Crypto's take-off year will be defined by stablecoin payments, tokenization, AI agents, security regulation, and escalating threats from fraud, scams, and phishing
Prediction is very difficult, especially about the future. The saying is doubly true in crypto. Just months ago, who would have thought that a world leader would drop a memecoin while another would get rugged by one, or that some zombie-chain tokens would be considered a strategic asset on par with oil, grain, and uranium.
And yet, some patterns are coming into clear focus. Hypernative's over 200 customers, which range from major chains and protocols to asset managers and wallets, give us a privileged view into Web3 developments across industry segments and ecosystems. Below are 5 trends that I believe will dramatically reshape crypto in the coming months.
Stablecoins have found their product-market fit. The total stablecoin market cap surged 48% last year, with transaction volumes tripling to over $27T, according to Coinbase. The US has lagged behind in regulatory clarity, but new bills—the GENIUS Act and the STABLE Act—could unlock adoption, following frameworks already in place in the EU, Singapore, and Japan.
Stablecoins are a natural fit for payments, an industry long dominated by gatekeepers and extractive networks. A16z's Sam Broner estimates that a 1.5% reduction in transaction costs for Walmart, Chipotle, and Krogers could increase their net income by 63%, 12%, and 105% respectively.
Some Web2 companies are already positioning themselves for this future, starting with Stripe's $1.1B acquisition of Bridge and PayPal's launch of PYUSD. The list of banks and financial institutions considering issuing stablecoins includes Bank of America, Standard Chartered, JP Morgan, Visa, BNY Mellon, Fidelity, Societe Generale, and more.
Read more: How Hypernative Secures a $40B Stablecoin Economy
The total value of onchain real-world assets (RWAs) has more than doubled in the past year to almost $18B, but is still just a tiny fraction of the total addressable market measured in trillions of dollars. Growing institutional recognition and clear regulations will unlock new asset classes, spur adoption, and open up new revenue models.
The global regulatory landscape for RWAs varies from friendly (the EU, Switzerland, Singapore, and UAE) to neutral (the UK and Japan) and cautious (China and South Korea). The US is playing catchup and actively developing legislative frameworks for integrating blockchain technology into traditional financial systems. These key US legislative initiatives are likely to serve as catalyst for adoption this year:
Web3 AI agents rode the hype cycle like a roller coaster -- soaring fast, crashing hard, screaming the whole way. While these may not have been the droids we were looking for, autonomous agents in crypto are inevitable.
Today's AI is the worst that it will ever be. One takeaway from the Deepseek bombshell that rocked the AI world (and the markets) is that we are entering a new stage of large language models (LLMs) development that is focused on reasoning. The next generation of models will wield capabilities that will make it impossible to dismiss them as mere stochastic parrots and glorified autocomplete.
Starting this year, we will see an explosion of AI agents use cases:
"Machines are talking about you behind your back," as Douglas Coupland wrote prophetically. This year, they might start transacting on your behalf too.
The rising tide of technology lifts all boats—including those of fraudsters and scammers. Writing malware to steal people's money is so 2010. Now, Fraud-as-a-Service vendors make it easy for anyone to launch a phishing campaign in minutes—no Web3 expertise required.
You can see this technologically-driven acceleration in the average lifespan of malicious contracts, which is now 4x shorter than just four years ago. The addition of powerful open-source language models that can be adapted for nefarious means will only accelerate this trend by making identity fraud easier to perpetrate and harder to resist.
Just as free translation and spellcheck tools made the comical Nigerian prince-style scams a thing of the past, powerful open-source language models adapted for nefarious uses will make phishing attacks more sophisticated. AI models will be used to automate malicious operations, making fraud both easier to perpetrate and harder to resist.
While Web3 is still looking for mainstream adoption, crypto-powered scams are already hitting mid-American mainstreet. That's the take away from the New York Times feature about a small Kansas town bank that was brought down by a pig-butchering scheme. Stories like that resonate with the electorate across party lines, building pressure for legislators to take action.
American investors lost an estimated $3.96 billion to crypto fraud in 2023, according to the FBI. The amount increased 53% from the previous year and, given the technological trends discussed above, will continue to grow.
In a preview of what's to come, the UK watchdog in October introduced new mandatory reimbursement rules for Authorised Push Payment (APP) fraud that require payment service providers reimburse victims for up to £85,000 ($110,000) of losses. In the United Arab Emirates (UAE), providers are required to operate payment transaction monitoring mechanisms designed to prevent, detect, and block fraudulent transactions.
These five trends are interlocking and will interact in complex ways. Regulatory clarity will accelerate tokenization and stablecoin adoption, introducing new security challenges amplified by AI advancements. This in turn will feed into laws mandating security standards. Hypernative is proactively developing products and solutions that anticipate these shifts to equip our customers with the tools to navigate the evolving Web3 landscape safely.
Hypernative is a real-time monitoring, risk detection and automated response solution that identifies threats with high accuracy and gives customers precious minutes to respond before exploits can do damage. The platform tracks both onchain and offchain data sources and uses battle-tested, sophisticated machine learning models, heuristics, simulations, and graph-based detections to identify over 300 risk types, from smart contract hacks and bridge security incidents to frontend compromises, market manipulations and private key theft.
Reach out for a demo of Hypernative’s platform, tune into Hypernative’s blog and our social channels to keep up with the latest on cybersecurity in Web3.
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