AI strategy

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Why AI ROI Is Stalling: A CEO and CIO Guide to Turning Pilots into Operating Results

ai, AI (Artificial Intelligence), AI Governance, AI portfolio management, AI ROI, AI strategy, Artificial Intelligence, CEO strategy, CIO strategy, Enterprise AI, scaling AI pilots, unit economics, value realization

TL;DR AI ROI is stalling because many organizations are managing experiments, not investments. A pilot can prove that a model works, users are interested, or a workflow can be partially automated. It does not prove that the organization can produce repeatable business value after integration, data, security, change management, support, and operating costs are included. […]

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AI Is Coming for Inefficiency: How Enterprise Leaders Should Redesign Work Before Automating It

agentic ai, ai, AI (Artificial Intelligence), AI Governance, AI operating model, AI productivity, AI Risk Management, AI strategy, Artificial Intelligence, Enterprise AI, Observability, Responsible AI, workflow automation

AI Is Coming for Inefficiency: How Enterprise Leaders Should Redesign Work Before Automating It AI is not just another technology wave waiting for a procurement cycle, a license rollout, and a few enablement sessions. It is a pressure test on the way work actually moves through the enterprise. That is why Gartner’s framing matters. The

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Why AI Pilots Fail to Scale in Enterprises

ai, AI (Artificial Intelligence), AI Adoption, AI failure, AI Governance, AI pilots, AI ROI, AI strategy, Artificial Intelligence, change-management, data quality, digital transformation, Enterprise AI, pilot to production, scaling AI, Uncategorized

Why it matters: Most enterprise AI pilots never reach production. Here is why they stall and the data, governance and change moves that let the rare ones scale.

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Planning for AI Induced Economic Volatility

ai, AI (Artificial Intelligence), AI strategy, Artificial Intelligence, Enterprise AI, governance, Thought Leader

Enterprise deployments of large language models and agentic workflows are shifting from experimental pilots to core infrastructure. In 2025, enterprises piloted AI. In 2026, they are going to production and, in 2027, they will scale.  As organizations go to production, the company focus is on operational efficiency and infrastructure cost optimization. However, enterprise leaders must

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ManageEngine User Conference Bengaluru – Vision 2026, AI Focus & Leadership Connect

ai, AI (Artificial Intelligence), AI & Innovation, AI & Machine Learning, AI & ML, AI Automation, AI developemnt, AI in IT Operations, AI strategy, AI Transformation, Artificial Intelligence, digital transformation, Enterprise IT Management, Events & Conferences, Industry Experience / Leadership, IT Innovation, IT Leadership Insights, IT Management, ITSM Automation, ManageEngine Bengaluru, ManageEngine User Conference, Partner Ecosystem, Shailesh Davey, Spritle Blog, SpritleSoftware, Technology Conference, Vision 2026, Zoho Corporation

Hi, I’m Karthi, QA Manager, and I recently had the opportunity to attend the ManageEngine User Conference in Bengaluru (Feb 19–20), along with our VP of Sales, Sriram. I went in expecting a typical technology conference — product announcements, feature updates, and technical discussions. I came back with something far more meaningful. Perspective. This wasn’t

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What is An AI Strategy and Why Every Business Needs One

AI For Business, AI strategy, Artificial Intelligence, Business News, Startups, undefined

This article discusses what an AI strategy means, the different types of AI strategies that you should know about, and how as a leader you can get started with an AI strategy. Table Of Contents What Is An AI strategy?Why Do Businesses Need an AI Strategy?Product Level AI StrategyBusiness Unit Level AI StrategyOrganizational Level AI

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3 Strategic Mistakes Leaders Can Easily Avoid When Thinking About AI Integration

AI For Business, ai for leaders, AI in Business, ai mistakes, AI strategy, Artificial Intelligence, Investments

Several years ago, a product manager at a tech company had a data collection problem: to scrape software security vulnerability data from multiple web sources, consolidate the vulnerabilities and store them in a database.As this was an automation problem relating to data, the product manager (PM) immediately concluded that this was a machine learning problem.

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Even if AI is Your Goal, Why Starting Without AI Improves Outcomes

AI For Business, AI strategy, Artificial Intelligence

When it comes to software automation, many teams turn to AI as their potential answer. AI in the form of machine learning or NLP may be an excellent solution to a problem. But did you know that the best way to start AI initiatives is to start with no AI at all? This may seem counterintuitive, but there’s a simple reason for it. It’s because you may not be

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