Mar 24, 2026 9:02 AM Eastern Daylight Time Zenity Announces Partnership With ServiceNow to Operationalize AI Agent Risk Reduction in SecOps ServiceNow SecOps now natively includes Zenity security signals and controls, giving customers built-in protection and governance for AI agents Zenity Announces Partnership With ServiceNow to Operationalize AI Agent Risk Reduction in SecOps Share SAN FRANCISCO--(BUSINESS WIRE)--(RSA Conference) — Zenity, the leading security and governance platform for AI agents, today ...

Summary of ServiceNow Conference Call Company Overview - **Company**: ServiceNow (NYSE: NOW) - **Event**: 2026 Conference - **Date**: March 02, 2026 Key Points Industry Insights - The current landscape is characterized by a significant investment in AI, with $2.5 trillion projected for 2026, yet many projects remain in the proof-of-concept stage, indicating a gap between thought and action [45][46] - The transition from traditional software models to AI-driven solutions is emphasized, with a focus on the importance of human interaction in sales despite the rise of AI [40][42] Company Performance - ServiceNow has consistently performed well, with a revenue growth rate more than twice that of competitors and a free cash flow margin that is higher than industry averages [108][122] - The company reported a 25% year-over-year growth in active users, countering concerns about the impact of AI on job roles [126] Strategic Initiatives - ServiceNow has embraced partnerships with major cloud providers (AWS, Azure, GCP) and AI platforms (OpenAI, Anthropic) to enhance its service offerings [92][93] - The acquisition of companies like Moveworks, Veza, and Armis is aimed at building an AI Control Tower for business reinvention, focusing on managing both human and machine identities [96][97] Competitive Landscape - ServiceNow positions itself as a leader in the AI supercycle, emphasizing the need for integrated solutions that connect front-end customer interactions with back-end operations [110][111] - The company aims to redefine CRM from customer relationship management to comprehensive resolution, integrating AI to enhance customer service [113] Federal Business - ServiceNow maintains a strong relationship with federal and state governments, with a notable 30% growth in the public sector despite market uncertainties [153] Misunderstandings and Future Outlook - Common misconceptions include concerns about seat-based licensing and the potential impact of AI on employment, which ServiceNow addresses through its hybrid pricing model and commitment to innovation [157][158] - The company is well-prepared for future challenges, leveraging its unique architecture that allows for sovereign cloud solutions and flexibility in deployment [127][128] Financial Metrics - The company has a robust pipeline, with $2 billion in CRM opportunities, indicating strong demand for its services [102] - ServiceNow's business model is designed to adapt to changing market conditions, ensuring resilience and continued growth [126][130] Additional Insights - The importance of emotional intelligence (EQ) in sales and customer interactions is highlighted, suggesting that personal connections remain vital even in an AI-driven world [40] - The narrative around AI and its implications for business processes is evolving, with ServiceNow positioned to lead in integrating AI into operational workflows [94][95]

Summary of Key Points from the Conference Call Industry Overview - The conference call focuses on the **US Technology Equities** sector, particularly the **software and AI** landscape, highlighting the transition towards AI productization expected by **2026** [1][2]. Core Insights - **AI Productization Timeline**: 2026 is projected as the pivotal year for AI productization within enterprise software, moving from early-stage deployment to widespread enterprise integration [1][2]. - **Current AI Deployment Challenges**: Companies are still in the early stages of AI experimentation, facing challenges in hiring skilled talent and achieving meaningful results from initial projects [1][2]. - **Shift in Investment Focus**: There is a notable shift from hardware to software investments as companies begin embedding AI into their existing workflows, with significant advancements seen in companies like **Oracle, Microsoft, Salesforce, and ServiceNow** [1][2][5]. - **Monetization Visibility**: Vendors controlling structured enterprise processes are expected to have improved monetization visibility as AI becomes a value-added feature in their product suites [2]. Financial Performance Highlights - **Q3 Earnings Performance**: Most companies reported modest revenue beats but significant improvements in non-GAAP operating income and EPS, indicating early economic benefits from AI deployments [7][9]. - **Revenue Growth Constraints**: Despite increased interest in AI, enterprise budget expansions remain modest, limiting revenue growth [9]. - **Profitability Boost from AI**: AI-driven efficiencies are enhancing unit economics, leading to higher non-GAAP operating income and EPS, even without substantial revenue increases [9]. Company-Specific Insights - **Preferred AI Stocks**: The report identifies **Oracle (ORCL), Microsoft (MSFT), ServiceNow (NOW), and Salesforce (CRM)** as preferred stocks likely to benefit from their strategic positioning in the AI landscape by 2026 [2][5]. - **Earnings Revisions**: Companies like **Microsoft** and **Palantir** have seen significant upward revisions in revenue and EPS forecasts, reflecting strong AI-related demand [13][14]. - **CoreWeave's Performance**: CoreWeave reported revenue of **USD 1,365 million** for Q3, exceeding consensus but below estimates, with concerns about asset turnover and future guidance indicating potential revenue decline [18][19]. Market Dynamics - **AI Infrastructure Demand**: The demand for AI infrastructure and data workloads is solid, with companies like **Oracle and CoreWeave** aggressively scaling capacity [15]. - **Investor Sentiment**: There is a growing investor focus on how companies will deploy AI to solve business problems, with many still not fully recognizing the link between AI deployment and enterprise software [2]. Conclusion - The technology sector is on the brink of a significant transformation driven by AI, with 2026 expected to be a critical year for monetization and integration into enterprise workflows. Companies that are well-positioned in the software space are likely to capitalize on this trend, while challenges remain in the broader economic environment and enterprise budget constraints.

Core Insights - KPMG has launched KPMG AI Trust, a suite of services aimed at ensuring AI reliability, accountability, and transparency as organizations scale AI applications, leveraging the Trusted AI framework and ServiceNow's AI Control Tower [1][2][4] Group 1: AI Governance and Risk Management - The KPMG AI Trust services utilize AI to help clients enhance value and manage risks across various domains including compliance, legal, and security, ensuring AI systems are secure and ethically sound [2][6] - A KPMG survey indicates that 82% of leaders view risk management as their biggest challenge, while 73% prioritize data privacy and security when selecting a Generative AI provider [3][6] - KPMG emphasizes the need for robust governance in AI, stating that it is critical for AI to be trustworthy as it becomes integral to business strategy and value creation [4][5] Group 2: ServiceNow Collaboration - KPMG AI Trust is enabled by ServiceNow's AI technology, which allows for automated compliance processes and continuous monitoring of regulatory adherence [8][10] - The collaboration with ServiceNow aims to create a transformative AI service delivery platform, KPMG Velocity, which will support enterprises in adapting to the intelligent economy [7][10] - The solutions provided are compatible with various large language model platforms and can integrate with ServiceNow's risk management software [9] Group 3: Features of KPMG AI Trust - The KPMG AI Trust suite includes features such as risk-tiered AI solution intake evaluation, AI inventory and controls, pre-launch validations, and dynamic regulatory assessments to ensure compliance and risk management [15] - These capabilities are designed to protect employees, companies, and consumers as AI adoption accelerates [6][10]