Most AI strategy initiatives don’t fail because of the tool. They fail because the IT foundation underneath them isn’t ready. Artificial Intelligence has moved from experimentation to expectation, and executive teams are under pressure to “do something with AI.” Most are acting before they’ve asked whether their organization is structurally prepared to realize value from
Higher education leaders are navigating an increasingly complex environment, and often doing it without a shared, trusted view of the data underneath them. The scenario is familiar to every institution: the cabinet is reviewing a major decision (a program to cut, a building to renovate, a new student segment to recruit), and the conversation stalls because no one in the
6 Ways Associations Can Use AI to Strengthen Member Value and Operational Efficiency Association leaders are navigating rising expectations by finding new ways to create value and differentiate. Delivering on that promise requires meeting higher member expectations for personalized experiences, equipping staff with integrated, effective systems, and providing leadership with clear, actionable insights. All of
Artificial intelligence is dominating boardroom conversations across the mid-market. Leaders are under pressure to “do something with AI,” often fueled by headlines, vendor promises, and peer activity. The result is a familiar pattern: organizations move quickly to adopt tools without a clear understanding of how those tools connect to business problems and business outcomes. A
For mid-market companies, AI is no longer a future opportunity. It’s a present-day force with the potential to reshape every function of the business. Yet with this progress comes a critical leadership responsibility: to balance innovation with governance. As AI adoption accelerates, boards and executive teams are rethinking risk, oversight, and accountability structures to ensure
AI is transforming the way businesses operate, but most mid-market companies struggle to capture its value. Roughly 85% of AI initiatives fall short of expectations, and nearly 75% never reach full production. The issue isn’t technology; it’s the lack of a clear, actionable strategy. Without a defined AI strategy, organizations risk fragmented efforts that waste
Manufacturers today face unprecedented demand volatility. Consumer preferences shift overnight, supply chain disruptions ripple unpredictably, and economic uncertainty makes planning more difficult than ever. The problem isn’t just volatility. It’s the fact that most companies are still planning with outdated processes. Monthly or weekly planning cycles simply can’t keep up with real-time demand shifts. By
“How do we make sure our AI projects actually deliver business value?” It’s a good question that executives are asking, and an urgent one too. AI is moving fast, and most organizations are still figuring out how to go from early experiments to measurable results. Here’s the hard truth: most AI projects don’t deliver. Studies
Local government officials face rising expectations with limited resources. Citizens demand faster services, better communication, and easier access to information. Unfortunately, many local governments still rely on outdated systems that hinder efficiency. To combat this, leaders are increasingly turning to modern tools to address these challenges, particularly by leveraging AI. According to a 2024 report
As we approach 2025, the health and human services industry is undergoing remarkable shifts driven by advancements in technology, an increased focus on engagement, and a growing emphasis on digital accessibility. These trends are not only reshaping operational strategies but also transforming how provider organizations interact with individuals under their care. Here are the top
