WHY CIOS MUST ABANDON THE‘ OSTRICH STRATEGY’ TO UNLOCK AGENTIC AI
Ascendion CTO & Global Head of Solutions Vaibhav Vora says CIOs risk falling behind by remaining stuck in AI experimentation and must embrace agentic AI as a core driver of productivity, innovation and Digital Transformation. n the late 19th century, the
I transition from gas to electricity began to reshape how societies, workplaces and cities were organised. But its introduction was not smooth sailing and incurred much initial scepticism from business owners that the costs and complexity of implementation would outweigh the benefits.
Retrofitting factories and offices required extensive rewiring and new generating equipment, often forcing organisations to overhaul infrastructure that was already functioning perfectly well.
As a result, early adoption was frequently cautious and piecemeal. In fact, one newspaper in 1880 noted of local factories’ attempts at converting to electricity that,“ The arrangements thus far are quite experimental.”
This infrastructural overhaul is likely familiar to CIOs, who are undertaking a similar shift with the development of AI. The technology is no longer just improving existing processes but, through autonomous agentic systems, has the potential to transform how organisations operate at a fundamental level.
But too many CIOs are dragging their heels in the experimentation phase and adopting the‘ Ostrich Strategy’.
They are ignoring the challenges and opportunities AI systems present and instead blindly clinging to old processes and assumptions.
Within a few years, the organisations that bury their heads in the sand to the transformations now underway could find themselves struggling to compete. By contrast, CIOs who act early and seize on the potential of agentic AI to power business operations could gain a powerful advantage in speed, productivity and innovation.
The agentic AI revolution
An excuse many CIOs use for evading the challenge posed by AI is that the technology is not ready – it is not mature, scalable or reliable
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