Logicalis-CIO-Report-2026 - Flipbook - Page 17
infrastructure limitations (84%). These are
not minor operational issues, they shape
whether AI can ever scale.
Without suf昀椀cient skills, AI remains
dependent on a small number of
specialists. Without robust data
foundations, outputs remain dif昀椀cult to
trust. Without scalable infrastructure,
success remains localised. Together, these
weaknesses prevent AI from becoming
an organisational foundation rather than
a series of projects.
What the research suggests is that
AI maturity is less about technology
and more about organisational
design. Scaling AI requires the same
things that scale any enterprise
capability: standardisation, governance,
accountability and measurement. It
requires clarity about who owns systems
once they move into production, how
performance is monitored, and how risk is
This is why the gap between con昀椀dence
and capability matters. Con昀椀dence
re昀氀ects optimism and momentum.
Capability re昀氀ects discipline and
readiness.
For CIOs, the challenge is to turn early
success into something more durable.
The real work now is not proving what AI
can do but making it reliable enough to
be scaled with con昀椀dence to deliver a net
business bene昀椀t.
Logica Lis gLoBa L cio R EPo RT 2026
absorbed.
17
