Demand is fragmenting faster than most growth models
How companies can identify emerging demand pools, changing customer economics and new sources of willingness to pay.
Read articleRelated macro
Articles
How companies can identify emerging demand pools, changing customer economics and new sources of willingness to pay.
Read articleHow companies can redesign roles, skills and capacity around the work that AI should automate, augment or leave to people.
Read articleFocus
EVs, software-defined vehicles and autonomy are shifting competitive advantage toward computing, architecture and continuous product evolution.
Public agencies are deploying AI broadly while evaluation, procurement discipline and accountability remain uneven across government systems.
Strategic challenges
The challenge is capturing AI and digital-asset efficiencies while managing concentration, cyber exposure and increasingly synchronized markets.
The challenge is balancing deployment, exits and investor distributions when traditional realization routes remain uneven.
POV
Connectivity may look strategically unexciting, but moving into lower-margin technology services is not automatically a better business.
Faster payments and programmable assets matter only if users and regulators believe the infrastructure can survive stress.
Strategic impact
Grid access, on-site generation and storage increasingly determine location economics as AI-driven computing demand expands.
Better data and automation can change operating economics, but only where legacy systems and risk governance can support scaled deployment.
What we observe
Copilots can improve the product while simultaneously undermining seat-based economics by reducing the human labor using it.
Broad stock increases protect service temporarily but can destroy working-capital productivity when demand and supplier risk vary by category.