AI Is a Multiplier - Architecture Determines the Outcome
Hiring developers, companies want better results at lower cost. Can AI alone resolve this or do you still need skilled developers?
Let us review the latest MIT report on this subject area (link in the comments), It strikes at the executive summary - “Despite $30–40 billion in enterprise investment into GenAI, this report uncovers a surprising result in that 95% of organizations are getting zero return”
Why would MIT say that?
““When you assign programmers to work effectively with AI, you are not replacing them — you are promoting them to a software architect.””
The answer is further in text “ these (AI) tools primarily enhance individual productivity, not P&L performance.” As our reflection on this we quote our AI lab lead - Alex M: “When you assign programmers to work effectively with AI, you are not replacing them — you are promoting them to a software architect.”
Think about hiring a labourer to refurbish your house. You would not let them build unreliable house just because they are using modern tools.
What is really happening when AI constantly update the codebase inside your big SaaS model?
Main weakness is not a developer but a lack of engineering
Giving AI too much you get an artist lyric in place of architect solid. MIT says “The core barrier to scaling is not infrastructure, regulation, or talent. It is learning. Most GenAI systems do not retain feedback, adapt to context, or improve over time.”
Better quality. Faster delivery still requires skilled professionals. A developer truly ready to work with AI is not only a programmer, but also a BA, solution architect, QA advisor, and internal auditor. Should you allocate fewer engineers to work with AI?
And more importantly AI increases individual productivity - but without architectural ownership, it does not improve business performance.
Ref: Ai Report 2025
