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  • for Month: 2026/09
Finance has been a hotbed of technology adaptation, especially in the digital age, because money is just numbers and therefore easily lends itself to new types of digital innovation. For centuries, fortunes were found in removing friction from financial transactions. For example, starting in ancient times, coins were minted to reduce the need for weighing metal in every transaction, along with... Read More

Topics: Office of Finance, ERP and Continuous Accounting, blockchain, digital finance, Procure-to-Pay, Consolidate and Close Management, Treasury, Order-to-Cash, Payments, Stablecoins


Enterprise AI governance is advancing faster than the operational controls needed to support it. Organizations are defining principles, policies, risk tiers, review boards, lifecycle gates and accountability models for AI. These efforts establish what should be allowed, required or prohibited. They do not always determine how those requirements will be enforced once AI is embedded in... Read More

Topics: Cybersecurity, Observability, Intelligent Automation, IT & Technologies, ADM & DevOps, Cloud Infrastructure, IT Management & Operations, AI Governance, Control Layer, Operational Control


When we talk about “enterprise CX,” we’re describing a process in which multiple teams inside a business try to analyze and anticipate customer behavior and then act on those insights towards desired outcomes. But try to make that happen and you soon find that the contact center remains woefully cut off from the people and systems that need to be involved. The links between service centers and... Read More

Topics: automation, Contact Center, Customer Experience Management, Intelligent Self-Service, Customers and CX - Business & Technologies, Back Office, Front Office


For Chief Revenue Officers, the central question about artificial intelligence (AI) is no longer whether sellers will use it. The question is whether they will use it well enough to improve revenue performance. Most sales organizations now have access to generative AI (GenAI), embedded copilots, conversation intelligence and predictive insights. Yet access alone does not create an advantage. As... Read More

Topics: sales engagement, Generative AI, Revenue Lifecycle Management, Office of Revenue - Business Technologies


We are experiencing a generational transformation of service delivery, and it’s not just about artificial intelligence (AI). I believe we are also seeing a reordering of how software providers organize the tools used in contact centers. We call it Contact Center as a Service (CCaaS) because that’s what people are used to, even though “as a Service” doesn’t accurately describe an environment where... Read More

Topics: Contact Center, agent management, Customer Experience Management, CCaaS, Intelligent Self-Service, Conversational AI, Customers and CX - Business & Technologies, Conversational Intelligence, Hyperscaler


The emergence of artificial intelligence (AI) agents capable of automating enterprise decision-making has placed greater focus on the need for trusted and reliable data. As I recently explained, the guardrails provided by agent harnesses ensure the output of agents and large language models (LLMs) is grounded by enterprise data. The accuracy and trustworthiness of the content are dependent on the... Read More

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


Enterprise security teams have access to extensive vulnerability intelligence but still struggle to determine where known flaws exist across large and changing software environments. Point-in-time assessments, manual code reviews and selective scanning cannot provide the coverage or frequency required as applications, dependencies and threats change. Artificial intelligence can accelerate this... Read More

Topics: Cybersecurity, IT & Technologies, Source-code Security, AI Vulnerability Management, Code Analysis, Vulnerability Operations, Application Security, Small Language Models, Vulnerability Localization


Artificial intelligence (AI) screening is forcing recruiting leaders to answer a question many organizations have avoided for years. When technology influences who gets seen, ranked, advanced or ignored, who owns the bias? The easy answer is to point at the software provider. The equally easy answer is to say the employer owns the hiring decision, full stop. Neither answer is sufficient. Bias in... Read More

Topics: Employee Engagement, Talent Management, Employees & HCM - Business & Technologies


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