Artificial
Intelligence Development in the Next Five Years
 |
A Look Into the Future |
What Is Happening With AI Right Now?
Imagine
your computer getting smarter and faster every single day. That is what is
happening with artificial intelligence, or AI, right now. Over the next five
years, from now until 2030, AI is going to change in some really big ways. This
is not just about better apps on your phone or smarter robots. It is about how
computers will help us solve problems in science, medicine, and almost every
part of our lives.
Think
of AI like a student who is learning very quickly. Right now, we are teaching
AI to do more complicated things, and we are giving it more computing power to
work with. By 2030, these AI systems will be so advanced that they might help
scientists discover new medicines, help doctors find diseases earlier, and even
help teachers make lessons that work better for each student.
How Much Power Does AI Need?
Here
is something interesting: AI computers need a lot of electricity. Right now,
data centers that run AI use about 55 gigawatts of power. To understand what
that means, think of a gigawatt as enough electricity to power about 750,000
homes. By 2030, AI data centers could need up to 200 gigawatts. That is almost
as much electricity as a country like Japan uses for everything combined
(McKinsey, 2025).
Why
does AI need so much power? When AI trains itself to get smarter, it processes
billions and billions of pieces of information. Each piece of information needs
electricity to be processed. The bigger the AI model, the more electricity it
needs. Some of the most advanced AI training runs today use as much power as
100,000 homes. By 2030, a single AI training run could use as much power as 1
million homes (Goldman Sachs, 2025).
The
cost of building all this equipment is enormous too. Companies will need to
spend about 6.7 trillion dollars worldwide just to build the computers and data
centers needed for AI by 2030 (McKinsey, 2025). That is 6.7 million million
dollars. To put that in perspective, that is roughly the total money the entire
world economy makes in one year.
What Will AI Be Able to Do?
Let us
talk about something more exciting: what AI will actually do for us. By 2030,
AI is going to be really good at helping people do their jobs better. Imagine
an AI that can read scientific papers and help researchers come up with new
ideas. That is coming. AI will be able to help mathematicians write down proofs
for mathematical problems. It will be able to look at information about
diseases and help doctors know what is wrong with a patient before the patient
even feels sick (Epoch AI, 2025).
In
hospitals, doctors are going to use AI more and more. AI can already look at
images of people's eyes and find out if they have diabetes. It can look at skin
and find early signs of cancer. The AI can do this in less than one second. By
2030, these AI doctors will be even better. They will be able to combine
information about your genes, your medical history, and your daily activities
to tell you when you might get sick. Then you can do something about it before
it becomes a real problem (University of Queensland, 2021).
At
work, things are going to change too. Many companies are starting to use AI
workers that can do specific jobs by themselves without a human telling them
what to do every single time. These AI workers are like coworkers who never get
tired. They can answer customer questions, organize files, or help create
reports. Right now, 41% of businesses say they think half of what they do will
be done by AI workers by 2025. By 2027, more than half of companies will
probably be using AI workers (Tech-Stack, 2025).
Could AI Become Human-Like?
This
is the big question that a lot of people are asking: Could AI become as smart
as humans? Some experts call this artificial general intelligence, or AGI. It
is a scary-sounding term, but it just means an AI that can do anything a human
can do.
Different
experts have different ideas about when this might happen. Some think it could
happen in just a few years, maybe by 2028 or 2029. Others think it will take
longer, maybe 15 to 20 years. The truth is, nobody really knows for sure
(AIMultiple, 2025). It is like trying to guess when someone invented the
airplane back in the 1800s. People had different ideas about how long it would
take.
What
we do know is that AI is getting smarter really fast. Every time we make AI
bigger and give it more data to learn from, it seems to get better at doing new
things. But AI still makes mistakes that humans would never make. AI can write
really interesting stories, but sometimes it gets facts wrong. AI can help with
math, but it sometimes cannot handle problems that are a little different from
what it has seen before (Clearer Thinking, 2025).
Who Is Making Rules for AI?
As AI
gets more powerful, people are starting to ask important questions: Who should
control AI? What should AI be allowed to do? What should AI not be allowed to
do? Different countries are coming up with different answers.
In
Europe, they made a big set of rules called the EU AI Act. These rules say that
some kinds of AI are too dangerous and should not be used at all. For example,
AI should not be allowed to judge people based on their skin color or where
they come from. Other kinds of AI, like AI that helps with medical decisions,
have to be very careful and transparent about how they work (AI21, 2025).
The
United States has taken a different approach. They are letting companies mostly
decide for themselves how to make AI safely, without as many government rules.
Different countries have different ideas about this, and that is actually
pretty normal. When something new comes along, people have to figure out the
best way to handle it (Mind Foundry, 2025).
The
important thing is that people are talking about these issues now, before AI
gets even more powerful. It is like making traffic rules before everyone gets
cars. You want the rules to make sense before people are already using the
roads.
