As we complete almost the first 10% of the year, it has become clear that AI and Web3 are stand out marketing and technological trends. As a result, it is then becoming even clearer that marketers are having to decide how to split the budgeting pie between these two things.
For most brands, AI and Web3 are fascinating innovations but are not yet must-have components of a marketing strategy, such as social media. This means they require testing and plenty of caution to see how—or whether—they make sense to use. But advertising is a fickle budget, especially with regard to the more experimental efforts. Amid economic uncertainty to boot, some brands will have to choose between investing in Web3 or AI.
Meanwhile, against the backdrop of a possible recession, brands are already cutting costs and having to make tough decisions over where to invest ad dollars. Their next choice may very well impact innovation budgets and pit AI against Web3. So how should marketers reconcile the two spaces? Are they competing technologies or complementary?
AI and Web3 have very different origins and use cases in advertising. AI has been an integral feature of ad tech for over a decade, enabling recommendations, powering programmatic ad buying and structuring customer data. Web3, on the other hand, is less of an automation and more a set of principles, which are manifested in technological tools. NFTs, DAOs and blockchain democratise digital ownership, participation and record-keeping.
Nevertheless, I would argue Web3’s reputation hosts more taboos and its ethics are very different to that of AI. Where Web3 promotes decentralisation, the AI space promotes a centralised reality which is currently run by sizable, for-profit companies supported by even bigger ones. Microsoft, for example, just invested another $10 billion—on top of $3 billion in previous investments—in ChatGPT and DALL-E creator OpenAI.
Furthermore, there are already numerous ways that marketers are using generative AI to their advantage, and the verdict is in: these tools can really improve productivity. Web3, on the other hand, is less obviously useful to advertisers, said Bennett, and is limited to only select brands who have reasons for activating NFTs or engaging crypto communities. Web3 expertise is also harder to source than experts on AI who have been researching the topic for almost a decade.
That isn’t to say, however, that there isn’t potential for the two to work together. Inversely, Web3 tools can help package, personalise and deliver creativity afforded by AI, said Chris McGarry, founder and chief executive of Authentic Artists. The company oversees an AI platform that creates original music, and last year dropped an NFT collection that paired pieces of unique instrumentation with digital avatars—ownable as a single asset.
Something negative the two future facing fields share is that both Web3 and AI are condemned because of their dependence on mass quantities of computing power. Web3 relies on arduous processes like crypto mining, while generative AI can only improve through larger models and datasets. Both of these systems inevitably result in high carbon emissions.
As both Web3 and AI work to hash out their problems, brands will inevitably experience collateral damage in the form of a lack of brand safety.