Leading Change

Leading Change

By Ema RoloffBusiness
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Leading Change episodes

  • When AI Marketing Gets Ahead of Reality
    Salesforce says it doesn’t regret laying off nearly 4,000 employees. It also says those layoffs weren’t really about AI. And it definitely says it trusts its AI models. So why do the headlines feel so contradictory?

    In this episode of Leading Change in the Wild, I break down the confusing and revealing signals Salesforce is sending about workforce reductions, Agentforce, and what trust really looks like when AI moves from pilot to production.

    📉 Here’s what I unpack:
    • Why Salesforce’s AI driven layoff narrative never quite added up
    • How mixed messaging from leadership is fueling confusion and skepticism
    • What internal comments reveal about trust, accuracy, and AI readiness
    • Why clean data, governance, and business logic are being re emphasized
    • What Salesforce’s pivot back toward rule based automation signals for the broader market
      • AI is not magic. It is a tool. And when even the largest software companies are recalibrating expectations, leaders need to pay attention.

      This moment is a reminder that AI first is not a strategy. Real value still depends on people, process, and foundations that cannot be skipped.

      👇 Let’s discuss:
      What do you make of Salesforce’s shifting narrative?
      Are you seeing similar disconnects between AI promises and reality in your organization?

      🔔 Subscribe for weekly insights on digital transformation, change management, and emerging technologies.
      12 min
    • The AI Vibe Shift in the Enterprise
      AI adoption at the enterprise level isn’t living up to the hype—and the “magic wand” promise of tools like Microsoft Copilot may be wearing off.

      In this episode of Leading Change in the Wild, I delve into what’s happening behind the scenes of enterprise AI adoption, why some tools are underperforming, and what this means for leaders navigating AI investments.

      📉 Here’s what I unpack:
      • Why Microsoft Copilot isn’t seeing the adoption expected across enterprises
      • How top-down directives fail to drive real AI adoption
      • Why using AI as a “checkbox” leads to wasted licenses and disappointed teams
      • The lessons leaders can take from hype versus reality when introducing AI tools
        • AI is a powerful tool, but it isn’t a strategy. Success still requires real work with your team, clear processes, and understanding the problems you’re trying to solve.

        👇 Let’s discuss:
        Are you seeing a similar AI adoption “vibe shift” in your organization?
        How are you ensuring your team and processes are ready before bringing in new AI tools?

        🔔 Subscribe for weekly insights on digital transformation, change management, and emerging technologies.
        15 min
      • Is the Metaverse Finally Dead?

        The year was 2021 and we were all told that virtual worlds were the future. Now, in 2025, Meta is reportedly preparing to cut its metaverse budget by up to 30%.

        In this episode of Leading Change in the Wild, I take a closer look at what this shift really means, how investors are responding, and why Meta might be turning its full attention toward AI and wearable technology instead.

        Here’s what I unpack:

        ✅ Why Meta is pulling back on a 60 billion dollar metaverse investment and why investors cheered
        ✅ Where that money is likely heading next, from AI infrastructure to wearable tech like Meta glasses
        ✅ Why wearables may become the next major data source for training AI models
        ✅ The privacy and ethical concerns tied to always-on, data-collecting devices
        ✅ Why the metaverse is a cautionary tale for leaders jumping into AI without a clear strategy
        ✅ How to avoid chasing hype and instead use technology to solve real business problems

        For years, people made it clear they didn’t want to live in a virtual world built by Big Tech. Now we’re seeing what happens when companies chase hype instead of listening to their customers. The same warning signs are showing up in today’s AI race.

        👇 Let’s discuss:

        - Is the metaverse really dead, or are we still in the early days?
        - Would you use AI-powered glasses in your daily life?
        - Is your organization leading with technology or strategy when it comes to AI?

        🔔 Subscribe for weekly insights on digital transformation, AI, and the human side of technology.

