Can AI automation transform the economy, or is it just a mirage?

Are AI’s promises of high productivity gains realistic given current technological limitations?

AI promises to automate tasks, increase productivity, and spur economic growth with its productive capabilities, but the path to achieving these lofty goals is fraught with obstacles.

The tech sector’s $1 trillion investment in AI over the next few years has yet to yield major returns beyond modest productivity gains, according to Goldman Sachs. Even NVIDIA, a major player in the AI ​​hardware sector, saw its stock price correct sharply.

The skepticism around the potential of AI is echoed by experts. Take MIT’s Daron Acemoglu, for example. He is highly skeptical about the big promises of AI.

According to him, only a small portion of work tasks will be automated by AI in the next decade, affecting less than 5 percent of all tasks.

He argues that AI will not advance fast enough to have a major economic impact, and predicts only a slight increase in productivity and GDP growth – far from the revolution many envision.

On the other side of the spectrum, Joseph Briggs of Goldman Sachs is more optimistic. He believes that AI will eventually automate 25% of tasks, leading to huge productivity gains.

His optimism is based on the idea that costs will eventually come down and AI automation will become more affordable, but that outlook is tempered by the reality of high start-up costs and technical hurdles to overcome.

Combining AI and crypto introduces a new set of challenges. AI’s need for massive computational power and current limitations in chip supply could slow progress for crypto-based AI applications. Cryptographic algorithms used in AI-powered crypto solutions require extensive processing power that could be hindered by these limitations.

Additionally, power demands for AI data centers are increasing rapidly, putting a strain on our already aging electrical grids. This is particularly critical for crypto mining operations, which are already under scrutiny due to their high energy consumption.

Experts like Microsoft’s former VP of Energy Brian Janous warn that our infrastructure is not ready for this surge in demand, which could hinder the growth of both AI and AI-enabled crypto technologies.

So where does this leave us? Are we on the verge of bursting the AI ​​and crypto bubbles, or are we witnessing the early stages of a technological breakthrough? Let’s find out.

Is an AI-crypto bubble forming?

In recent discussions, leading experts Daron Acemoglu from MIT and Jim Covello, Head of Global Equity Research at Goldman Sachs, shared their views on the future of AI and its economic impact.

Acemoglu is cautious about the economic potential of AI, predicting a modest 0.5% increase in productivity and a 1% increase in GDP over the next decade. This forecast contrasts sharply with Goldman Sachs’ more optimistic estimates of 9% productivity growth and 6.1% GDP growth.

Acemoglu’s skepticism stems from the focus on generative AI, which primarily automates specific tasks rather than transforming entire industries.

For example, AI can increase efficiency in tasks like data analysis, but it will not significantly impact multifaceted tasks that require real-world interaction, such as transportation and manufacturing.

He estimates that AI could cost-effectively automate just 4.6% of all tasks over the next decade, corresponding to a 0.66% increase in total factor productivity and a 0.9% increase in GDP.

Covello shares Acemoglu’s skepticism, but from a different angle. He highlights the significant costs associated with AI infrastructure, which is expected to exceed $1 trillion in the coming years. Covello questions whether AI can solve complex and important problems at a cost that would justify such an investment.

Drawing parallels with past technology transformations, the author notes that AI differs from previous innovations, such as the internet, which offered low-cost solutions from the start, due to its high cost and uncertain return on investment.

Covello also challenges the assumption that AI costs will drop rapidly over time, noting that the AI ​​hardware market is currently dominated by Nvidia, with little competition to drive prices down.

Nvidia’s monopoly, combined with the enormous upfront costs of AI infrastructure, raises questions about whether the technology will ever be affordable enough to be widely adopted.

Despite these reservations, the intersection of AI and crypto is an area of ​​tremendous interest and potential.

Throughout 2024, AI-related crypto tokens have gained popularity, reaching a combined market value of nearly $30 billion as of July 23. This excitement stems from the belief that AI can innovate across a variety of industries, including finance and healthcare.

Additionally, three prominent AI and crypto companies – Fetch.ai, SingularityNET, and Ocean Protocol – recently formed an alliance and merged their tokens to create a new AI token called Artificial Super Intelligence (ASI).

Their vision is to develop a decentralized AI platform targeting Artificial General Intelligence (AGI) and eventually Artificial Super Intelligence (ASI).

While AGI refers to artificial intelligence systems that can perform any human task at the same level of competence, ASI are systems that completely exceed human capabilities.

But the path to ASI is fraught with challenges. The need for massive computing power and limitations in chip supply could slow progress for AI-powered crypto applications.

Additionally, the strain on electrical grids due to the high energy demands of AI data centers and crypto mining operations cannot be ignored.

A continuing unity

Recent developments explain how closely related AI and cryptocurrencies are and how they could become even more compatible in the coming years.

For example, Bitcoin miners are turning to AI after facing decreasing rewards due to the Bitcoin halving event. The last halving event in April 2024 reduced mining rewards from 6.25 Bitcoin to 3.125, prompting companies like Lancium and Crusoe Energy Systems to invest in AI data centers.

Their multibillion-dollar deal to build a 200-megawatt data center in Texas aims to meet the growing demands of artificial intelligence and a move away from traditional Bitcoin mining.

Why is this happening? Bitcoin mining and AI infrastructure share common ground: Both require extensive data centers, high energy consumption, and advanced cooling systems.

As AI’s computational needs grow, Bitcoin miners see an opportunity to repurpose their existing infrastructure. Companies like Core Scientific and Hut 8 have already entered AI, confident in its long-term potential.

Adding another layer to this intersection is the fact that Grayscale recently launched a digital asset fund focused on AI tokens, indicating a rapidly growing demand for them.

So where does this leave us? Are AI and crypto on the verge of a breakthrough or collaboration, or are we just blowing up a bubble?

The answer lies in balancing optimism with realism. Both technologies have enormous potential, but their success depends on overcoming technical, financial and infrastructural challenges.

Given the era we are in, the possibilities are endless. At one end of the spectrum, we could see potential fusion and growth in both sectors, or perhaps a complete overhaul if conditions change.

Whatever the case, the age of technology is sweeping the world and it is certain that unexpected changes are on the horizon in the coming years and decades.