As enterprises accelerate AI adoption, secure governance, automation, and operational resilience are becoming business priorities. Shivaprakash Muthukrishna, Global Practice Head – ServiceNow, discusses, in an exclusive conversation with Abhineet Kumar of Elets Technomedia, how the expanded collaboration with Inspira is helping organisations scale AI securely while strengthening cybersecurity, governance, and enterprise-wide automation.
Edited excerpts:
Q1. Inspira has expanded its strategic collaboration with ServiceNow to become a full-spectrum partner. What drove this decision, and how does it strengthen your vision for helping enterprises adopt AI securely and at scale?
Organizations today are looking beyond isolated AI deployments, demanding secure AI adoption for businesses at scale and making innovation achievable. By leveraging the AI-driven ServiceNow platform and security solutions, we at Inspira assist customers across the entire lifecycle, including strategy, implementation, governance, automation, and managed services. This collaboration brings together seamless workflow orchestration with enterprise intelligence and control, combining ServiceNow’s industry-leading AI-based workflow and ITSM capabilities with Inspira Enterprise’s deep cybersecurity expertise. Together, we deliver comprehensive, end-to-end, and resilient solutions for organizations while embedding cloud, security, compliance, and governance at the outset. With these, customers can accelerate innovation, enhance operational efficiency, and realize the full potential of AI at enterprise scale.
Q2. AI governance is becoming as important as AI adoption itself. How do you see the ServiceNow AI Control Tower addressing concerns around transparency, compliance, and responsible AI deployment for enterprises?
AI governance is crucial to ensure responsible use, regulations, compliance, and alignment with enterprise goals. As organizations scale their deployment of autonomous AI agents, concerns surrounding “AI sprawl” and security risks rise. Enterprises need complete visibility into how AI is being deployed, which models and agents are in use, what data they access, and whether they comply with organizational policies and regulatory requirements. These challenges can be addressed with ServiceNow AI Control Tower, a centralized governance and compliance command center that provides enterprises with total visibility to discover, monitor, and manage both native and third-party AI agents and models from a single interface. It provides a real-time, 10,000-foot view of all active AI models, prompts, datasets, and agents running across the enterprise. It helps organizations enforce frameworks like the EU AI Act and ISO/IEC 42001 by tracking approvals, bias testing, and privacy guardrails throughout the AI lifecycle. The Control Tower oversees AI initiatives from the initial intake and assessment phase through building, deployment, and continuous performance optimization, while ensuring it is done responsibly.
Q3. Inspira has deployed more than 50 AI agents across identity management, cyber defence, threat detection, and risk operations. What have been the biggest operational lessons from these real-world implementations, and where have you seen the highest business impact?
Inspira Enterprise initiated the MindSpark initiative, where we managed to collate more than 150 ideas from our internal operations team. Our team defined and deployed 50+ AI agents in the system. By implementing these, we have fast forwarded the journey towards a “Closed Loop Remediation” approach we have established, where our main focus is to resolve operational issues with minimal or no human in the loop. This reduces the regular issue MTTR from days to minutes. The major business impact has been on the part where the AI agents are participating in the resolution methods. – With this approach, the user experience has improved significantly. Ticket handling is now more focused on resolving complex issues that AI agents cannot address, while performance analytics demonstrate a substantial improvement in operational efficiency. Now we are stepping into areas such as Legal, HRSD, BCM, DR, Armis, and TPRM modules, where AI agents can be utilized as part of addressing operational challenges.
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Q4. Your organisation has reported a 40% increase in AI adoption and a 35% improvement in productivity. What were the key factors behind these outcomes, and how should enterprises measure the success of AI initiatives beyond productivity metrics?
The 40% increase in AI adoption and 35% productivity improvement were driven by a combination of strong governance, targeted use cases, and close alignment between ServiceNow expertise, technology understanding (tool and process) and operational roadmap activities. We implemented more than 50 AI agents across identity management, cyber defence, threat detection, and risk operations, focusing on repetitive, high-volume activities where automation could deliver measurable outcomes. Adoption was accelerated through strong leadership support, close collaboration between ServiceNow experts and Inspira’s ServiceNow team, secure access to enterprise data, and human-in-the-loop controls that involved stakeholders across all operational functions. Clear ownership, user training, and continuous feedback also helped employees trust and integrate ServiceNow AI workflows into daily activities.
Enterprises should measure AI success beyond productivity by assessing business, operational, risk, and employee outcomes. The relevant measures we focused,-on were toward reduction in security incidents, faster threat identification and response, improved access governance, lower error rates, stronger regulatory compliance, and better risk visibility. We were also evaluating user adoption, decision quality, customer and employee experience, model accuracy, explainability, resilience, and the level of human intervention required. Financial measures such as cost avoidance, revenue protection, and return on investment remain important, but they should be balanced with responsible AI indicators, including bias, privacy, security, and auditability. Ultimately, AI success should be measured by sustainable business value, improved resilience, and better outcomes for stakeholders.
Q5. With cyber threats becoming increasingly sophisticated, how do you see AI-powered automation reshaping Security Operations Centres (SOCs), and what safeguards are essential to ensure trust and resilience?
AI-powered automation enables rapid threat detection, intelligent prioritization, and automated response. SOCs that are powered by AI efficiently process and analyze telemetry from various endpoints, networks, and cloud environments without overwhelming analysts. AI, as a cognitive layer, performs automated triage and prioritization of alerts. With false positives getting filtered and alerts getting prioritized, security teams can focus on priority alerts. The contextual enrichment by AI automation includes ingesting data from SIEM, EDR, and Cloud logs, applying contextual tagging related to asset criticality or user risk scores. AI links events, timelines, and systems to build a clear picture of an incident. Automated AI-led incident correlation relieves analysts from mapping out timelines from a dozen different tools. AI algorithms filter out the noise and highlight only those alerts that have real context and risk scores. AI agents can take over the majority of Tier I and Tier 2 tasks, freeing security analysts to focus on high-end tasks.
However, automation must be deployed responsibly. Trust and resilience depend on strong AI governance, human oversight for critical decisions, transparent and explainable AI models, robust identity and access controls, and continuous validation of AI-driven actions. Establishing clear rules for critical actions is key, where SOC specialists can review and approve certain AI decisions before a disruptive action is taken, especially if it could impact critical infrastructure.
Q6. Enterprises often struggle with fragmented visibility across IT, security, risk, and compliance functions. How does the combination of ServiceNow’s AI capabilities and Inspira’s implementation expertise help organizations build a unified “single pane of glass” for decision-making, and what strategic advantages does this deliver in today’s rapidly evolving threat landscape?
By combining ServiceNow’s AI-powered platform with Inspira Enterprise’s deep expertise in cybersecurity, cloud, and enterprise transformation, organizations can establish a unified operational view that links people, processes, assets, and security events across the enterprise. Inspira has established a unified operational view by deploying the ServiceNow Control Tower as the enterprise-wide governance layer across its ecosystem. This includes AI agents, agentic workflows, models, datasets, prompts, and skills, from intake and assessment through deployment, monitoring, and optimization. The ServiceNow Control Tower also provides Inspira’s customers with a proven framework for AI portfolio management, risk oversight, regulatory compliance, and value realization, enabling organizations to scale AI adoption with confidence.