        11 min
      • Are Insurers Ready for AI Risk?
        Are nuclear plants, spaceships, and oil rigs riskier than AI? Some insurers believe AI poses a greater risk.
        In this episode of Leading Change in the Wild, I take a close look at how major carriers like AIG, Great American, and WR Berkeley are approaching AI risk—and what that means for leaders and organizations betting on this technology.

        📉 Here’s what I unpack:
        • Why carriers are asking to limit AI liability coverage
        • How real-world AI mishaps—from chatbot hallucinations to deepfake fraud—are creating concern
        • Why agentic AI introduces systemic risk that could trigger thousands of simultaneous claims
        • What recent cloud outages at AWS and Microsoft reveal about scale, dependency, and exposure
        • Why AI’s “black box” nature makes it nearly impossible to price risk accurately
        • How this shift could impact AI-first companies that assumed insurance would back them up
        • The key questions leaders need to ask their brokers before diving into AI
          •  
          Insurance has traditionally been there to catch the risk when we experiment, innovate, or try something new. But with AI, we’re entering uncharted territory, and companies need to think carefully about risk before jumping in.

          👇 Let’s discuss:
          Should insurers be able to limit AI coverage?
          How is your organization weighing risk versus reward when using AI?

          🔔 Subscribe for weekly insights on digital transformation, AI, and the human side of technology.
          8 min
        • Is Your Organization Ready for AI?

          AI is showing up in every strategy deck, every board meeting, and every company roadmap. But if you look closely, most AI initiatives are quietly failing long before they ever deliver value.

          In this episode of Leading Change in the Wild, I sit down with Brandy Ferrer to break down the real reasons AI projects fall apart and what leaders can do to keep their investments on track.

          📉 Here’s what we unpack:

          • Why “AI first” mindsets push teams to chase hype instead of solving real problems
          • How unclear goals and poor communication derail even the best technical solutions
          • The role culture plays in whether employees adopt or reject new AI tools
          • Why companies overestimate the technology and underestimate the human side
          • What leaders can do to design AI initiatives that actually stick

            • AI isn’t magical. It isn’t plug-and-play. And it isn’t a shortcut.

            It’s a tool that only works when we prepare our organizations to use it well.

            👇 Let’s discuss:

            Where do you see AI initiatives breaking down in your industry?
            What’s one thing leaders should focus on before implementing AI?

            52 min
          • Salesforce, Synthetic Data, and the Death of AI Trust
            Is synthetic data the solution to "jagged" enterprise AI... or the fast track to Model Collapse?

            We just got used to "Agentic AI." Now, Salesforce is defining the next frontier of automation with the new term Enterprise Generalized Intelligence (EGI) and betting big on synthetic data to train its new Agent Force solutions. But is this the right path for enterprise trust?

            In this episode of Leading Change of the Wild, I dig into Salesforce's move and the massive risks involved in training AI on "fake" data.

            Here’s what I explore:

            • What Salesforce's new term (EGI) really means and why they introduced it.
            • The argument for synthetic data: cost savings, compliance (HIPAA), and mitigating historical bias.
            • The critical risk of Model Collapse when AI models are trained on their own generative outputs.
            • When synthetic data makes sense (e.g., self-driving cars and fraud detection) versus general enterprise use.
            • The paradox: Using synthetic data to smooth out models may introduce new, unverified bias and hurt trust.

              • The goal is 100% accurate, trustworthy AI. But training models on data that was literally designed to mimic human output might be the opposite of what's needed for lasting organizational trust.

              👇 Let’s discuss:

              Do you believe synthetic data is a viable path to increasing AI trust and accuracy in the enterprise?

              Should models be honed with proprietary data or a specialized synthetic environment before deployment?
              11 min
            • Is the AI Bubble About to Burst?

              AI is fueling record-breaking valuations, trillion-dollar companies, and endless hype. But… are we living in a bubble?

