🎯 The 15% Who Are Winning Big
While most organizations struggle with AI pilots that never scale, a select group has cracked the code. NTT DATA's comprehensive research surveyed 2,567 senior executives across 35 countries and 15 industries between September and October 2025, revealing a stark divide in the business world.
The AI Leaders Advantage:
- 2.5x more likely to achieve over 10% revenue growth
- 3x more likely to reach profit margins of 15% or higher
- Clear AI strategies aligned with business objectives
- Mature operating models with focused execution
According to Yutaka Sasaki, President and CEO of NTT DATA Group, the message is clear: AI responsibility now resides in the boardroom and requires enterprise-wide strategy rather than departmental experiments.
🚀 Strategy: From Side Project to Business Core
The fundamental difference between AI leaders and laggards isn't technology — it's strategic alignment. While average companies treat AI as experimental, leaders embed it into their core business strategy.
What AI Leaders Do Differently:
- Align AI with Business Goals: Every AI initiative directly supports measurable business outcomes
- Focus on High-Value Domains: Target one or two areas for complete AI transformation rather than spreading resources thin
- Create the Flywheel Effect: Early wins generate momentum that attracts more investment and talent
- Rebuild, Don't Bolt On: Redesign applications with embedded AI rather than adding features to legacy systems
As Abhijit Dubey, CEO and Chief AI Officer at NTT DATA Inc., explains: once business strategy aligns with AI capabilities, the most effective approach involves selecting domains that deliver disproportionate value and redesigning them comprehensively with AI at their foundation.
⚡ Execution: The Five Pillars of AI Success
Strategy without execution is just wishful thinking. AI leaders distinguish themselves through five critical execution pillars that transform plans into measurable results.
1. Secure at Scale: Building Resilient Foundations
AI leaders invest heavily in infrastructure that can handle enterprise-scale deployments:
- Scalable and secure technology stacks
- Localized or relocated infrastructure for private and sovereign AI needs
- Proactive elimination of system bottlenecks
- Modern data architectures designed for AI workloads
2. Expert-First AI: Amplifying Human Capability
Unlike companies that view AI as workforce replacement, leaders take an "expert-first" approach. They deploy AI to enhance their most skilled employees, allowing experienced professionals to focus on high-value decision-making while AI handles complex, time-consuming tasks.
This philosophy delivers dual benefits: higher productivity from top talent and better employee retention as workers see AI as an empowering tool rather than a threat.
3. Change That Sticks: Enterprise-Wide Adoption
Successful Adoption Strategies:
- Company-Wide Change Programs: Treat AI adoption as organizational transformation, not IT implementation
- Structured Change Management: Clear communication and training reduce resistance
- Leadership Buy-In: Visible executive support drives adoption at all levels
- Continuous Reinforcement: Regular updates and success stories maintain momentum
4. Governed for Scale: Centralized Oversight
AI leaders formalize governance structures that balance innovation with risk management. This includes:
- Centralizing AI oversight under dedicated leadership
- Empowering Chief AI Officers (CAIOs) with real authority
- Establishing clear accountability for AI ethics and compliance
- Creating frameworks that allow rapid innovation within defined boundaries
Critical Insight: Without centralized governance, AI initiatives fragment across departments, creating security risks, compliance gaps, and missed opportunities for enterprise-wide value creation.
5. Partner-Powered Growth: Strategic Collaboration
Top performers understand they can't build everything in-house. They leverage strategic partnerships with external experts and embrace outcome-based models where partners share both risk and reward.
This approach accelerates time-to-value while bringing specialized expertise that would take years to develop internally.
💡 The End-to-End Transformation Approach
Perhaps the most transformative insight from the research is the power of end-to-end domain redesign. Instead of making incremental improvements across many areas, AI leaders identify one or two critical business domains and completely reimagine them with AI at the center.
Why This Works:
- Concentrated resources deliver deeper impact
- Complete redesign unlocks value impossible through incremental changes
- Clear success metrics and accountability
- Learnings can be replicated across other domains
- Creates visible proof points that drive broader adoption
📊 Industry and Regional Perspectives
The NTT DATA report provides insights across multiple sectors including technology, manufacturing, banking, financial services, healthcare, and consumer goods. While specific tactics vary by industry, the fundamental principles remain consistent.
The research spans 35 countries, revealing that AI leadership isn't confined to traditional tech hubs. Organizations worldwide are successfully implementing these strategies, demonstrating that execution matters more than geography.
🎯 Benchmarking Your Organization
Are You an AI Leader? Key Questions:
- Strategy: Is AI central to your business strategy, not just your IT roadmap?
- Alignment: Can you directly connect AI initiatives to revenue and profit goals?
- Focus: Have you identified and transformed at least one domain end-to-end?
- Governance: Do you have centralized AI oversight with clear accountability?
- Adoption: Is AI usage growing organically across your organization?
- Infrastructure: Can your systems scale to enterprise-wide AI deployment?
If you answered "no" to most of these questions, you're not alone — 85% of organizations are in the same position. The good news? The playbook for catching up is now clear.
🚨 The Cost of Falling Behind
The performance gap between AI leaders and followers is widening rapidly. Organizations that delay action face not just missed opportunities but potential irrelevance as competitors leverage AI for fundamental competitive advantages.
The research makes clear that this isn't about having the latest AI models — it's about organizational readiness, strategic clarity, and disciplined execution.
🔮 What Comes Next
AI technology continues evolving at breakneck speed, but the principles of successful adoption remain remarkably stable. Leaders who master the fundamentals today position themselves to capitalize on tomorrow's capabilities.
Immediate Action Steps:
- Audit Your AI Maturity: Honestly assess where you stand on strategy, execution, and governance
- Define Your Focus Domain: Identify one high-value area for end-to-end transformation
- Establish Governance: Create clear accountability and oversight structures
- Build Your Foundation: Ensure infrastructure can support scaled AI deployment
- Plan for Change: Develop comprehensive change management strategies
- Identify Partners: Assess where external expertise accelerates progress
🎬 The Bottom Line
The NTT DATA 2026 Global AI Report demonstrates that winning with AI isn't mysterious — it's methodical. The 15% of companies achieving outsized results follow a clear playbook: align strategy with business goals, focus on high-value domains, build strong foundations, empower people, ensure adoption sticks, govern for scale, and leverage strategic partnerships.
The performance gap between leaders and followers is real, measurable, and growing. With 2.5x revenue growth and 3x profit margin advantages, AI leaders aren't just winning — they're establishing positions that will be increasingly difficult to challenge.
The question isn't whether your organization will adopt AI at scale. It's whether you'll be among the 15% who do it right — or the 85% who struggle while competitors pull ahead.
Access the Full Report: The complete 2026 Global AI Report: A Playbook for AI Leaders is available for download at NTT DATA's website, offering detailed insights, industry-specific findings, and regional analysis.
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