AI Architecture Mirrors Organizational Structure: Conway's Law in AI
In the rapidly evolving world of artificial intelligence (AI), it's not just the algorithms, data, or model size that determine success. The organisational structure plays a crucial role, predicting AI capability better than technical metrics (Evaluate org charts, not just technology).
The winning AI companies won't be those with the best algorithms or the most data or the biggest models, but those with the best organisations (The winners in AI). A well-structured team can produce coherent AI, while a disorganised one may lead to incoherent results.
One way to escape the constraints of organisational structure is for small teams to adopt minimal structure. These teams, due to their size, can iterate faster and learn faster, compounding their advantage (The advantage of small teams). Rotating people across teams can also create shared context and a more connected social graph, fostering collaboration and innovation.
However, when small AI startups are acquired by larger companies, the innovation gets Conway's Law-ed into dysfunction. The acquired innovation is moulded to fit the acquirer's structure, often destroying innovation in the process (Every acquisition becomes an unintentional lobotomy).
Conway's Law, which states that any organisation that designs a system will produce a design whose structure is a copy of the organisation's communication structure, creates convergent evolution toward organisational monoculture. This monoculture makes innovation impossible (Conway's Law creates convergent evolution).
Companies often copy their competitors' organisational structures, hoping to copy their success. However, this leads to similar structures, architectures, and limitations across the industry (Companies copy competitors' org structures). This homogeneity can stifle innovation and limit the potential for breakthroughs.
To counteract this, organisations might embrace Conway's Law by building explicitly modular AI. By letting each team own their module completely and making organisational boundaries into feature boundaries, organisations can encourage innovation and prevent the creation of technical seams (Organizations might embrace Conway's Law).
A notable example of this approach is Microsoft's Copilot. The development of Microsoft's Copilot involves three main organisations: Microsoft itself, OpenAI, and the teams integrating GPT-4 and Microsoft Graph data. The integration of these parts was completed by the time the Microsoft 365 Copilot was launched and integrated into Microsoft 365 applications such as Word, Excel, PowerPoint, and Outlook. This development is ongoing through 2023 and refined with updates into 2025 (The three main organizations involved in the development of Microsoft's Copilot).
In conclusion, the organisational structure is as important as the technology in AI development. Designing a well-structured organisation can lead to coherent AI, while a disorganised structure can lead to incoherent results. By embracing Conway's Law and building modular AI, organisations can encourage innovation and prevent the creation of technical seams.
Lastly, it's essential to resist the temptation to create AI departments, as they become silos that produce siloed intelligence. Instead, keep teams small and boundaries minimal to avoid creating technical seams. Your org chart is your AI strategy, as no amount of technical excellence overcomes organisational dysfunction (Your org chart is your AI strategy). Your org chart is your AI's mind, as your AI will mirror your organisation whether you want it to or not (Your org chart is your AI's mind).
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