Understanding the Hurdles – Why Companies Aren’t Ready for Full AI Integration in Business – The Daily Hodl

HodlX Guest Post  Submit Your Post

AI (artificial intelligence) is the topic that has got the attention of not only tech enthusiasts but also the general public since last year.

Is AI going to steal my job? Can it fully automate what I’m doing for a living? These and other questions make some people write columns – like yours truly – and make others actually worry about the future.

Yes, it’s probably a tale as old as time – the technological shift affecting the lives of workers. But let me remind you that AI isn’t all that new.

It was on the market for decades, assisting industries such as mass manufacturing, healthcare, finance, logistics, agriculture and many more. Today, AI is everywhere.

PwC suggests that by 2030, AI can contribute $15.7 trillion to the global economy, resulting in up to a 26% boost to local economies’ GDP (gross domestic product).

And earlier this year, we saw over 50 prominent tech companies and institutions joining the AI alliance, including NASA, IBM and Meta, to ‘support open innovation and open science in AI.’

But what’s really behind this AI hype? Are companies ready to hop on the AI mass adoption trend?

Let’s take a closer look at the reasons for the popularity of AI, challenges for companies and trends we can expect in 2024.

Real face of AI adoption by businesses in 2023

In late 2022, ChatGPT did what no other tech company had done before. It reached one million users in a record five days after the launch and then got 100 million monthly active users in just two months.

To compare, it took TikTok nine months and two and a half years for Instagram to reach a 100 million users milestone.

Overall, the VC winter may have negatively affected the tech industry, but AI’s share of US startup funding, for instance, only doubled in 2023.

You could say that AI is a real FOMO (fear of missing out) for all VCs right now, as institutions want to get on board and not miss out on the latest opportunity.

Google, Apple and Amazon began to actively develop their AI solutions immediately after the launch of ChatGPT to succeed their competitors in the ‘race to dominate the [AI] space.’

But in reality, the trend isn’t translating into real-world action, and we experience the opposite – despite all the hype surrounding AI technologies, only 4.4% of American companies use AI for business purposes.

What are the reasons behind this evident gap between the hype and tangible results? Let’s get into the challenges the companies face while implementing this high-tech solution.

The highly centralized and misleading nature of generative AI

As I see it from a business perspective, the mass adoption of generative AI solutions is challenged by a few crucial factors.

First and foremost, it’s still pretty vulnerable due to its centralized nature.

Essentially, AI today is very much dependent on two to three companies with enormous power in their hands – and any self-respecting business will be concerned about the issue of such centralization and oligopoly.

Therefore, now we see numerous Web 3.0 projects actively exploring and working on decentralized AI solutions.

I personally fully support this convergence of AI and Web 3.0 and the potential it can give businesses and individuals alike.

Secondly, referring to the analogy I enjoyed, generative AI is like a ‘proud, bold toddler,’ who can be pretty intimidating and harmful without supervision.

Have you ever tried to ask ChatGPT to generate a piece of written content with factual support from relevant sources?

If not, let me assure you that it can come up with bizarre and non-existent articles, books and even people with other misleading or biased information in mere seconds.

AI relies on large amounts of data to train models and make informed decisions. Therefore, the lack of quality data is a serious barrier to its practical implementation in business.

Hypothetically, this can be solved by introducing AGI (artificial general intelligence).

Theoretically, AGI can accomplish intellectual tasks a human being is capable of – but figuring out when, how and under whose control this can happen is a matter of time.

AI business trends to watch in 2024

So, which industries will lead the AI revolution this year despite the barriers? I believe the fintech and payments industry will be very active in integrating AI into their businesses.

Here, we can mention payment routing processes and various AI-based antifraud solutions.

When it comes to routing, AI can be a great tool to help optimize the routes a provider takes to process bank card data.

Speaking of fraud, for example, this year, OpenAI and ChatGPT launched a partnership with the fintech startup Stripe to combat fraud in the B2C sector.

This way, AI can help scan inbound communications and identify fraudsters’ activity.

Additionally, as I’ve mentioned before, 2024 can be the year of synergy and collaborations between AI and Web 3.0, marking a new era of decentralized solutions.

This can challenge the now prevailing monopoly businesses and even ordinary users are concerned about it.

Finally, I see this year as a catalyst for human-AI or human-machine collaboration. We won’t see jobs being fully automated or humans being replaced by machines – not yet, at least.

Instead, we’ll notice a growing emphasis on human talent that can effectively combine their skill set with knowledge of generative AI and LLM implementation and supervision.

Human AI managers, so to speak.

Ready or not, here it comes

I feel like the past few years have taught business leaders to be even more agile, flexible and adaptable when it comes to market turmoils or other factors.

As we’ve seen, the hype surrounding AI often overshadows the practical challenges companies face when implementing it, but the developments won’t keep us waiting.

With the fintech and payments industry leading the way and the potential of decentralized AI solutions, we can expect to see more exciting advancements in AI in the years to come.

So, let’s keep our eyes on the trends and be ready for the next wave of the AI revolution.

Bakhrom Saydulloev is a C-level executive and a product lead at Mercuryo, a global payments infrastructure platform. Mercuryo provides fiat and crypto businesses with a wide range of financial services accessible through API integration. Bakhrom’s efforts since joining the company have simplified onboarding processes and increased client retention by over 20%.

Generated Image: DALLE3