How AI is Shaking Up Web3 Development

‍The times, they are a-changin’. Industry pundits forecast a majority of the world’s leading software solutions will be rewritten entirely with artificial intelligence (AI) and machine learning (ML) technologies as their nexus.

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And, at the risk of overhyping what many have already said about AI’s potential – the potential to create trillions of dollars in global economic value will cause waves of disruption across industries. Global corporate services firm PwC certainly seems to think so, forecasting that AI will bring in as much as US$16 trillion to the world economy by 2030. Talk about no cap.

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AI’s path of disruption is sending shockwaves across technologies, and web3 is no exception – even as the latter continues evolving through its birth pains. Namely, the ebbs and tides of the crypto sector’s inherent volatility, and yet the technology’s immense potential we’ve just barely scratched. 

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The potential of AI in web3 is tantalizing, and it seems as though both major technological shifts present interesting synergies that will come to dominate the web3 development meta in the coming years. Just in time too, as web3 itself shakes itself out of its doldrums and weeds out the real use cases from the pies in the sky – as the industry whistles in the dark for the next narrative, the next chapter as it navigates itself out of last year’s existential crisis.

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That said, how exactly can AI shake up web3 – in particular, the dev side – in the coming years? What makes them such a tantalizing match? What role will AI play in the ever-changing world of web3? The next paragraphs will explore these topics in further detail.

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How Will AI Benefit Web3?

AI is in the middle of every tech-related conversation just as web3 was a couple of years ago – but it has become a lightning rod for conversation in the web development field. Some dread the loss of human ingenuity and creativity, or worse – their livelihoods – as the next logical step in technology threatens to make conventional, too-big-to-fail business models redundant at a flick of a wrist. 

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But that’s just par for the course for disruptive technologies like AI and web3. Before we discuss how AI benefits web3, let’s start off with a couple of definitions. 

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In a nutshell, AI refers to the simulation of human cognition and intelligence by computer systems. AI systems generally work by taking in massive amounts of data, which they then deduce patterns and correlations and use them to forecast future states. 

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Web3, on the other hand, has been touted as the next iteration of the internet – one that has been marketed as a new, better, decentralized version of the internet as we know it. At the very heart of web3 lies distributed ledgers, cryptocurrencies, NFTs, and DAOs, among other innovations that devolve the power and data ownership from the monolithic conglomerates that support the present internet’s infrastructure back to the people. 

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AI and web3 are firmly among the leading trends in tech, and machine learning will most likely play a key role in evolving AI-enabled web3 apps. 

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And while it’s definitely true that the bloom is off the rose as far as web3 and the metaverse are concerned, as the broader crypto industry recovers from a brutal 2022 – and industry giants scaling back enterprise blockchain development – 0% of the ideas that the web3 movement took up the cudgels for are any less valuable or relevant. 

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Nevertheless, AI and web3 – particularly when it comes to development – are seemingly a match made in digital heaven. We think it will drive further innovation in the space and provide that narrative web3 so desperately needs to get it out of the doldrums of hyper-financialization – here’s how.

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AI and Web3: A Match Made in Digital Heaven

It’s a foregone conclusion: as web3 begins to evolve and build towards its vision and AI unlocks the next wave of innovation across sectors, we will continue seeing exciting new products and services taking the best of both worlds. Here’s how AI will drive innovation in web3 in the coming years.

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AI's role in simplifying complex tasks

One of the most important innovations that AI will bring is its pivotal role in simplifying complex tasks and reducing the margin of human error to virtually nil. This bodes well for developers, who could save time on performing rote tasks and create better-quality code in the same timeframe – exponentially increasing their productivity and allowing them to focus on more complex, challenging, or priority projects with the most impeccable precision.

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For instance, blockchain engineers will no longer need to spend oodles and oodles of time on testing and debugging because AI will have already taken care of that part with zero backlog and optimal accuracy. This will hasten their dapp or service’s time-to-market immensely, creating web3 solutions that are ready to use after writing.

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Web3's focus on decentralization and user empowerment

AI’s disruptive potential plays well with web3’s core tenets of decentralization, trustlessness, verifiability, censorship resistance, and, most importantly – user empowerment.

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We will likely see AI-enabled decentralized applications incorporating ML and blockchain technology altogether – and the creation of such will spur the development of community-owned decentralized AI models, rather than by OpenAI or other centralized entities.

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AI could be the unlock that will democratize the internet back to the people who wouldn’t have gained access to AI-enabled tools to fend off the centralization by tech giants.

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How AI and web3 complement each other

Web3 is built on distributed ledger technologies (DLTs), which serve as the bedrock of web3. These open, decentralized, and distributed ledgers enable immutable, secure and transparent transactions and trustless interactions between parties through self-executing smart contracts wherein contract terms are “baked” into the code.

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AI is a complementary technology that can significantly enhance web3 functionality by enabling the creation of more robust, data-driven, and sophisticated decentralized apps. Moreover, AI can also be harnessed to boost UX on web3 by using natural language processing (NLP) and machine learning.

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Advanced AI algorithms are evolving by the day and capable of analyzing and parsing through copious amounts of data in real time – and in doing so, allow web3 dapps to predict trends, user behaviors, and other key performance indicators as they see fit.

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Making Web3 Development Faster and Easier

If you work in traditional or web3 development, then you will have most likely had some conversations with colleagues about how AI and machine learning spells curtains for developers all over the world – in the sense that they would be out of jobs within the next several years.

