AI Anxiety Points to Organizational Capabilities

As always an informed and considered opinion from Jon. The change curve applies to the enterprise. As leaders we need to push through and support our people, everyone can buy the tools, the edge is creating the organisation to leverage the tools.

Why do conversations about AI so often circle back to the same concerns? According to Jon Webster, COO at CPP Investments, it may be because organizations are trying to solve the wrong problem. In his latest column, Jon argues that AI-related worry is not primarily about technology. It is a symptom of a deeper challenge: building the organizational structures needed to manage a rapidly changing environment. The question isn't how to eliminate the worry. It's what the worry is telling us to build next. Read his latest column at CPP Investments Insights Institute “Why Worry? AI Anxiety Is Structural:” https://lnkd.in/gZ3pFDid #CPPInvestments #InsightsInstitute #LeadershipPerspectives #EmbeddingEdge #FutureOfWork 

Organizations are investing heavily in AI. Many are also grappling with uncertainty about how it will reshape the way they work. In his latest column, Jon Webster, COO at CPP Investments, argues that this uncertainty shouldn't automatically be viewed as a problem to solve. Instead, it may be a signal that organizations are still building the structures, processes and shared language needed to operate effectively in an AI-enabled world. The challenge isn't simply adopting new technology. It's creating the organizational architecture that allows people to use it with confidence.  Read his latest column at CPP Investments Insights Institute “Why Worry? AI Anxiety Is Structural:” https://lnkd.in/gZ3pFDid  #CPPInvestments #InsightsInstitute #LeadershipPerspectives #EmbeddingEdge #FutureOfWork

We are at AI4 in Las Vegas this week, and we have some questions. 🎬 The numbers around AI investment and return are genuinely troubling. Trillions going in, 6-30% seeing any return. We think we know a few of the reasons why. 👇 Shadow AI. Agent sprawl. The reasoning trap. Sovereignty paralysis. Budget shock. These are not new and abstract concepts. They are the measurable reasons why the dream of AI productivity that so many organisations were promised still feels like a 'mirage' for most of them. 👀 We are shooting a documentary series on the ground here this week, putting these questions directly to the tech leaders and executives who are closest to the problem. What does genuine organisational readiness for AI actually look like? Who is getting it right and how? And what needs to change before that 6% starts to look more like 60%? 💬 If there is a question you think we should be asking the leaders we meet this week, drop it in the comments.

The AI era is redefining value creation, creating new opportunities for businesses to rethink growth, talent, and transformation.   Gryphon Operating Partner Vikram Mahidhar Mahidar shared with Subhro Mallik on Talking Breakthroughs perspectives on how AI is reshaping private equity, influencing investment strategies, and driving business reinvention. Vikram also discusses what it will take for organizations to move beyond experimentation and unlock lasting value from AI. Watch the full conversation: https://lnkd.in/gj8Xq_aT

It's important to remember that, until, if, or when, AI takes all the jobs, companies are still made up of people. Real people. And because of that fact, we need to shift our thinking away from this generalized organizational lens to an individual one. The #1 need of employees when it comes to change? Experimentation and practice. The #1 reason why change fails according to those same people? Those same people don't get it. I'd say it's not rocket science (because that's true), but it is, in fact, science. Change is rooted in a mixture of science of learning, stress, motivation, repetition, failure, and more. It's not governed by an artificial timetable or a derived return on investment (ROI). The wave of AI implementation pilots is demonstrating this everyday. What started as a story of riding the wave of AI transformation has turned into an odyssey (...too easy...) of real people struggling through the practice of shifting decades of hard earned behavior. Maybe this time we'll learn the lesson. Michael J Lopez Consulting #rethinkingchangemanagement

Artificial intelligence has moved from technology budget to the balance sheet, forcing companies to decide simply not how much to spend, but which parts of the AI stack they must control. In our recent article, Breakwater Capital Markets believes businesses that are able to turn AI into stronger growth, margins and resilience while protecting critical data, infrastructure and market access will command a “Sovereign AI Premium”. Those companies that become overexposed to costly infrastructure, concentrated suppliers, regulatory fragmentation or rapid obsolescence risk an “AI Dependency Discount”. In our view, the winners will be the companies that combine disciplined capital allocation with credible governance, operational flexibility and a clear explanation of how AI investment translates into durable returns. Learn more about Breakwater Capital Markets from our website: https://lnkd.in/enUSwUYh Breakwater Capital Markets: Driving the Global IR Thought Leadership Conversation

By Stantin Siebritz Artificial intelligence is entering a defining new phase. After years of breathless headlines, billion-dollar investments and promises of disruption, business leaders are beginning to ask a tougher and far more important question: where is the return on investment? Like many technological revolutions before it, AI has moved beyond the excitement of possibility and into the scrutiny of performance. In 2026, success will not be measured by who has the most advanced model, but by who can apply AI in ways that create measurable business value. For African businesses, this shift could not come at a better time. The AI Advantage Is No Longer Reserved for Big Tech For much of the past two years, the narrative around AI was dominated by a handful of global technology giants. https://lnkd.in/dyBRq3ZS #namibia #ai #investment #businesses #value

“If you don’t know where you’re going, any road will get you there.” It is one of the best-known ideas from Alice in Wonderland. But in organizations, I’m not sure it is true. Often, we genuinely don’t know where we need to go. The problem is new. The context is changing. No solution has been validated yet. And sometimes we can only discover what works by moving forward. Still, that does not mean every path is equally useful. When the destination is uncertain, the best path may not be the one that promises the fastest arrival. It may be the one that helps us learn while moving. One that: -makes our assumptions explicit; -produces signals we can observe; -reveals early when we may be wrong; -limits the cost of failure; -preserves alternative routes; allows us to change direction before a mistake becomes structural. This becomes even more important when introducing AI into organizations. AI can accelerate decisions and scale execution. But without the ability to observe, learn and correct, it can also institutionalize the wrong decision much faster. So, before asking: “How can AI accelerate this process?” Perhaps we should ask: “What are we trying to learn?” “What would tell us that our hypothesis is wrong?” “And until when can we still turn back?” Transformation is not about knowing the entire path in advance. It is about building the capacity to discover the path without becoming trapped by the first direction we choose.

“We’re now, like, in the singularity.” No, Sam. We are, like, not. We are witnessing extraordinary progress in AI. But progress, even exponential progress, is not the singularity. Today’s systems do not autonomously redesign, train, deploy and continually improve their successors without substantial human direction, infrastructure, capital and carefully constructed feedback loops. They remain brittle. They hallucinate. They fail outside familiar distributions. They depend on human-defined objectives, human-built evaluation systems and an enormous human-operated supply chain. Calling this “the singularity” is not visionary. It is technically dishonest and institutionally reckless. Words matter, particularly when they come from the CEO of one of the companies building this technology. If the singularity has already arrived, then every failure can be framed as unavoidable. Every demand for oversight can be dismissed as resistance to history. And every commercial milestone can be sold as evidence of an unstoppable transformation. That is a very convenient narrative for the companies raising unprecedented amounts of capital to build it. AI does not need more mythology. What it needs are precise definitions, honest capability assessments and leaders who understand that shaping public perception is part of their responsibility. What we have achieved is remarkable enough. There is no need to turn it into science fiction.