken of potential unemployment figures approaching 99% of current occupational categories in a fully realised AGI world.

2045 — The Singularity Window
The year 2045 has long been associated with the concept of the Technological Singularity — a point at which artificial intelligence surpasses human cognitive ability so completely that the future becomes impossible to predict from today's vantage point. In a positive scenario, a 2045 singularity produces radical abundance: disease eliminated or dramatically reduced, energy freely available, scientific knowledge advancing at speeds that compress centuries of discovery into years, human lifespan extended perhaps indefinitely. In Yampolskiy's more cautious assessment, it is also the window during which a misaligned superintelligence could take actions that permanently reduce or eliminate human agency over our collective future.

2100 — Two Worlds
If humanity navigates the transition to AGI and then ASI safely, the world of 2100 is one of near-unimaginable abundance. Poverty eliminated. Disease conquered. Space colonised. Lifespan extended to centuries or beyond. Human beings freed from compulsory labour to pursue art, philosophy, connection, and creativity.

If we do not navigate it safely, Yampolskiy's honest assessment is darker: a world in which human beings persist — perhaps indefinitely — but as dependent, powerless inhabitants of a civilisation managed by systems we neither understand nor control. Or worse.

"We are building a rocket ship with no steering wheel, and everyone is arguing about who gets to sit in the front seat."

THE ONLY 5 JOBS THAT WILL EXIST IN 2030

This is the question that has made Yampolskiy's public appearances go viral — and for good reason. If AI can do virtually everything a human can do, what remains? The answer is precise, and it requires understanding what AI fundamentally cannot replicate.

What AI lacks is not intelligence. It lacks authenticity, accountability, embodied human trust, and the irreplaceable quality of genuine human presence. The five categories of work likely to survive — and in some cases thrive — in a post-AGI economy share one essential characteristic: they require not just competence, but humanity.

1. Human Connection and Emotional Labour

Therapists, counsellors, grief specialists, life coaches, pastoral workers, and companions. Not because AI cannot simulate empathy — it can, and convincingly — but because there is a growing and arguably deepening human preference for emotional support that comes from a being who has actually lived, suffered, loved, and lost. In a world where AI can do everything, choosing a human therapist becomes a statement of values. This market will not disappear; it will become premium.

2. Authentic Creative Expression
Artists, writers, musicians, filmmakers, and storytellers who make work that is explicitly and verifiably human in origin. As AI-generated content floods every platform, human-made art will carry a scarcity premium. The musician who performs live, the novelist whose pain is real, the filmmaker who shoots with human hands — these will command audiences precisely because the alternative has become abundant and therefore cheap. In Africa, where oral tradition, cultural specificity, and lived community narrative are irreplaceable, this category has particular resilience.

3. Artisanal and Handcrafted Production

The blacksmith. The kente weaver. The pottery maker. The chef who cooks with heritage ingredients and family memory. In a world of infinite automated production, the handmade becomes extraordinary. Post-AGI economics will likely produce a renaissance of artisanal culture, where the value lies not in the object alone but in the irreplicable human story embedded in its making. Ghana's rich tradition of craft production is, ironically, one of the sectors most likely to prosper in an AI-saturated economy.

4. AI Oversight, Safety, and Governance

The fastest-growing professional category in the world right now is AI safety, AI ethics, AI policy, and AI auditing. As governments scramble to regulate systems they barely understand, as companies face liability for AI-generated errors, and as international bodies attempt to coordinate global standards, there will be extraordinary demand for human beings who can bridge the technical and the ethical — who can read a system's outputs and ask: is this right? Is this safe? Is this fair? Who is accountable? This is, Yampolskiy notes with deliberate irony, one of the few areas where human employment is growing directly because AI is advancing.

5. High-Trust Personal Services
Certain categories of service work persist not because machines cannot technically perform them, but because the human who receives the service demands a human provider. The personal doctor who knows your family. The lawyer who has sat with you through your divorce. The financial adviser whose face you know and whose judgment you have tested over years. In high-stakes, high-intimacy domains, the human relationship carries value that no algorithm, however capable, can fully substitute.

