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As enterprises accelerate investments in agentic artificial intelligence (AI), advanced analytics and data-driven decision-making, the ability to provide trusted, governed and real-time access to distributed data has become increasingly important. Many enterprises continue to contend with fragmented data estates spanning cloud platforms, on-premises systems, software-as-a-service (SaaS)... Read More

Topics: Operations, Analytics, Generative AI, Data Intelligence, AI & Technologies


Salesforce’s Dreamforce event was an event of epic proportions. Pre-pandemic attendance peaked at 170,000 about 10 years ago. This year’s event garnered nearly as much attention with 50,000 attendees and 122,000 online viewers. The event took over the entire Moscone Convention Center, including the North, South and West pavilions, as well as surrounding venues. If the agentic future that... Read More

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


The ability to access and analyze data from multiple data sources has always been critical to business intelligence (BI), driving the evolution of the market for data integration products to ensure data from operational workloads is available for analytics use cases. Despite that, data silos continue to be a perennial challenge with the potential to stifle innovation given the speed and... Read More

Topics: Data Platforms, Generative AI, Data Intelligence, AI & Technologies


A software provider recently described a familiar exchange between enterprise IT and executive leadership during a disruption: IT: Systems are down. We are confident we can achieve the company’s Recovery Time Objective of eight hours. CEO: I need it sooner. What can you do? IT: We can achieve a Minimum Viable Organization in three hours. CEO: Do it. The exchange captures what happens when a... Read More

Topics: Disaster Recovery, Cybersecurity, IT & Technologies, Data Resilience, RTO, Return Time Objective, Minimum Viable Organization, Cyber Resilience, Operational Resilience, Enterprise Control Architecture, MVO


The Contract Lifecycle Management (CLM) market is entering a new phase as providers move beyond repositories, workflows and electronic signatures toward contract intelligence. Yet many CLM systems still meet the needs of only some buying centers, leaving legal, procurement, finance, sales and operations to contend with fragmented processes, difficult handoffs, inconsistent data and tools that are... Read More

Topics: Revenue Lifecycle Management, Contract Lifecycle Management, Office of Revenue - Business Technologies, CLM


Dreamforce is usually a performative exercise, one in which Salesforce uses the gathering to solidify messaging around products that act as tentpole explanations of its strategy, even if many of those announced products aren’t going to be GA for the better part of a year. This year was markedly different. Product announcements were less flashy, but potentially far more consequential to the... Read More

Topics: Analytics, Contact Center, Dreamforce, Customer Experience Management, Generative AI, Customers and CX - Business & Technologies, AI and Machine Learning, Service Management, Context, Agentic


What job postings reveal about the mandate of the CRO? The Chief Revenue Officer is no longer simply the executive responsible for closing more deals. ISG Research analysis of 102 current CRO job postings finds that organizations expect the role to connect sales, marketing, customer success, revenue operations (RevOps), partnerships, pricing and technology into a coordinated revenue engine. Sales... Read More

Topics: sales engagement, Revenue Performance Management, Office of Revenue - Business Technologies


I have written before about how enterprises are realizing the importance of data management if they are to succeed in implementing artificial intelligence and enabling agentic decision-making. Data quality and veracity are important aspects of increasing trust in the data used to generate content and automate decisions. More fundamentally, however, a successful data strategy depends on an... Read More

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


You may be old enough to remember the Talking Heads 1984 concert film, “Stop Making Sense.” I think that phrase is a fitting warning to anyone designing agents for human-centric business processes who assumes that their behavior must always be rational. Despite significant advances in applied analytics, behavior modeling and process intelligence, achieving the right balance between achievable... Read More

Topics: Office of Finance, Employee Engagement, Talent Management, Workforce Management, Revenue Performance Management, Office of Revenue, Generative AI, Employees & HCM - Business & Technologies, AI & Machine Learning, Agentic Systems, Agents


We stand at a watershed in enterprise planning activities as a result of the availability of artificial intelligence (AI) and agentic systems. In particular, AI and agents will facilitate the process of continuous supply chain planning through better cross-functional coordination, significantly shortening the time it takes to iteratively juggle and resolve supply and demand chain objectives and... Read More

Topics: Governance, Supply Chain Planning, Business Planning, Enterprise Resource Planning, supply chain management, Manufacturing, Healthcare, Energy, Automotive, CPG & Retail, Supply Chain and Operations, AI & Machine Learning


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


Black Hat USA 2026 reinforced a practical shift in enterprise cybersecurity: AI is no longer just a threat vector or productivity aid. It is becoming an operating model. The most relevant software provider signals pointed toward agentic security operations, nonhuman identity, runtime control, security data architecture and AI-generated remediation. For CIOs, CISOs, platform leaders and software... Read More

Topics: Cybersecurity, IT & Technologies, Non-Human Identity, NHI, Autonomous SOC, AI Governance, AI Runtime Security, Black Hat


Your application tracking system (ATS) may not be broken. It may be doing exactly what your hiring process told it to do. In a market buzzing with AI, agentic workflows and automation, that should make recruiting leaders pause before they blame the platform, replace the system or automate the next step in a process nobody has challenged in years. Software does not get a free pass, and neither do... Read More

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


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