There are clear signs that AI will change or
disrupt a whole host of industries:
● ●
Intelligent transportation will make traffic
way more efficient.
● ●
Autonomous driving and electric cars will
bring dramatic changes to the automotive
industry.
● ●
Personalised education will deliver
efficiency gains for both teachers and
students.
● ●
In healthcare, early prevention and
precision treatment have the potential to
increase life expectancy.
● ●
Precision drug trials will cut the cost and
time of discovering new medicine.
● ●
With real-time translation across multiple
languages, communication will be easier
than ever before.
● ●
Tele c om ne t work O p er ation and
Maintenance (O&M) will become more
efficient.
The list goes on.
In just the past year since we launched Huawei
Cloud EI and HiAI, we have already seen AI drive
unprecedented momentum across all kinds of
industries.
AI will also change every organisation
We have seen several technological revolutions
since the 18th century. Each has had a huge
impact on organisational structures, processes,
and workforce skills. But AI will change jobs and
skills in a way that is quite different from the
previous revolutions.
Previous revolutions led to huge demand
for repetitive routine tasks, such as operating
equipment in textile mills, and running car
and phone assembly lines. AI will greatly
boost automation in almost all aspects of an
organisation. This means there will be much less
demand for jobs that handle repetitive, routine
tasks.
Demand for data science jobs will keep rising,
including those for data scientists and data
science engineers with basic know-how in data
science. The total number of these jobs will be
much smaller than the number of jobs that handle
repetitive, routine tasks.
It is likely that organisations will become more
diamond-shaped, with AI systems taking the place
of the people at the bottom, where they handle
huge volumes of repetitive and routine tasks.
AI-triggered change has just begun.
Finding the right problem is more
important than devising a novel solution
Change can mean good news for some and bad
news for others, especially when the changes first
start to emerge.
Some people might get excited about the new,
once-unimaginable functions that AI will make
possible. These people will feel a strong urge to
drive large-scale AI adoption. And there will also
be those who feel anxious about underperforming
AI projects, or who worry about the reliability and
security of AI applications. These are the ones who
will remain uncertain about how to best use AI in
the future.
If we look at the history of all GPTs, these
reactions to AI are all very natural.
There are four different phases along the AI
productivity/adoption curve. We have just left the
first phase, where exploration of AI technology and
application takes place on a small scale.
Now we are in the second phase, where new
technology and society are colliding. From a tech
perspective, more issues are emerging as AI
technology continues to advance. If we look at
things from an application perspective, however,
the value of AI is seeing greater recognition as it
comes into wider use.
That said, existing policies, corporate
processes, and workforces are built around older
technologies, such as those in the information
and Internet eras. The broader social environment
is not yet ready for the AI era. Therefore, in this
phase we see a certain degree of collision, even
conflict, between tech development and society.
However, AI will ultimately find itself in a
social environment that is more conducive to its
development and application. When that happens,
we will step into the third phase, where we will see
rapid, comprehensive advances in AI adoption and
productivity.
The fourth phase will be the golden era of
AI, where humanity will benefit from a constant
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