R Systems International Limited has officially set March 12, 2026 as the record date for determining shareholder entitlement to interim dividend for the financial year 2026. The company communicated this decision to both major stock exchanges following the Board of Directors' approval during their meeting held on March 6, 2026.

Official Record Date Announcement

The company has filed the official intimation with stock exchanges pursuant to Regulation 42 of the SEBI (Listing Obligations and Disclosure Requirements) Regulations, 2015. The record date specifically determines which shareholders will be entitled to receive the interim dividend declared by the board for the financial year ending December 31, 2026.

Stock Exchange Communication

The formal communication was addressed to both the National Stock Exchange of India Limited and BSE Limited, ensuring compliance with listing requirements. The company provided comprehensive details in its official intimation, including the specific purpose and timeline for the dividend distribution.

Corporate Details and Authorization

R Systems International Limited operates with Corporate Identity Number L74899DL1993PLC053579. The company maintains its registered office at GF-1-A, 6, Devika Tower, Nehru Place, New Delhi – 110019, while its corporate office is located at 3rd Floor, Tower No. 1, IT/ITES SEZ of Artha Infratech Pvt. Ltd, Plot No. 21, Sector TechZone-IV, Greater Noida West, Gautam Buddha Nagar, Uttar Pradesh - 201306.

Shareholder Entitlement Process

Shareholders holding equity shares as of the record date March 12, 2026 will be entitled to receive the interim dividend for the financial year ending December 31, 2026. Company Secretary and Compliance Officer Bhasker Dubey has digitally signed the official communication on March 6, 2026, maintaining transparency in this corporate action.

The dividend declaration represents the company's commitment to rewarding shareholders while maintaining regulatory compliance through proper disclosure to stock exchanges and adherence to SEBI regulations.

R Systems International has announced the publication of comprehensive research on artificial intelligence adoption among mid-market enterprises. The company commissioned independent research from Everest Group, resulting in a detailed report that examines how enterprises are implementing agentic AI technologies to enhance their competitive positioning.

Research Findings on AI Adoption Patterns

The study, titled 'Agentic AI 2026: A Mid-Market Playbook for Adoption and Scale,' surveyed over 200 global mid-market enterprise leaders and revealed significant insights about AI implementation strategies. The research found that more than 40% of mid-market enterprises are bypassing traditional AI adoption stages to accelerate their competitiveness, indicating a shift toward more aggressive AI implementation approaches.

The research indicates that while most enterprises maintain high trust levels in agentic AI, governance frameworks are significantly lagging behind adoption rates. Approximately 30% of enterprises operate with either generic AI frameworks or no policy structure at all.

Functional Areas Showing Strong Results

The report identified specific business functions where agentic AI is delivering measurable returns. Software engineering emerged as the strongest area for AI implementation, with organizations achieving nearly 30% efficiency uplift across monitoring, requirements gathering, and testing activities.

IT operations has become the most scale-ready function, with capabilities including semi-autonomous incident triage, root-cause analysis, and automated runbook execution that reduces operational workload. Customer support functions are evolving from simple deflection to active resolution, with AI agents executing policy-bound actions such as processing refunds and managing entitlement changes.

Implementation Challenges and Solutions Framework

The research identified several key challenges that enterprises face when scaling agentic AI within their existing technology environments. These include integration complexity across fragmented legacy systems, immature tooling and ecosystem fragmentation, and limited governance maturity across organizations.

Primary Implementation Challenges:

• Integration complexity with legacy systems
• Security, auditability, and rollback controls
• Workforce readiness gaps in AI oversight
• Limited governance maturity
• Ecosystem fragmentation issues

The playbook recommends anchoring adoption in outcome-led, high-impact use cases while embedding governance and accountability directly into production workflows. Organizations are advised to scale autonomy in clearly defined tiers aligned to business risk levels and address integration complexity upfront.

Industry-Specific Adoption Patterns

Adoption rates vary significantly across different industry sectors, with patterns correlating strongly to existing digital maturity levels. Technology and telecommunications firms are implementing AI solutions at the fastest pace, while financial services organizations are proceeding more cautiously due to regulatory complexity requirements.

Healthcare organizations largely remain in exploratory phases, reflecting the sector's careful approach to implementing new technologies in patient-care environments. The research emphasizes the importance of building hybrid ecosystems that combine hyperscaler capabilities, system integrators, and specialist AI partners.

Leadership Perspectives and Strategic Guidance

Nitesh Bansal, Managing Director & CEO of R Systems, emphasized the critical nature of the current enterprise AI adoption phase. The research aims to provide clarity on enterprise positioning in agentic AI adoption while offering practical guidance for embedding AI into real enterprise environments.

Akshat Vaid, Partner at Everest Group, highlighted the report's focus on moving from AI experimentation to execution phases. The research provides structured guidance for organizations seeking to scale agentic AI responsibly while converting early implementation promise into sustained business value through formal oversight mechanisms and clearly defined ownership models.