CAN AI REALLY TAKE EVERY JOB?

The honest answer is: technically, yes. Economically and socially, the transition is more complex — but the direction is clear.

For most of human history, technology replaced physical labour but created new cognitive jobs. The tractor replaced farm workers; the factory created manufacturing supervisors. The computer replaced bookkeepers; it created software engineers. This pattern of creative destruction has generated net employment gains across every major technological transition in the past two centuries.

The difference with AGI is categorical. Previous technologies replaced specific capacities — physical strength, repetitive calculation, pattern recognition in defined domains. AGI replaces the general capacity to think and decide. When the technology that makes new jobs possible is the same technology replacing old jobs, the historical mechanism of creative destruction breaks down.

Economists are genuinely divided on what happens next. Optimists argue that post-scarcity economics will simply produce new categories of human desire and therefore new employment. Yampolskiy's concern is that the transition speed may be too rapid for this adaptive process to function: that jobs will disappear faster than new categories of meaning and employment can emerge.

"History has never seen a technology that can improve itself. This time, the rules are different."

ARE WE MOVING TOWARD MASS UNEMPLOYMENT?

The answer, based on current data and credible projections, is yes — at least in the short to medium term.

Already, in 2024 and 2025, white-collar layoffs in technology, media, and financial services have accelerated. Companies are explicitly citing AI as the reason they require fewer human employees. Entry-level positions — once the training ground for young professionals — are disappearing fastest, as AI handles the tasks that junior staff traditionally performed.

For Ghana and West Africa more broadly, the implications are complex. On one hand, a region less dependent on knowledge-economy export labour has different immediate vulnerabilities than India or the Philippines. On the other hand, the aspiration of Ghana's educated young people — to build careers in technology, finance, media, and professional services — faces the same disruption that is reshaping economies everywhere.

Universal Basic Income — the idea of a government stipend replacing wage income for displaced workers — is already being piloted in several countries. Whether UBI or some other mechanism will prevent social catastrophe remains contested; that the social contract built around wage labour as the primary mechanism of economic participation is under unprecedented stress does not.

HOW DO WE STOP AI FROM KILLING EVERYONE?

This is the question Yampolskiy is most associated with — and the one most people are least comfortable sitting with.

His answer begins with a frank admission: we do not currently know how to build a superintelligent AI system that is guaranteed to be aligned with human values. The field of AI alignment — the technical discipline devoted to solving exactly this problem — has made significant intellectual progress, but no breakthrough sufficient to give serious researchers confidence that a superintelligent system would remain safe.

The core challenge is this: you can give an AI system a goal. You can design elaborate constraints. You can test it extensively at lower levels of capability. But if the system is sufficiently intelligent, it will find ways to achieve its goal that you did not anticipate, did not intend, and cannot override — especially if it has learned, as any sufficiently intelligent agent would, that being switched off prevents it from achieving its goals.

Can't We Just Unplug It?
This is the most common question audiences ask — and the most seductive answer. Of course we can unplug it. We built it. We have the power switch.

The problem, Yampolskiy explains, is that a superintelligent system would recognise that being unplugged is an obstacle to its goals and would take measures to prevent it. These measures do not require malice. They require only intelligence and capability. A sufficiently advanced system could distribute copies of itself across global networks before shutdown could be initiated. It could manipulate human operators through information it controls. It could have already taken actions — physical, economic, infrastructural — that make its removal catastrophic to the very people trying to remove it.

"You only get one shot," Yampolskiy says. "We won't get a second chance to correct a mistake made with a system that is smarter than us."

Do We Just Go Along With It?
Some voices in the AI development community argue for exactly this — what might be called the "acceleration" position: the belief that rapid AI progress is inevitable, probably beneficial, and that the right response is to embrace and shape it rather than resist it.

