Overview

Mumbai, 15 Sept 2026 – SAS, in partnership with IDC, released the second annual Data and AI Impact Report: The New Economics of Trust. The study surveyed 2,699 decision‑makers across 28 countries, focusing on four industries – banking, insurance, life sciences and the public sector – to identify drivers of AI profitability.

Trustworthy AI and ROI

Organizations that applied trustworthy AI practices were 15 times more likely to report strong or high ROI (62 % versus 4 % for laggards). These leaders realized 1.85 times greater gains across 13 business outcomes, including revenue growth, cost savings and customer experience. 85 % of AI‑leader firms are increasing investment in trustworthy AI by more than 10 % this year, widening the performance gap.

Investment Intentions in India

In India, 91.8 % of surveyed firms expect to raise AI spending over the next 12 months. The share planning a >20 % spend increase rose from 5 % in 2025 to 27.3 % in 2026, underscoring AI as a strategic priority.

Data Quality & Governance

Data quality and governance were cited as critical by 69.4 % of Indian respondents. Yet only 17.5 % of enterprises have a fully optimized data infrastructure capable of supporting agentic AI, limiting performance. Companies with an optimized data foundation are four times more likely to expect strong ROI and six times more likely to mandate data‑quality and explainability controls.

Trust Gaps and Override Rates

Overall, 97.2 % of users override AI‑generated recommendations at least occasionally. The primary reason is the AI’s inability to provide an explanation. Trust levels fall from 76 % for generative AI to 66 % for agentic AI, reflecting growing concerns as autonomy rises.

Sector‑Specific Findings

  • Banking: 85 % of AI‑leader banks have established governance frameworks, compared with 29 % of laggards.
  • Public Sector: 41 % of leaders plan to increase trustworthy‑AI investment by >20 % in the coming year.
  • Life Sciences: 23 % have scaled AI company‑wide, the highest among surveyed industries.

Quotes

> “When AI works, it’s incredibly impactful. However, state‑of‑the‑art agents can have error rates exceeding 25 % on complex tasks – unacceptable in high‑stakes decisions.” – Bryan Harris, CTO, SAS.

> “The findings reflect a broader shift among Indian organisations toward strengthening foundations for trustworthy and explainable AI.” – Noshin Kagalwalla, Vice President – Public Sector, APAC & Managing Director, SAS India.

> “Stronger oversight, explainability, accountability and data foundations are becoming prerequisites for scaling AI successfully.” – Chris Marshall, Vice President, IDC.

Trustworthy AI Scoring

Organizations were evaluated on five dimensions (scored out of 100):

1. Data quality and governance

2. Model governance and oversight

3. Explainability and fairness

4. Responsible AI policy

5. Audit and accountability

Leaders achieved an average total score of 80 or higher.

Conclusion

The report highlights that AI profitability in India hinges less on technology choice and more on governance, data quality, and explainability. Companies that embed trustworthy AI practices are poised to capture superior returns as AI adoption accelerates.