In recent years, artificial intelligence

has been marketed as the technology that

will replace humans. But today, this is

still far from happening.

>> Look, I think what it's going to do is

completely transform the industry. It's

going to change the way content is

created, produced, and distributed. But

that doesn't mean there isn't going to

be a role for the great artists who are

in roles today.

>> Well, a recent study reveals that AI

fails in 96% of almost all real

professional tasks it performs.

>> But this was just a reaction to the

headline, because as you dig deeper into

what was actually said in the report,

the picture isn't as clear-cut as AI is

simply failing everywhere.

>> In addition, it makes many constant

errors, such as producing corrupt files

or incomplete work that forces people to

redo them from scratch.

>> But the real problem is you don't know

what it's made of, and you don't know

what's accurate. So you or your staff

manually have to go back and check

everything.

>> For this reason, AI cannot work on its

own, since it does not understand rules

and does not know what it is doing. It

only imitates language without having

real logic.

>> But sometimes, that answer is unwieldy

or not what you wanted.

>> Despite this, many companies are laying

off people, while one in five AI systems

makes critical errors in sectors such as

medicine or engineering. Even in the

medical field, Reuters just reported

that the FDA has received 100 reports of

AI malfunctions, botched surgeries, and

misidentified body parts.

>> Thus, what seemed to be the future of

work could become a problem with much

more serious consequences than expected.

So, why is AI failing so much? In recent

years, artificial intelligence has gone

from being a technological promise to a

tool present in daily life. More than

300 million people use AI in their work,

which has accelerated the debate about

its impact on employment. However, a

recent study shows that AI fails in 96%

of professional tasks, which raises

doubts about its ability to replace

humans anytime soon. As companies invest

large amounts of money in this

technology, expectations also grow. The

six US firms pouring the most cash into

AI are projected to spend over 750

billion dollars on it this year alone,

more than the entire GDP of Ireland.

>> It is expected to take on complex

functions autonomously. More than 400

million dollars are allocated each year

to the development of new models,

reflecting market confidence in its

potential. It is estimated that AI

investment up to 2025 shows steady

growth, reaching 126 trillion dollars.

However, there is a clear gap between

what is expected from these systems and

what they can actually deliver with

professional quality. This gap raises a

clear issue regarding the true scope of

artificial intelligence in today's labor

market.

>> It's only honest for people um to speak

frankly about the fact this will have a

big effect on the job market.

>> One of the main problems is the low

effectiveness of AI in real tasks. In

tests carried out in areas such as

design, programming, and writing, more

than 500 different professional tasks

were evaluated. Most systems failed to

complete them correctly. This shows that

although AI can generate content, it

still does not reach the level of

precision required for human work. In

addition, only 12% of the results were

considered acceptable without

modifications. This limitation becomes

even more evident when results are

compared with human performance under

similar conditions. In work carried out

by professionals, eight out of 10 tasks

meet standards from the start. This

shows a clear difference in consistency

and reliability. AI can produce fast

responses, but the final quality still

depends on human intervention.

Furthermore, more than 200 million work

tasks have been analyzed across

different sectors to measure AI

performance. Despite this volume of

testing, results continue to show that

technology does not fully adapt to the

demands of professional work. In one

study, GenAI failed in 95% of cases

where companies tried implementing it.

In another study of 25,000 Danish

workers, introducing AI meant more work

for about 8% of people.

>> Added to this limitation are the

frequent technical errors these systems

present. In many cases, AI generates

corrupted or incomplete files that

cannot be used directly in a

professional environment. This not only

affects work quality, but also causes

delays in processes. For example, in

programming tests, around 35% of

solutions had failures that prevented

execution. This type of error forces a

human to review and correct the work

from scratch, reducing the expected

benefit of automation. Additionally, it

is estimated that more than 230 million

AI-generated files require some type of

correction before they can be used. On

top of that, around 35% of results

contain formatting errors that make

immediate use difficult. This shows that

the technology is still not fully

reliable in producing technical content.

>> And like we told you the beginning of

this, we did use AI to make part of this

segment, and when we got back from the

prompt that we put in, there were

actually a lot of mistakes.

>> On the other hand, it is important to

understand that AI works better as a

tool rather than a complete replacement

for human work. Its real value lies in

its ability to support processes and

improve efficiency in specific tasks. In

simple activities such as summarizing

information or generating drafts, it can

reduce work time by approximately 40%.

This allows professionals to focus on

more complex tasks. However, these

benefits largely depend on constant

human supervision. When AI is used

without control, results tend to lose

quality. In many cases, errors go

unnoticed without proper review. In

fact, teams that combine AI with

supervision achieve better results,

where seven out of 10 tasks reach an

acceptable level. Additionally, more

than 150 million workers use AI as

support in their daily activities. This

shows that its current role is more

related to assistance than full

replacement.

>> Sure, we're going to have some jobs that

change, but really it's going to be

about working hand in hand with AI,

using AI as our co-worker.

>> Despite these limitations, many

companies have begun making rushed

decisions regarding the use of AI. In

some sectors, human teams have been

reduced by 15% with the expectation that

technology can cover those functions

without issues. However, results have

not been as expected. In several cases,

staff reduction has led to a decrease in

work quality and an increase in

operational errors. This situation has

forced many organizations to rethink

their strategies. It is estimated that

more than 110 million workers could be

affected by similar decisions in the

coming years. However, it is also

expected that three out of 10 companies

will need to rehire staff to recover

lost quality levels. Additionally,

around 45% of companies that implemented

AI rapidly have reported problems in

their internal processes. This

highlights poorly planned adoption. The

CEO recently walked that policy back and

started hiring people again. Not out of

the goodness of his heart, but because

AI just couldn't cut it, and he's not

alone. Another key aspect is the lack of

real logic in these systems. Although

they can generate coherent text, they do

not truly understand the content they

produce. This limits their ability to

make correct decisions in complex

situations. In specific tests, more than

60% of decisions made by these systems

were incorrect when practical rule

application was required. This shows

that AI does not possess a deep

understanding of the world. This

limitation is also reflected in the fact

that five out of 10 responses contain

reasoning errors in complex contexts.

Although the language may appear

correct, the content can have

significant flaws. Additionally, more

than 170 million analyzed interactions

show that AI tends to repeat patterns

without evaluating whether they are

appropriate for each situation. All of

these disasters make sense. LLMs predict

the next word statistically, but they'll

never tell you when it doesn't know the

answer or if it can't understand

something. Finally, risks increase when

AI is used in critical areas where

errors can have serious consequences. In

sectors such as medicine or engineering,

precision is essential. A 25% increase

has been observed in incidents related

to the improper use of automated systems

in technical environments. This data

reflects the importance of maintaining

constant human oversight. Additionally,

more than 60 million automated decisions

per year require human review to avoid

significant errors. This shows that

technology still cannot assume full

responsibility in these fields. Compared

to processes controlled by

professionals, two out of five automated

results present risks that cannot be

ignored. And in another study focusing

on programmers specifically, AI made

coding take 19% longer on average.

Despite the advancement of artificial

intelligence, its inability to perform

complex tasks with precision shows that

it is still not ready to replace humans.

The gap between expectations and reality

remains wide, confirming that its role

should remain as support rather than a

substitute.

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