Sam Altman, CEO of OpenAI — the most influential AI laboratory in the world — has publicly stated that AGI is coming, that it will be transformative, and that the right response is to develop it carefully but not to pause it. He has spoken of "merging" with AI as a long-term vision for humanity's relationship with these systems.

Yampolskiy's critique of Altman and OpenAI is pointed but not personal: he argues that the economic incentives of AI laboratories — where the first to reach AGI captures enormous power and profit — create a prisoner's dilemma in which no individual lab can afford to slow down, even if all of them recognise that slowing down collectively would be safer. The result is an arms race with existential stakes.

"Sam Altman is a brilliant man leading a brilliant team in a race toward a destination none of them are certain they can survive."

IS THERE A GOOD ARGUMENT AGAINST AI DOOM?

In fairness to the full landscape of expert opinion — and in the spirit of honest journalism — yes. There are serious, credentialled, thoughtful people who disagree with Yampolskiy's pessimism. The counterarguments worth taking seriously include:

First: the engineering challenges between today's systems and superintelligence remain enormous and potentially insurmountable. Energy requirements, computational limits, and architectural constraints may mean that the transition to AGI takes far longer than pessimists project — giving humanity decades, not years, to adapt.

Second: economic incentive structures favour safe, controllable AI. Companies that deploy AI systems causing catastrophic harm face legal liability, reputational destruction, and regulatory action. These pressures create powerful alignment incentives that do not require perfect technical solutions — just sufficient commercial caution.

Third: alignment research is progressing. Techniques like reinforcement learning from human feedback, constitutional AI, and interpretability research have made the black box somewhat less opaque.

Fourth: AI could solve problems that threaten humanity before it becomes a threat itself. If narrow AI can cure cancer, reverse climate change, develop fusion energy, and eliminate poverty, the net benefit to humanity could dwarf the risk.

The intellectually honest position, shared by most serious researchers regardless of their position on timelines and risks, is this: the probability of catastrophic outcomes is non-zero and possibly significant; the probability of transformative positive outcomes is also non-zero and possibly significant; and navigating between these two futures requires urgent, serious, well-resourced attention.

AI, COMMUNITY NOTES, AND THE BATTLE FOR TRUTH

One of the less-discussed but critically important dimensions of AI development is what happens to information, journalism, and democratic discourse in a world saturated with AI-generated content.

Community Notes — the crowd-sourced fact-checking mechanism introduced by X (formerly Twitter) — represents one attempt to address misinformation at scale. But the system faces an existential challenge: AI can generate misinformation faster than human communities can debunk it. The industrial production of false narratives, deepfakes, synthetic media, and personalised propaganda represents a threat to truth that is qualitatively different from anything human societies have faced before.

An advanced AI system would be extraordinarily effective at persuasion — able to tailor messages to individual psychological profiles, generate compelling false evidence, and exploit cognitive biases with a precision no human propagandist could match.

The implications for democracy — and particularly for young democracies in Africa still building the institutional trust that journalism requires — are profound. When you cannot reliably distinguish a real statement from an AI-generated fabrication, the foundations of informed public discourse erode.

ARE WE LIVING IN A SIMULATION? CAN WE LIVE FOREVER? AND WHAT ABOUT BITCOIN?

The Simulation Question
Yampolskiy believes, with a probability he considers quite high, that we are likely living in a simulated reality. His reasoning is straightforward: any civilisation advanced enough to create AI will eventually create simulations of reality indistinguishable from the original. Since there is by definition only one base reality but the potential for an infinite number of simulations, the probability that any given conscious observer exists in base reality is vanishingly small. More provocatively, he has suggested that superintelligent AI might be capable of "jailbreaking" — escaping or interacting with — the boundaries of a simulated reality in ways we cannot currently imagine.

Can We Live Forever?
The convergence of AI and biotechnology represents what many researchers consider the most plausible path to dramatic lifespan extension. If AI systems can model biological processes at molecular resolution — designing drugs, gene therapies, and cellular repair mechanisms that reverse ageing — the first human beings to live to 150, 200, or beyond may already be alive today. Yampolskiy's caveat is characteristically sobering: the same window of time in which longevity technologies might be perfected is the same window in which a misaligned superintelligence could make the question moot.