The Jobs Question
One
thing people worry about is jobs. If AI can do more and more things, will there
be jobs left for people? The answer is complicated.
The
world will need many more people who know how to work with AI and machine
learning. Right now, there are not enough people with these skills. Companies
need programmers, engineers, and data scientists. By 2030, companies might need
85 million more people in these jobs than there are actually available
(MobiDev, 2025).
At the
same time, some jobs might change or disappear. Jobs that are very routine and
repetitive might be done by AI instead. But history shows us that new
technologies usually create new jobs while old jobs change. When computers
first came out, people worried that no one would need office workers anymore.
Instead, computers created millions of new jobs.
The
real challenge is helping people learn new skills if their old job changes. If
you work in a job that might be affected by AI, learning about AI and how it
works could help you stay valuable to your company (Nexford, 2025).
Real-World Examples
Let us
look at some things that are actually happening right now, not five years from
now. AI is already helping farmers know when to plant crops and when to harvest
them. Farmers use AI to look at their soil, the weather, and past harvests to
make better decisions. This is saving money and growing more food.
Hospitals
are using AI right now to help read X-rays and find tumors faster than humans
can. In some places, AI has found cancers that human doctors missed. Companies
are using AI to predict what customers will want to buy before the customers
even know they want it. Stores are using AI to decide how much of each product
to stock. These things show that AI is not just a future idea. It is here now,
and it is already making real changes in the world.
What Should You Know?
If you
are a young person thinking about your future, here are some important things
to know: First, AI is not magic. It is a tool, like a calculator or a
microscope. It is really smart and fast, but it still has limitations. It makes
mistakes. It cannot think about things in completely new ways like humans can.
Second,
learning about AI does not mean you have to become a computer programmer.
People will need people who understand AI to help make ethical decisions about
how to use it. You might become a doctor who works with AI, or a teacher who
helps students learn about AI, or a businessperson who uses AI to make better
decisions.
Third,
AI is made by people, and people can decide how to use it. We can choose to use
AI to help people or to hurt people. We can choose to make AI systems that are
fair or unfair. The choices we make now about AI will affect what the future
looks like.
Looking Forward
The
next five years are going to be really interesting for AI. It is going to get
smarter, faster, and more powerful. It will help solve problems we have not
solved yet. It might create some new problems we have not thought about.
What
is important is that we pay attention to what is happening. You do not have to
be a scientist to care about AI. You do not have to be a programmer to ask good
questions about how AI is being used. Just like everyone thinks about whether
new medicines are safe or whether laws are fair, everyone should think about
whether AI is being used in ways that help people.
The future of AI depends on the choices people make today. And those choices will shape what the world looks like for your generation.
References
AI21. (2025, October 29). What are the key principles of AI governance frameworks for 2025. AI21 Knowledge. https://www.ai21.com/knowledge/ai-governance-frameworks/
AIMultiple. (2025, September 25). When will AGI/singularity happen? 8,590 predictions analyzed. AIMultiple Research. https://research.aimultiple.com/artificial-general-intelligence-singularity-timing/
Clearer Thinking. (2025, October 27). Why there's so much disagreement about the timeline for advanced AI. Clearer Thinking. https://www.clearerthinking.org/post/why-there-s-so-much-disagreement-about-the-timeline-for-advanced-ai
Epoch AI. (2025, September 15). What will AI look like in 2030? Epoch AI Blog. https://epoch.ai/blog/what-will-ai-look-like-in-2030
Goldman Sachs. (2025, February 3). AI to drive 165% increase in data center power demand by 2030. Goldman Sachs Research. https://www.goldmansachs.com/insights/articles/ai-to-drive-165-increase-in-data-center-power-demand-by-2030
McKinsey. (2025, April 27). The cost of compute: A $7 trillion race to scale data centers. McKinsey Insights. https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-cost-of-compute-a-7-trillion-dollar-race-to-scale-data-centers
MobiDev. (2025, September 10). Top 13 machine learning trends CTOs need to know in 2025. MobiDev Blog. https://mobidev.biz/blog/future-machine-learning-trends-impact-business
Mind Foundry. (2025, January 24). AI regulations around the world - 2025. Mind Foundry Blog. https://www.mindfoundry.ai/blog/ai-regulations-around-the-world
Nexford. (2025, October 19). How will artificial intelligence affect jobs 2025-2030. Nexford University Insights. https://www.nexford.edu/insights/how-will-ai-affect-jobs
Tech-Stack. (2025, February 10). Top AI development trends for 2025-2030: What's next? Tech-Stack Blog. https://tech-stack.com/blog/top-ai-dev-trends/
University of Queensland. (2021, March 31). Expert artificial intelligence (AI) predictions. UQ Business School. https://business.uq.edu.au/momentum/4-ways-ai-will-revolutionise-the-world