Case studies in Agentic and JPM Kinexys

Key Themes

1. Value exchange requires a commercial construct such as a contract, marketplace agreement or commercial network.
2. Tech is enabling fragmentation both within an organization and across domains with finer-grained access to services (ex APIs), faster settlement (ex blockchain), immutable digital representations of physical world goods (ex NFT), digital trust and assertions (ex W3C Verifiable Credentials), …etc.
3. While the tech is progressing at light speed, the real battle surrounds the structures, incentives and politics for how value is exchanged, and risk is assumed. 
4. This atomization of products, services and organizations has created new opportunities for value orchestrators. For example, what if the battle for AI and Agentic Commerce is not about LLMs efficacy, but about enabling consumers to choose the best agent and permission it from their phone (ex Apple). 
5. Free and Open are great tech models, but terrible business ones (ex Open Banking). Fragmented voluntary Agreements in Web3 and Agentic Commerce spaces struggle to scale due to high transaction costs associated with establishing bilateral trust.
6. We are in a flux period where incumbent marketplaces and networks will dominate.  For example, there is little prospect for OpenAI to disrupt Google across 7B+ Devices, 3B+ consumer accounts, GC, Advertising, Analytics, Consumer/Enterprise Services. While the buzz of “on chain” finance is loud, application of DLT in closed private blockchains is driving the majority of growth by bringing new efficiencies to established businesses (JPM Kinexys). 
7. While alternative “federated” and decentralized models are possible, their core challenges surround economics and governance. Who owns the end-end risk?  Who manages bad actors or system flaws? Where is the commercial agreement that assigns risk? 
8. The next 10 yrs will NOT be a uniform movement toward one single future, but a fragmentation of how value exchange happens. For example, how identity is handled in Agentic commerce will depend on WHO owns the risk for the transaction (merchant, bank, PSP, Platform, Consumer)?  
9. At the consumer end, I see mobile platforms acting as the controller/orchestrator for trusted interaction across healthcare, retail, government, agentic … etc. I wouldn’t count Apple “out” of the AI race as they may assume the consumer interface role for “everything”.
10. Kinexsys Case Study – Closed network, strong governance, massive scale.