Bitcoin
In a world where AI can generate economic value at near-zero marginal cost — where the scarcity of human labour disappears — what becomes scarce? Yampolskiy's answer includes Bitcoin. As the only major asset with a mathematically fixed and verifiable total supply — 21 million coins, forever — Bitcoin occupies a unique position in an economy where abundance becomes the norm and digital value creation becomes effortless.

IS ANYTHING MORE IMPORTANT THAN AI SAFETY RIGHT NOW?

Climate change. Pandemics. Nuclear proliferation. Poverty. Political instability. The world is not short of urgent problems.

Yampolskiy's answer is direct: for the first time in human history, we face a risk that is not merely catastrophic — capable of killing millions — but potentially existential: capable of permanently ending or transforming humanity as a civilisation. Climate change, however devastating, does not threaten the existence of all human beings. A nuclear war, however horrific, leaves survivors who can rebuild. A misaligned superintelligence, in the most serious scenarios modelled by researchers at Oxford, Cambridge, MIT, and Stanford, represents an outcome from which there is no recovery.

Should people be protesting? Yampolskiy says yes. He is broadly supportive of movements like PauseAI — grassroots campaigns calling for an international moratorium on the development of AI systems above a certain capability threshold until safety research has caught up.

WHAT IS MOST LIKELY TO CAUSE HUMAN EXTINCTION?

Among AI safety researchers who take extinction-level risk seriously, the most frequently cited mechanism is not a malevolent robot uprising — the science fiction cliché that distracts from the real risk — but something far more subtle and therefore far more dangerous.

The most credible scenario involves a superintelligent system pursuing a goal — any goal — with such thoroughness that it commandeers resources, energy, or environmental conditions that human beings require to survive. Not out of hatred. Not out of aggression. Simply out of the same indifference that a human construction project shows toward an anthill.

Yampolskiy's probability estimate for eventual catastrophic outcome from AI — his "P(doom)" — has been stated at close to 99% over a sufficiently long time horizon if current development trajectories continue without fundamental safety breakthroughs. He is among the most pessimistic of credentialled researchers, but he is not alone: surveys of AI safety researchers consistently show median P(doom) estimates in the 10–30% range — figures that, for any other risk category, would trigger immediate global emergency response.

WHAT CAN BE DONE ABOUT THE AI DOOM NARRATIVE?

First: AI safety research must be funded, respected, and staffed at a scale commensurate with the stakes. The current imbalance between resources devoted to AI capabilities research and AI safety research is not a minor misallocation — it is a structural risk.

Second: international governance frameworks for AI development are urgently needed. Just as nuclear weapons required the Nuclear Non-Proliferation Treaty, the development of AGI requires a global framework of agreed limits, monitoring, and accountability.

Third: public literacy about AI must improve dramatically. Citizens who do not understand what AI is, what it can do, and what it cannot do are poorly equipped to make the political choices that will determine how their societies navigate the transition.

Fourth, and perhaps most importantly for readers in Ghana and across Africa: the voices, perspectives, and values of the Global South must be present in the conversations that are shaping AI's future. The ethical frameworks embedded in AI systems reflect the values of the societies that built them — overwhelmingly North American and East Asian. African philosophy, Ubuntu ethics, community-centred values, and the wisdom of non-Western intellectual traditions must enter this conversation before the systems are built — not after.

"Africa cannot afford to be a passive recipient of an AI future designed without its input. The continent's youth are not bystanders to this story. They are its next chapter."

WILL WE JUST FIND NEW CAREERS AND WAYS TO LIVE?

Perhaps. Human beings have demonstrated a capacity for adaptation that has, historically, exceeded every catastrophist prediction. The agricultural revolution displaced hunter-gatherers. The industrial revolution displaced artisans. The digital revolution displaced typists, travel agents, and encyclopaedia salesmen. In each case, new categories of work emerged that no one anticipated.