              In this episode of Leading Change in the Wild, I dig into what’s really happening behind the scenes of the AI boom and what it could mean for leaders and organizations betting big on this technology. 📉

              Here’s what I unpack:

              • Why Nvidia’s $5 trillion valuation has leaders divided
              • What Bill Gates and Sam Altman are saying about overhype and dead-end investments
              • How “circular funding” between AI giants could unravel if investors start demanding returns
              • The parallels between today’s AI surge and the dot-com bubble
              • What business leaders can do to stay grounded and make AI work for them

                • AI isn’t going anywhere, but the way we use it will define who thrives and who disappears when the hype fades.

                👇 Let’s discuss: Do you think we’re in an AI bubble? What steps is your organization taking to ensure AI investments create real value?

                12 min
              • Will AI Kill the Cloud & SaaS?
                An AWS outage took down apps around the world this week and it exposed a bigger question about the future of cloud, SaaS, and AI-first strategies.

                In this episode of Leading Change in the Wild, I break down what happened during the Virginia data center failure and what it signals for organizations that are pushing automation, AI decision-making, and cloud dependency deeper into critical infrastructure.

                Here is what I explore:
                • Cloud was supposed to make uptime safer, but automation took the system down
                • AI-first strategies are removing humans from the loop while infrastructure is getting more fragile
                • Enterprises are rethinking disaster recovery when everything runs in the cloud
                • Subscription fatigue is driving a return to building and hosting in-house
                • The pendulum may be swinging back from SaaS and cloud to proprietary and on-prem
                  • My biggest question is this. If automation and cloud fail, what will still work when we have removed the human expertise that was used to manage the system?

                  👇 I would love to hear your take:
                  - Are outages like this a warning that we bet too much on cloud and automation?
                  - Do you see companies starting to build in-house again instead of buying subscriptions?
                  11 min
                • Big 4 Consulting & AI with Ian McCain

                  Would you settle for a partial refund on a $440,000 report that used fake sources generated by AI?

                  That’s exactly what happened in what headlines are calling “The Blunder Down Under.” Deloitte reportedly delivered a government audit built on fabricated citations, and only after being caught did they admit the “sources” never existed.

                  In this episode of Leading Change in the Wild, Ema Roloff and Ian McCain unpack what this story reveals about the growing human intelligence problem behind our obsession with AI efficiency.

                  Here’s what they explore:

                  - How Deloitte’s AI blunder exposed a lack of digital literacy at the highest levels
                  - Why “AI-first” doesn’t mean “think later”
                  - What real accountability looks like in an era of generative tools
                  - Why leaders need to build critical thinking alongside AI fluency

                  This isn’t just about one consulting firm. It is a wake-up call for every organization chasing the next big tech trend without understanding the risks.

                  👇 Drop your thoughts in the comments:

                  - Do you think AI tools are making us smarter or lazier?
                  - How is your organization balancing speed with accountability?

                  🔔 Subscribe for weekly videos on digital transformation, AI, and the human side of technology.

                  41 min
                • AI Isn't Going to Steal Your Job

                  The headlines say AI is taking everyone’s jobs… but the data doesn’t agree.

                  In this episode of Leading Change in the Wild, I break down a new report from Yale’s Budget Lab that challenges everything we’ve been hearing about AI-driven disruption. 

                  Here’s what the data actually shows:

                  - Generative AI is shifting jobs at the same pace as past tech waves like the internet and computers
                  - AI adoption is slowing among large enterprises because ROI isn’t matching the hype
                  - The biggest “disruption” is happening inside the tech industry itself, not everywhere else
                  - We’re still nowhere near the workforce shifts of the 1940s and 1950s

                  So what should leaders do now?

                  Invest in upskilling. Focus on digital literacy. And help your teams prepare for how AI will change their work — not if it will replace them.

                  10 min

                About Leading Change

                From the publisher's feed

                Welcome to Leading Change, where we dive into the real conversations shaping the future of work. Hosted by Ema Roloff, this series brings together business leaders, change-makers, and innovators to explore the intersection of technology, change management, and leadership in today’s evolving workplace.