Yet adoption is only the first step. The real challenge is impact at scale. Technology alone cannot deliver that outcome. The organizations that are pulling ahead recognize that success depends as much on mindset as on tools. Fragmented architectures and siloed ownership may slow progress, but the deeper issue is how leaders define priorities and how employees choose to engage with AI.
This paper, based on insights from 54 senior data and technology leaders, explores three dimensions where technology and mindset must come together:
Functional Maturity: adoption is advancing unevenly across functions.
AI Readiness: Cloud enables rapid experimentation, but fragmentation stalls scale.
Investment & ROI: Impact isn't just about technology spend. It requires a mindset shift in people and organization.
Together, these perspectives show what it takes to move beyond adoption and develop the mindset required to make AI real at enterprise scale.
Global private investment in AI hit
$150 Billion
Key Findings
Our survey of 54 senior data and technology leaders shows enterprise AI adoption is accelerating, but scaling impact remains uneven. The metrics below highlight where progress is stalling and what is required to move forward.
Functional Maturity
Top 3 functions with traction are technology and efficiency-driven areas such as IT, marketing, and customer support.
lack a primary AI framework, showing fragmentation blocks scale
allocate 10%+ of strategic budgets to AI, yet ROI remains inconsistent
of CEOs are now AI champions, making leadership and talent alignment critical.
Conclusion
Scaling AI Demands Mindset and Focus, Not More Fragmented Tools.
Enterprise AI has moved past adoption. The real challenge is scaling in ways that deliver consistent, measurable value. The barriers are no longer technical; they are structural, cultural, and organizational. Leaders must focus on what truly drives enterprise-wide impact.
Focus on Outcomes.
Success is measured in business results (growth, productivity, and stronger customer impact) not model accuracy alone
Design for Integration.
AI will not scale on patchwork layers. Cohesive platforms, interoperability, and governance are essential for durability
Unified Leadership Vision.
The most effective organizations make AI a shared responsibility across the CEO, CIO, and business leaders, with clear ownership and accountability.
Build Talent from Within.
Develop existing engineers with domain expertise and AI skills. Rely less on pure-play AI vendors and build institutional capability.
Empower People, Evolve Mindsets.
Scaling AI is about skills, standards, and confidence. Leaders must invest in workforce readiness alongside technology deployment.
Contributors
Arvinder Singh
Managing Partner
Utpal Bakshi
Partner
Diana Ying Liu
Managing Director
Shirley Chen
Director
