By james youngco-founder Collab.land
Recent breakthroughs in artificial intelligence have ushered in a new era of automation and content creation, but coordination across organizations remains a highly manual and often opaque process. This is about to change, with AI poised to play a huge role in streamlining interactions between various organizations – from legacy businesses to Decentralized Autonomous Organizations (DAOs).
AI tools, paired with information about specific on-chain activity, community sentiment analysis and hard-coded organizational goals, will be able to automatically facilitate a wide range of partnerships and other formal agreements in a trusted yet transparent manner . And while new, socially impactful technologies inadvertently introduce new questions around policy and regulation, there are many reasons to be cautiously optimistic.
identifying new opportunities
One of the major advantages of AI is its ability to analyze large amounts of data and identify patterns and correlations that are not easily visible to humans. In the context of organizational synergy, AI tools can be used to help identify potential organizational synergies based on a mix of privately-encrypted and publicly available data on market trends, customer behavior and business performance.
Within a Web 3 setting, these tools can derive additional information from analysis of on-chain activity, in-app community sentiment, and other relevant data points. In other words, you don’t need a human-readable universal index for The DAO to identify potential partnership opportunities using insights from AI-synthesized on-chain activity. And for privacy-focused organizations and communities, this data can be encrypted or otherwise protected while still being usable by AI.
In other words, AI can enable organizations to identify partnership opportunities that may have been overlooked using traditional methods, and to make informed decisions about which partnerships to pursue. This is especially helpful in emerging, fast-moving industries that lack clear industry leaders and standards, but is ultimately beneficial to any organization wishing to collaborate with an outside party. Right now, companies can only partner with organizations they already know, but AI development is already at a stage where businesses can replace their old business development routines with low-cost automation tools.
streamline operations
The cost of coordination is not limited to the search – once a business or DAO has identified a potential partner, it must conduct proper research, negotiate an agreement and execute the deal. AI can help streamline all these processes.
For example, AI can help streamline the negotiation and execution of cross-DAO agreements such as co-branded marketing campaigns and other formal partnerships. By automating some of the tasks involved in these processes, such as financial due diligence, legal compliance and performance tracking, AI can reduce the time and cost of organizational collaboration while ensuring trustworthy and transparent transactions. Eventually there will be AI-powered smart contracts that can automatically enforce cross-DAO partnership terms without the need for intermediaries or manual oversight, and I know there are developers working on this already.
This is particularly beneficial for complex arrangements such as the above M&A agreements, which currently require entire teams of highly paid advisors and lawyers. Ultimately, the goal is not to replace manpower with automation – it is to enable open collaboration based on publicly verifiable logic, and free up more human capacity for open-ended value creation rather than routine, for-hire tasks. To do.
setting concrete, measurable goals
Organizations will only be able to harness AI’s full potential if they orient their businesses toward concrete, measurable goals. This, incidentally, is something every organization should be doing anyway – even if they choose to use AI coordination tools.
AI is increasingly capable of understanding open-ended statements and turning them into empirical objectives and key results. But there should be no room for ambiguity and misinterpretation when it comes to inter-organizational collaboration, especially if many processes will be automated. This means that the best approach for business leaders and DAO committees is to establish clear organizational goals that their AI tools can adapt to without the need for provisional assumptions.
In other words, AI tools enforce a certain clarity of purpose throughout the organization. By analyzing hard-coded organizational goals and other relevant data points, AI can help businesses, nonprofits and DAOs identify potential partners and negotiate agreements that benefit all involved parties. This could lead to a more open and collaborative business environment that is based on publicly verifiable logic rather than subjective backroom deals.
turbocharging innovation
The reduction of multi-party coordination costs is critical to unlocking new forms of collective experimentation and value creation. Substantial costs can be saved and revenue can be created by abandoning today’s manual business development approach in favor of AI tools that make the entire collaborative process more seamless and efficient. Once the AI-powered analytics tool identifies overlapping interests between different organizations, it is a matter of manually approving or acting on the most beneficial partnerships in a way that minimizes cost and friction.
And while these AI tools can be used to benefit any type of organization, ultimately the strongest business cases can be built around cross-DAO collaboration. The possibilities are endless – medical research DAOs will eventually be able to use AI-powered tools to collaborate with other DAOs with complementary research agendas or data sources. Decentralized VC funds can invest in new startups based on transparent performance metrics and product synergy across their entire portfolio. And by analyzing market trends, user behavior and other data points, AI-powered liquidity management tools collaborate across multiple DeFi DAOs with complementary assets and user bases to increase overall market liquidity and re-risk investor positions. Will be able to do.
In an ideal world, every collaboration between multiple organizations is greater than the sum of its parts. While understandably this is not always the actual case, it will increasingly become true. Relative to many other AI use cases currently being debated, there is little downside to AI tools that make it easier for organizations to work together based on convergent goals, complementary capabilities, or shared resources. It remains to be seen how the full range of AI-powered tools will continue to evolve and be deployed – but when it comes to cross-organisational collaboration AI may be just what we need to turbocharge human value creation .
About the Author
James Young is the founder and CEO of Abridged Inc., the makers of Collab.Land. James has founded and grown web-based companies since the early 2000s. He was the first lead developer for Zynga’s game FarmVille, and has served in previous roles as a software developer and chief architect. An early crypto community member, James wrote a white paper on token-curated registries in 2017, was a co-creator of the Moloch DAO framework and a co-convenor of MetaCartel.
James is proud to be involved in the development of the Internet by empowering individuals through digital ownership. In 2019, he co-founded Abridged, the creator of Collab.Land. When he’s not thinking about crypto, James’ hobbies include working on other emerging technologies, as well as working/exiting.
The views and opinions expressed here are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
