AI INFRASTRUCTURE
Hyperscale data centre
The barriers are both technical and deeply human. Poor data readiness remains the biggest stumbling block, especially with unstructured data.
While legacy IT systems create friction – and building multi-disciplinary teams proves difficult. Gartner predicts at least 30 % of AI pilots in 2025 will be abandoned due to poor data quality, weak governance, rising costs or unclear business value.
“ We are writing the playbook for how to be the most AI-enabled, client-focused professional services company in the world,” says Julie Sweet, Chair and CEO, Accenture.
The scaling priority: Walking before running So how do the 8 % crack the code? KPMG’ s research reveals that deploying AI isn’ t enough – businesses need a structured approach and strong foundation to overcome scaling challenges. Its analysis identifies five critical strategies.
Adopt a phased approach: Focus on high‐impact, low‐risk AI use cases first to assess readiness, prove early value and build alignment for scaling.
Build a strong data foundation: Invest in governance, cleansing and integration to ensure quality, accessible
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