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  • for Topic: Ai Governance
I have previously described how context is everything when it comes to establishing enterprise trust in the output of generative and agentic artificial intelligence. Based on our recent interactions with analytics and data software providers, it might be more accurate to say that context is everywhere, as almost all providers of analytics and data software are currently positioning products in... Read More

Topics: Operations, Data Platforms, Generative AI, Data Intelligence, AI & Technologies, AI & Machine Learning, AI Governance


I recently wrote about the distinction between personal productivity artificial intelligence (AI) and enterprise AI. Each has a role to play. An important challenge facing enterprises in the coming years will be encouraging and supporting the use of AI-enabled personal productivity applications for individuals and small workgroups while preventing their misuse in performing enterprise tasks and... Read More

Topics: Office of Finance, Supply Chain Planning, Business Planning, Enterprise Resource Planning, ERP and Continuous Accounting, supply chain management, digital finance, Procure-to-Pay, Consolidate and Close Management, Order-to-Cash, AI & Machine Learning, Buyer Behavior, AI Governance


Enterprise architecture has traditionally been organized around three primary control planes: infrastructure, identity and applications. Each evolved to solve a specific challenge. Infrastructure established where workloads execute. Identity determined who could access enterprise resources. Applications standardized business processes and information flows. Artificial intelligence introduces a... Read More

Topics: Observability, IT & Technologies, Identity, IT Management & Operations, AI Governance, Control Layer, Enterprise Architecture, Policy, Runtime Control, Detection and Response


As an increasing proportion of enterprise software becomes replaced or augmented by artificial intelligence agents, capabilities for application, data and API management are evolving accordingly. Orchestrating communication and integration among applications, data, systems, tools and processes is essential to enabling agents to execute business processes through autonomous actions. Established... Read More

Topics: Operations, Generative AI, AI & Technologies, AI & Machine Learning, AI Governance


Artificial intelligence is giving IT Asset Management (ITAM) an unexpected second act. Over the past decade, Software Asset Management (SAM) gradually lost strategic visibility as organizations shifted toward SaaS subscriptions and decentralized technology purchasing. Business units acquired applications directly. Developers consumed cloud services on demand. Employees adopted productivity tools... Read More

Topics: ITSM, Observability, IT & Technologies, IT Management & Operations, AI Governance, Software Asset Management, SAM, Software License Management, SaaS Management, AI Asset Management


As enterprises embracing artificial intelligence move from initial pilots and trial projects through deployment and into production at scale, many are realizing the critical importance of reliable data management and agile, responsive data operations (DataOps) processes to improve trust in the data used for AI and business intelligence. With an emphasis on agility, automation and continuous... Read More

Topics: Operations, Data Intelligence, AI & Technologies, AI & Machine Learning, AI Governance


In the first stages of any major technology breakthrough, there is often a three-blind-men-describing-an-elephant effect at work. In the case of artificial intelligence (AI), its vast potential has people looking at it from their single perspective to the exclusion of others. It’s that narrow focus that has lent itself to the “Saaspocalypse” meme earlier this year. AI is already having a... Read More

Topics: Office of Finance, Supply Chain Planning, Analytics, Business Planning, Workplace, Enterprise Resource Planning, supply chain management, Digital Business, Generative AI, Customers and CX - Business & Technologies, Employees & HCM - Business & Technologies, Vertical Industry, AI Governance


ServiceNow used the Knowledge 26 conference to make a clear market claim: Enterprise AI will not scale through disconnected assistants, isolated copilots or unmanaged agent experiments. It will scale through governed autonomous work tied to workflow execution, operational data, identity controls and measurable business outcomes. That is the right conversation for enterprise IT leaders. The risk... Read More

Topics: ITSM, Cybersecurity, Intelligent Automation, AIOps, IT & Technologies, ADM & DevOps, Platforms, Non-Human Identity, IT Management & Operations, ServiceNow, ESM, Cybersecurity Automation, AI Governance, Autonomous Workforce, ITAM, Identity Governance, Workflow Automation


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