Besides holding the power to change rules suddenly, governments control access to a range of
valuable resources. Past experience suggests these
resources can be allocated in ways that reflect political favoritism rather than competitive allocation.36
As a result, capital, labor, and public funds can be
directed toward firms that are politically connected
rather than those that create the greatest economic
value, weakening institutions in the process.37
A recent example is Indonesia’s Pusat Data
Nasional Sementara (Temporary National Data
Center) project. Investigators found that a small
group of opportunistic officials misused their contracting power to rig the tender process to benefit Lintasarta, a subsidiary of Indosat Ooredoo
Hutchison group, in exchange for kickbacks. As
a result, the state lost an estimated 140.8 billion
rupiah.38 Checks and balances held, however, and
the officials were held accountable. The example
provides a cautionary tale; if checks and balances
fail and transparency is lacking, such conduct
may evolve into systemic rent-seeking dynamics. Research from several countries has shown
that politically connected firms tend to survive,
yet industries with a higher share of such firms
exhibit lower growth and productivity.39 Over
time, such misallocation reduces market dynamism, crowding out firms that would have generated more value. This process could diminish the
broad-based gains AI could have generated and
could concentrate the greatest gains in the hands
of those who already hold power.
Beyond resource allocation, there is also the
risk of firms being drawn into the exercise of
state power. Many technology companies collect
large volumes of personal information; governments increasingly request access to such data.40
Although there may be legitimate security or law
enforcement reasons for such requests and companies have safeguards in place, the rising frequency of these requests normalizes this access
mechanism—which may be exploited to further
the state’s power over its citizens. Ultimately, the
safeguards rely on mutual restraint—with companies pushing back on overreach and governments
using such access judiciously. This equilibrium
can easily go either way when there is a change in
corporate policy or government.
Although the three outcomes discussed are distinct, they all stem in part from the imbalance of
power between corporations (which supply the
technology) and states (which depend on these
technologies but are responsible for regulating
them). Reducing or eliminating this imbalance is
crucial to ensuring that countries do not let the
opportunities for AI to deliver positive outcomes
for their economies slip away. Part 3 of this Report
discusses policies to avoid such outcomes.
Dynamics between
corporations and individuals:
Market structure determines
who gains from AI
Unlike competition between states or contested
bargains between governments and firms, the
power imbalances between firms and individuals
in the AI economy emerge from features of the
AI value chain itself, such as large up-front investments, network effects, data feedback loops, and
spillover effects that standard market mechanisms
cannot address.41 These characteristics lead to
market concentration that benefits capital owners
more than users and workers. Treating this concentration as a well-understood market failure rather
than an inherent characteristic of the AI value
chain helps clarify which policy tools can address it.
Data advantages lead to durable
market power that benefits AI
capital owners more than users
AI systems improve with use. Each user interaction generates data that can be used to train better
models; better models attract more users; more
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