What should software consultancy companies do in the AI transformation?
They have a special position in the software ecosystem and AI-driven data-polarization which has traditionally been based on the scarcity of experts. So, when the AI-transformation is needed across the board, surely the scarcity of AI experts will provide a convective updraft for the software consultancy companies with the AI experts?
Perhaps. But there are many challenges.
First of all, classical software consultancy houses are typically at a disadvantage in attracting the best AI people. The compensation isn't competitive when the domain is capital-intensive and you're structured into a labor-intensive setting. For large capital concentration, you want to hire the best people no matter the cost because otherwise your capital doesn't produce value.
There is also the Claude Code effect where businesses won't contract with consultancy companies for small non-core projects because AI can do those as well.
In AI-driven data-polarization, the data is created by applied AI companies, and the models by foundation model providers. Both of these positions are defensible in the medium-term future. But is a position based on talent scarcity defensible? When that talent is hard to attract as well?
I think software consultancy houses should really re-evaluate their strategy. They should focus on AI and on lifting the capability level of specific domains by sharing data management and refinement practices. With that, they become capital-intensive in a way because data is capital, and become able to attract talent, and sit in a defensible position in the ecosystem.
Without this AI and data-focus, the software consultancies will wither against Claude Code eating their bread, talents choosing to go elsewhere, and the position being inherently indefensible in the coming AI-driven, data-polarized economy.