Many organisations are accelerating the rollout of generative AI tools, but most are struggling to turn pilots into sustained business impact. According to General Assembly, the core challenge is not technology adoption but the lack of leadership-led strategy, clear AI literacy standards, and workforce alignment.
Speaking to iTNewsアジア, Ryan Meyer said many companies confuse AI adoption with simple tool deployment. As a result, initiatives stall as fragmented proof-of-concepts rather than scaling into strategy.
Meyer identified the lack of executive ownership as a major barrier to deeper transformation. When AI treated as an IT rollout instead of a core business capability, it lacks strategic direction and sponsorship, leading to siloed initiatives, limited adoption, and weak returns. Without clear leadership, AI tools are frequently bolting onto existing processes instead of reshaping how work is done across functions.
He also warned that AI adoption is often outpacing governance. While leaders do not need deep technical expertise, they must understand AI’s risks and limits.
As a result, simple, repeatable governance is essential to manage risk while moving fast.
Another obstacle is the absence of consistent AI literacy standards. Expectations often differ between executives, HR, and technical teams, resulting in fragmented training and unclear performance benchmarks. Meyer argued that literacy should define by role, not theory. Executives need governance and ROI awareness, practitioners require hands-on skills, and frontline teams need practical guidance for safe daily use. He pointed to UOB’s bank-wide AI reskilling programme as an example of structured workforce enablement.
Ultimately, Meyer said successful AI transformation is measuring by operational outcomes, not pilots. Organisations that treat AI as a continuous capability—grounded in leadership accountability, skills, and governance—will be better positioned to extract long-term value from their investments.
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