Comment: At the Very Least, AI is a Force for Deflation

Each
of
these
ground-breaking
waves
of
innovation
significantly
impacted
economies,
societies
and
culture
–
and
generative
artificial
intelligence
(AI)
promises
to
be
the
next.
But
how
exactly
it
will
impact
our
economies
is
dependent
on
a
number
of
intersecting
factors,
from
policy
and
regulation
to
competition
and
the
pace
of
innovation
itself. 

For
a
start,
there
is
the
big
question
of
how
much
infrastructure
will
be
required
to
facilitate
AI’s
implementation
compared
to
previous
innovations.
The
physical
footprint
of
AI
may
appear
small
in
comparison
to
industrialised
cities,
rail
networks
and
steel
plants.
However,
the
production
and
advancement
of
semiconductor
technology,
data
centres
and
(clean)
energy
production
required
to
drive
AI
comes
with
a
large
cost.

Furthermore,
the
spread
of
generative
AI
could
be
aided
by
mass
recursive
learning
and
even
AI
itself
providing
insights
for
a
more
efficient
roll-out.
Again,
however,
this
will
at
least
in
part
depend
on
the
regulatory,
governmental
and
societal
reactions
to
its
introduction. 

AI
is
the
Next
History
Lesson

History
teaches
us
technological
advances
have
boosted
productivity,
reducing
the
need
for
labour
in
certain
sectors,
but
simultaneously
creating
jobs,
and
often
in
new
areas.
The
movement
from
agriculture
to
manufacturing
is
a
textbook
example.

However,
historic
shifts
have
repeatedly
moved
large
sections
of
the
population
from
abject
land
poverty
to
more
industrialised
penury.
That
in
turn
has
led
to
material
changes
in
the
structure
of
society.
More
recently,
technological
gains
have
led
to
deindustrialisation,
leaving
heavily-concentrated
impacts
in
some
areas.   

Insofar
as
we
consider
AI
to
be
a
material
positive
supply-side
boost,
economic
theory
suggests
it
should
create
disinflationary
pressure.
The
actual
impact,
however,
is
likely
to
reflect
institutional
frameworks.
Productivity
gains
mean
producers
can
produce
more
for
less.
But
whether
these
gains
are
passed
on
to
consumers
through
lower
prices,
or
retained
as
profits,
will
depend
on
the
scale
of
competition
producers
face.

The
degree
of
the
eventual
industry
concentration
may
also
be
a
function
of
the
technology
itself.
If
AI
develops
quickly,
it
may
be
easier
for
its
developers
to
quickly
expand,
ensuring
a
dominant
position
to
exclude
later
competition
–
a
more
monopolistic
outcome.
However,
if
it
develops
slowly,
it
is
likely
progress
would
not
be
limited
to
one
initial
developer,
creating
a
more
competitive
(and
likely-disinflationary)
landscape. 
 

Can
Governments
Control
AI?

Plausible
widespread
disruption
to
labour
markets
could
have
a
major
impact
on
governments.
In
previous
technology
waves,
governments
have
played
an
active
role
in
boosting
the
education
of
the
workforce.
They
may
have
a
further
role
to
play
this
time
by
providing
re-training
opportunities
for
workers
displaced
by
AI.

And
given
AI’s
far-reaching
potential,
governments
are
already
focusing
on
regulation.
This
will
become
more
urgent
if
AI
develops
quickly
or
in
a
network
that
allows
for
monopolies
or
greater
concentrations
of
market
power.
The
question
would
then
be
how
effectively
it
addresses
such
complications
and
how
much
it
might
delay
or
divert
progress.      

The
ultimate
impact
on
growth
is
perhaps
most
difficult
to
fathom,
however.
A
material
positive
supply
shock
should
lift
the
trend
rate
of
growth
for
the
global
economy
and,
all
else
being
equal,
quicken
expansion
across
many
sectors.
The
most
immediate
beneficiaries
are
likely
to
be
economies
most
involved
in
the
development
of
AI,
including
the
US,
Japan
and
South
Korea
–
leaders
in
the
semiconductor
industry
–
but
also
those
able
to
gain
the
most
from
implementing
AI.
That
includes
Europe
and
the
UK.

AI:
it
Could
go
Either
Way

Generative
AI
promises
a
new
technological
revolution,
and
one
which
could
be
as
far-reaching
as
previous
technology
breakthroughs.
That
is
a
truly
exciting
prospect
and
suggests
material
change
to
both
society
and
economies.
But
history
suggests
these
changes
roll
out
over
relatively
prolonged
periods
–
typically
over
a
half
a
century.

Previous
waves
also
indicate
these
transitions
deliver
significant
productivity
and
growth
gains,
but
also
material
disruption.
The
way
AI
hits
over
the
coming
decades
will
be
a
product
of
the
institutional
choices
we
make
as
societies
and
how
we
co-ordinate
globally.

This
may
materially
boost
productivity,
raise
living
standards,
reduce
inequality,
and
put
rocket
boosters
on
the
fight
against
climate
change.
But
such
outcomes
are
not
guaranteed.
There
are
several
challenges
to
overcome
first
to
avoid
alternate
and
less-universally-beneficial
outcomes
occurring.

David
Page
is
head
of
macro
research,
core
investments,
at
AXA
Investment
Managers

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