Page 10 - EngineerIT June July Issue 2026
P. 10
AI GOVERNANCE
The invisible gap in artificial
intelligence adoption
Consider a customer service
operation that introduces AI
to improve response times. If
departments follow different
approval processes, maintain
separate information
sources and communicate
inconsistently, the AI cannot
resolve those underlying
problems independently.
It simply processes them
faster and at a greater scale.
The result is often increased
complexity rather than
greater efficiency.
Artificial intelligence depends
on clarity, structure, context
and well-defined processes. It
performs best in environments
where operational discipline
already exists. But many
organisations continue to
rtificial intelligence has rapidly Still, beneath the slowly fading approach AI as though it
become one of the most aggressively novelty and excitement can singlehandedly correct
Aadopted technologies in modern surrounding AI, organisations are flawed workflows, inconsistent
organisational history. Just about every feeling the impact of the new governance practices or
industry is seeing executives under growing reality - that the environments strategic confusion. In
pressure to integrate AI into operational into which AI is being introduced reality, AI may amplify the
workflows, customer engagement, were never operationally weaknesses already present
analytics, governance processes, software coherent to begin with. Therein within an organisation.
development and strategic decision-making. is the invisible gap in artificial
intelligence adoption. This becomes particularly
Boards demand acceleration, markets visible in hybrid environments
reward innovation and competitors As companies increasingly where employees delegate
are moving quickly. No institution aims attempt to deploy AI into work to AI systems, then
to be perceived as standing still while environments where workflows interrupt, override or manually
technological transformation reshapes are poorly defined, responsibilities adjust parts of the process
entire sectors. are fragmented, communication without fully understanding the
is inconsistent and decision- downstream consequences.
making relies heavily on informal Workflows gradually fracture
workarounds. Notably, technology between machine logic
is often expected to compensate and human improvisation,
for institutional weaknesses that and frequently long before
long predate the arrival of AI, but leadership recognises the scale
it can’t. of the problem.
By Dr Mai Moodley
10 | EngineerIT June/July 2026
