What’s Covered?
This executive report from NTT DATA confronts a pressing dilemma in AI: the widening “responsibility gap”—the growing disconnect between how fast AI (and especially GenAI) is advancing and how prepared organizations are to use it safely, ethically, and sustainably. Based on a global survey of over 2,300 senior leaders in 34 countries, the study reveals that while excitement about GenAI is high, clarity and alignment on responsibility are still missing at the top.
The report dives into four key sections:
- Responsible Governance: Maps tensions at the executive level, with leaders split between prioritizing innovation or responsibility. Notably, 80%+ of C-suite respondents say the gap is significant.
- The Workforce Blind Spot: Points to education on ethical GenAI use as a key limiter—more so as investments grow. Lack of clarity from leadership and weak internal policies also compound the problem.
- Closing the Gap: Lays out a four-step roadmap:
- Responsible by Design – embed ethics early
- Upskill the workforce – train on both usage and risks
- Multilevel governance – go beyond compliance
- Global collaboration – engage with standards, academia, and government
- Leadership’s Role: Repeatedly emphasized as the single most important factor for narrowing the gap. Organizations that perform best financially are also those most likely to invest in aligning innovation with ethical practices.
The authors don’t just list risks—they highlight how lack of responsibility actively slows down implementation, wastes investment, and heightens exposure to legal, security, and reputational threats.
💡 Why it matters?
This isn’t just a compliance problem. It’s a strategy bottleneck. Without senior leadership stepping in to define what responsible AI means for their organization, GenAI projects stall, fragment, or expose companies to real risk. Responsibility isn’t the brakes—it’s the steering wheel. And right now, too many organizations are building horsepower without knowing how to drive.
What’s Missing?
The report identifies governance gaps but doesn’t provide a detailed operational model to fill them. There’s no toolkit, no checklist, no benchmark maturity model. It also doesn’t define how responsibility metrics should be tracked or integrated with innovation KPIs. The training focus is clear, but the guide falls short on how to institutionalize governance across silos, especially in global orgs.
The leadership recommendations, while important, lean motivational rather than actionable. There’s a lot of “what” and “why,” but less “how,” especially for companies that lack resources or are still defining internal AI use cases.
Lastly, while it briefly mentions global collaboration, it doesn’t directly engage with emerging standards like ISO 42001, EU AI Act obligations, or NIST RMF—so the legal/regulatory alignment piece is still a missing link.
Best For:
C-level leaders—especially CEOs, CISOs, and Chief Data or Innovation Officers—at large enterprises looking to balance GenAI excitement with grounded oversight. It’s also useful for strategy and ethics officers who want evidence that responsibility isn’t just nice to have—it’s key to unlocking AI’s full business value.
Source Details:
Title: The AI Responsibility Gap: Why Leadership is the Missing Link
Publisher: NTT DATA Inc. (2025)
Lead Author: Abhijit Dubey, CEO
Methodology: Based on interviews and survey data from 2,307 AI decision-makers and influencers across 34 countries, spanning 12 sectors. Research conducted in partnership with Jigsaw Research, with 98% confidence level and ±3% margin of error.
Scope: Global (with strong representation from large enterprises >10,000 employees)
