NTT DATA leadership is urging enterprises to prioritize 'Return on Experimentation' (ROE) over traditional ROI for early-stage AI initiatives. The firm argues that deep testing in specific business functions is essential before companies can realize tangible financial value, as the tech giant prepares for its Q1 FY2026 earnings update.
NTT DATA is signaling a shift in how enterprises should measure the success of their artificial intelligence investments. Sudhir Chaturvedi, Global Chief Growth Officer and CEO of North America, recently stated that the current focus on immediate Return on Investment (ROI) is often misaligned with the maturity phase of AI technology. Instead, the company is encouraging businesses to adopt a framework of 'Return on Experimentation' (ROE).
Moving Beyond Immediate ROI
According to the leadership at NTT DATA, AI is a breakthrough technology that is still evolving in terms of its commercial frameworks and pricing models. By prioritizing ROE, companies can focus on testing specific, high-impact business functions—such as supply chain management, insurance underwriting, and the detection of financial crime—without the pressure of immediate, short-term financial returns. The core idea is that once an organization understands the operational capabilities of AI, measurable financial benefits will follow as a natural result.
This strategic perspective comes as NTT DATA prepares to share its Q1 FY2026 financial results on August 6, 2026. The firm’s approach reflects a broader industry recognition that deploying AI in complex, real-world enterprise environments requires a deeper business understanding than simple off-the-shelf software implementations.
The Reality of Enterprise Implementation
While the focus on experimentation is central to NTT DATA's advisory, the broader enterprise market is concurrently seeing a pivot toward measurable profit-and-loss (P&L) impact. As AI technologies move toward production, there is increasing pressure on companies to justify the substantial infrastructure costs associated with these deployments.
NTT DATA’s research has identified significant architectural hurdles, particularly concerning data sovereignty, privacy, and security. Many organizations are finding that their existing cloud maturity levels are insufficient to fully capitalize on AI investments. The company notes that addressing these infrastructure gaps is now a strategic differentiator, especially for firms seeking private AI solutions to protect their intellectual property.
Operational Governance and Infrastructure
NTT DATA continues to emphasize a 'human-at-the-core' philosophy. This involves deploying AI agents with defined guardrails and escalation paths that prioritize human oversight. In its own operations, the company utilizes these agents to manage workflows, ensuring that governance is integrated from the start.
As the company moves forward, the market will be looking for updates on how these advisory strategies are translating into tangible project execution. Investors and industry observers will be closely tracking the upcoming quarterly performance to gauge the effectiveness of the company's focus on infrastructure services and the scaling of its AI business, particularly in light of overseas operational targets and the competitive landscape for cloud-based AI services.