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On the contrary, the fears are largely unfounded – web development jobs aren’t going away anytime soon. Instead, AI is here to make the whole process of development – web2 or web3 notwithstanding – faster and easier so developers can focus on more critical or more delicate tasks.

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Speeding up the coding process with AI

AI will help accelerate growth for web3 projects that may not necessarily have the same budgets and get their products and services to market in record time. AI has the ability to write and debug code, not to mention write programs, assist in producing documentation and locating/identifying snippets of code.

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We’ve seen this with OpenAI’s ChatGPT. A potential use case for AI in web3 is employing AI tools like ChatGPT to create smart contracts. While both technologies are in their embryonic stages, that hasn’t stopped users from testing AI tools to create, audit, and find vulnerabilities in smart contracts to promising results.

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OpenAI has since debuted Codex, an AI tool that translates human language to code, making it so that literally anyone and everyone can create their own programs without necessarily having extensive coding knowledge – which will open the door to a deluge of innovation in the future.

Finding and fixing bugs in a snap

We already know that automation is one of AI’s key benefits because it can automate routine coding tasks that free up developers to focus on the bigger things. And one task developers could definitely use AI for is locating and debugging the kinks out of smart contract code, reducing the time it takes to create decentralized apps and services. 

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With AI, developers no longer have to spend hours on end sifting through code to find and fix bugs – reducing another pain point for web developers on both sides of the traditional web/web3 fence.

Enhancing User Experience in Web3 Apps

As we mentioned earlier, AI in web3 opens the door for developers to focus on improving UX – a long-standing hurdle for mass web3 adoption. AI-enabled chatbots, for instance, can go a long way in providing bespoke, real-time customer support for less technically-inclined individuals or new entrants into the space

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Moreover, AI can be leveraged to suggest content that’s contextually relevant to a user’s preferences, behavior, and interests. We can further drill down on this by using AI to create a personalized, unique customer experience using data insights from user behaviors.

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Accessibility is a critical aspect of UX, and AI can be implemented within web3 apps to provide real-time text translations and provide alternative text for sight-impaired users for better localization for users in different regions.

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Personalizing web3 apps with AI-generated content

AI-generated content is the next evolution of content generation techniques, where AI is used to create digital content based on prompts in an automated or semi-automated manner.

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Content generated by AI has featured prominently ever since ChatGPT and Dall-E first sparked this ongoing wave of interest in the technology – and such content can be further leveraged to personalize and improve UX on web3 apps which have long been criticized for the lack thereof of the latter.

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As AI models continue to evolve, it is but a matter of time before more potent, more knowledgeable AI models produce strictly better content across all formats, and ultimately boost user experience for the billions of users that web3 seeks to onboard.

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Improving security and privacy in web3 apps with AI

The intersection of AI and web3 can also boost UX by introducing improved privacy and security in web3 decentralized apps. AI can be leveraged to detect and remediate potential security incidents, repelling cyber attacks and protecting the veracity and integrity of the blockchain.

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For instance, decentralized finance (DeFi) protocols can harness AI to detect and flag any suspicious, fraudulent, or otherwise anomalous transactions based on machine learning algorithms that may indicate potential or active security threats, and subsequently advise respective teams to mitigate them.

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Boosting Decentralized Governance and Tokenomics

Governance is one of the fields AI and web3 definitely intersect. AI can be harnessed to scale distributed ledgers and/or create new paradigms for decentralized governance, fairer tokenomics and incentives, greater accountability, and more intelligent decision-making.

Streamlining decision-making with AI algorithms

Thanks to AI’s machine learning algorithms, they can benefit DeFi platforms by pulling data on past actions and events in order to create better, more accurate predictions about the outcomes of a particular event. Then, the protocol can use said predictions to make better-informed decisions based on cold, hard data.

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Moreover, AI can also draw from data analytics and crunch the numbers to detect voting trends and behavioral patterns members exhibit within a particular company, organization, or DAO – which helps build confidence and trust among its members and that every decision is done fairly and transparently. That all leads to smarter, more streamlined decisions.

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Creating fairer and more effective incentive models using AI

Likewise, streamlined decision-making can be a prelude for AI to help promote fairer, more sensible, and better incentivization models for teams and members of a particular organization or web3 protocol. Again, by using AI to pore through the data and detect patterns that can be used to create a more equitable token and incentive distribution beneficial to all – as indicated by AI.

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And that’s just off the top of our heads – as both technologies further mature, there will certainly be more novel, interesting AI applications in web3.

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Conclusion

It’s a fools’ errand to create a comprehensive list of how AI and web3 will intersect in the future. Nobody can say for sure as to how AI’s emergence and its interaction with web3 will look like in the near future.

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One thing is for sure, however: web3 and AI aren’t going anywhere, and we’re all richer for getting a sneak preview of how these disruptive technologies are changing the way we build, connect, and interact with the World Wide Web as it evolves. We’re seeing the fruits of their collective work in the realm of web development – and it will be exciting to see how AI translates to web3 in that regard.

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While AI isn’t without its flaws, as has been demonstrated in the saga of web3 – the trend is promising, as all signs point to a more democratized, more accessible, and more efficient web development scene that both novice, experienced, or transitioning web3 developers and users alike over the long haul.

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