New NTT Survey: Global CEOs to Increase Enterprise AI Investment Despite Infrastructure and Sustainability Concerns
White paper identifies CEO challenges and opportunities for the realization of optimized, effective and sustainable AI infrastructure
A new whitepaper from
“Amidst historic AI investments, business leaders are asking vital questions about achieving an AI-empowered future with the potential to unlock unprecedented growth and productivity but without sacrificing quality, resilience, and the employee and social contract that is expected of businesses,”
Demand for AI Investment Outpaces Scaling Readiness
When prompted about their organization’s active deployment of infrastructure specifically for AI, only 18% of respondents believe their technology infrastructure is highly optimized to support AI at scale, even as 68% plan to increase investment in the next two years.
As Dubey explains in the white paper, an enterprise’s AI investment philosophy must reflect the company’s core ethos: “AI scales not through advanced models alone, but also through the strength of the foundations beneath them. When organizations invest in skilled talent, unified teams, resilient platforms, and trusted data, AI moves from isolated experiments to a disciplined capability that drives enterprise transformation.”
Nearly half of the executives surveyed plan to increase AI budgets by 11% or more. While two out of three CEOs currently regard predictive AI as their top strategic priority, they acknowledge that the combined implementation of predictive, generative, and agentic AI will yield the most significant business results. However computing power constraints, legacy networks and data-preparation bottlenecks represent major obstacles to achieving AI maturity and scaling.
CEOs Call for AI Resilience, Connection and Ethics
According to the survey, 83% of executives identified that human-AI collaboration skills will become critical by 2030, with AI now a core driver of competitiveness for their organizations. However, three key challenges still define these integrations:
- Performance Over Planet: About 70% of CEOs prioritize either maximum performance or a performance-first approach to AI workloads; 75% still believe sustainable practices will sacrifice profitability, revealing a persistent zero-sum mindset.
- Data Integrity and Cybersecurity: Respondents identified top risks associated with Shadow AI as data leakage (41%), data integrity (40%), security vulnerabilities (38%) and unreliable decisions (35%); 67% of leaders believe their organizations have implemented effective AI governance processes.
- AI Infrastructure Scaling Demands: 83% of respondents think executives face immense pressure to prioritize rapid AI scaling benefits over energy concerns. At the same time, new technologies such as optical networking and computing are viewed as potential solutions for a more sustainable AI infrastructure.
Growing Workloads Driving Interest in Photonic Infrastructure
New information technology infrastructure is needed to meet growing workloads and increased capacity requirements intensified by AI without proportionally increasing power consumption. A clear example is NTT’s IOWN initiative which facilitates the move from electronic to optical data transmission across networks and in data centers - between circuit boards, silicon packages on circuit boards and silicon die inside packages. IOWN is designed to ultimately achieve three key performance targets for data transmission in networks and data centers: up to 100x less power consumption, a 125x increase in capacity and a 200x reduction in end-to-end delays compared to conventional infrastructure.
The survey revealed that 91% of executives are familiar with photonics, with 55% expressing strong interest in adopting this technology into their operations and 36% already using photonic technologies in some capacity.
Methodology
Report findings are drawn from a survey of 359 global CEOS of companies with at least
The research measured investment priorities, infrastructure maturity, perceived risks, workforce expectations and attitudes toward sustainability, photonics, data governance and AI regulation.
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