3 Web3.0 Industry Trends Affecting Current Blockchain Businesses

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By 2030, the Web3 industry‘s market size is projected to reach £66.3 billion, and many companies and start-ups are planning to introduce new products and solutions in the coming years. According to me, the current Web3 cycle might be longer than previous ones, not only because of internal factors but also due to the overall state of the global economy. “There remain many challenges to be overcome, particularly for blockchain and crypto-related projects, whose tech is also intrinsically linked to Web3, but the next year could be key to implementing many of these strategies in practice,” says Chammah. 

 

“It is timely to take a look at some of the key projections for the Web3 industry, and understand how it may continue to evolve and transform. Web trends are always changing, but what will be big in the future?” These are the major Web3 industry trends that businesses should be aware of. #1 – A rise in decentralized autonomous organizations (DAOs) governed by autonomous smart contracts DAOs governed by autonomous smart contracts are emerging as a new option for digital distribution platforms in the creator economy. These organizations don’t depend on centralization to share their content, which creates opportunities for creators who prefer self-management. However, there are risks inherent in this choice, as these DAOs lack regulatory intervention. 

 

Design flaws and vulnerabilities in the source code of smart contracts can pose a major risk to sustainable operations and continuous user acquisition by DAOs. Fully computer-controlled operations leave zero fallback options in the event of a protocol hijack caused by a compromised contract. Therefore, it is essential to conduct diligent code review and testing practices in the early stages as well as throughout the lifecycle of DAOs where these smart contracts form the backbone of blockchain operations. #2 – Permissionless and trustless applications of traditional business models will spearhead the maturity and mainstream adoption of Web3 When bad actors can anonymously influence decision-making, it’s more difficult to build on the Web3 standard. They’ll have no accountability, low barriers to entry, and a lack of due diligence. 

 

This independence in the model presents several security and privacy challenges. Recommended: Swedish Library Harnesses NVIDIA to turn Library Archives into AI Training Data Transaction information on the blockchain is available for everyone to read, but permissionless blockchains allow any user to access this data. Malicious actors can use this opportunity to reverse-engineer and study the behavior of user addresses, leading to even more attacks in the future. Permissionless blockchains may expose sensitive user information to bad actors, which may tarnish its reputation. 

 

This then would drive legitimate users away from the platform leading to business redundancy. #3 – Usage of artificial intelligence (AI) in Web3 products will be the driving force behind decentralization of control and autonomous decision making by blockchains. AI can improve user trust and experience in Web3 applications by playing a pivotal role to drive consensus among application users. Raw data from models can be used to extract valuable insights and drive business strategies towards more economically favorable outcomes. Wallet addresses on a blockchain cannot be easily mapped to physical users for verification, making it crucial for Web3 organizations to respond to and remediate threats before any adverse impact. This sets the tone for predictive analytics, allowing fraudulent activity to be predicted based purely on users’ past behaviors. 

 

Overall, Web3 remains an evolving business landscape, but whilst the allure of new technology will bring in plenty of investors, its volatility also attracts plenty of cyber actors. Businesses would do well to invest in their own security measures so that, no matter what changes or cyber threats emerge, they can always proactive and a step ahead of any potential malicious activity or revenue loss. AI ML Insights: How To Fast-Track AI and Machine Learning With New Automation Technologies [To share your insights with us, please write to sghosh@martechseries.com] 

 

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