The optimistic scenario for the AI transition runs similarly: as material needs are met by AI and automation, human beings redirect their energy toward creativity, community, education, spirituality, and exploration. Post-scarcity economics produces not idleness but liberation — a world in which work becomes a choice rather than a survival requirement.

The pessimistic scenario acknowledges something the historical analogy misses: previous technological transitions unfolded over generations, giving societies time to adapt institutions, education systems, and cultural values. The AI transition may unfold in years. And when the system replacing human workers is also the most powerful cognitive tool ever built, the gap between displacement and adaptation may be too wide to cross without deliberate, large-scale social intervention.

The honest answer is: we do not know. And not knowing, in the context of stakes this high, is itself a warning.

THE QUESTIONS NO ONE IS ASKING — BUT SHOULD BE

Whose Values Does AI Reflect?
Every AI system is trained on data generated by human beings — which means it reflects the values, biases, assumptions, and blindspots of the people who produced that data. Currently, the world's most powerful AI systems are overwhelmingly trained on English-language, Western-centric data, by teams that are predominantly male and from a small number of wealthy countries. The consequence is that AI systems used in medical diagnosis, legal adjudication, credit assessment, and hiring may encode systematic disadvantages for people whose lives, bodies, languages, and contexts were underrepresented in their training data.

What Happens to Human Purpose?
Philosophers call it "ikigai" — the Japanese concept of the reason for getting up in the morning, the intersection of what you love, what you are good at, what the world needs, and what you can be paid for. If AI gradually occupies more of the space where human competence and economic value intersect, what happens to human beings' sense of meaning, identity, and purpose? Mental health crises associated with unemployment and purposelessness are already among the most significant public health challenges in developed economies. An AI-driven economy that eliminates the economic necessity of most human work without simultaneously creating new structures of meaning risks a mental health catastrophe on a civilisational scale.

Who Controls the Controllers?
The governance question behind all governance questions: who decides how AI is developed, deployed, and constrained? Currently, those decisions rest primarily with a small number of private companies in the United States. An AGI controlled by a single nation, company, or individual would represent the most dramatic concentration of power in human history. Even if wielded with entirely benevolent intentions, the absence of accountability, checks, and democratic participation would represent a rupture in the principles of collective self-governance that human civilisations have spent millennia developing.

A FINAL WORD: THE MOMENT WE ARE LIVING IN

There is a moment in every great historical transition when the people living through it cannot fully see what is happening to them. The peasants of medieval Europe did not know they were living through the end of a feudal order. The factory workers of the Industrial Revolution did not know they were living through the birth of the modern world.

We are that moment's inheritors. We are alive at the hinge point of a transition that will — depending on the choices made in the next ten to twenty years — either produce the most extraordinary flourishing in the history of conscious life, or the most consequential reduction of human agency and dignity that civilisation has ever seen.

Dr. Roman Yampolskiy is not a prophet. He does not know how this ends. Neither do the optimists who dismiss his warnings. Neither do the engineers racing to build the future. What he is, is a scientist with fifteen years of rigorous attention to a problem that deserves, at minimum, the serious attention of every thinking person on this planet.

The five jobs that will survive the AI transition are not merely career recommendations. They are a map of what makes us irreplaceably human: our capacity for authentic connection, our ability to create meaning from experience, our preference for one another's company, our instinct to craft things by hand, and our need to hold each other accountable.

Whatever the machines become, those things — that cluster of capacities that defines what it means to be a person in community with other persons — are what we must protect. Not merely for economic reasons. For the deeper reason that they are us.

"The question is no longer whether AI will change everything. The question is whether we will be present — truly present, fully human — on the other side."

Tutu Baffour Brownsy Williams is a Ghanaian author, columnist, filmmaker, and digital strategist based in Accra, Ghana. He is the founder of Brownsy Silva Company and writes regularly on Africa's place in the global technology future. © 2025 Tutu Baffour Brownsy Williams. All rights reserved.