Dana Berg is the Chief Executive Officer of SADA, An Insight company.
As leaders, we’re constantly evaluating how technology can drive meaningful results. For years, cloud adoption centered largely on transformation aimed at efficiency—optimizing infrastructure, improving security operations and ultimately, saving costs. That was necessary, foundational work—the essential “plumbing,” if you will—for modern business.
But the landscape as we look toward the rest of 2025 is dramatically different. Today, the promise of AI integrated with the cloud isn’t just about trimming expenses; it’s about fundamentally reinventing how we generate value. There’s often an assumption that if the technology is powerful, adoption will automatically follow. But history shows even brilliant solutions can falter if the people meant to use them aren’t truly part of the journey.
We’re now exploring use cases aimed squarely at the top line: driving new revenue streams, deepening customer engagement and reducing churn. It’s fascinating, really. The question has shifted from “How can technology save us money?” to “How can technology help us grow?” Yet, while the potential is electrifying, a critical question looms: The technology is advancing at breakneck speed, but are our organizations, and specifically our people, ready to harness it?
The Readiness Paradox: Technology Races Ahead
We are witnessing remarkable progress in GenAI, with powerful, sophisticated models and increasingly accessible tools that are well-equipped to solve complex business challenges. In my role leading a company immersed in this ecosystem, I see the potential firsthand every day. The technology, in many respects, feels ready for prime time.
However, there’s a growing paradox. While technology surges forward, organizational readiness often lags. As I’ve discussed with leaders and observed in the market, the primary bottleneck to realizing AI’s value isn’t usually the tech itself; it’s often us, the humans. Think about past technology initiatives in your organization. Were the biggest hurdles the tech itself or driving adoption and ensuring teams could effectively leverage the new tools?
More often than not, the challenges are human-centric. Are our teams equipped with the right skills? Is our company culture conducive to adopting new ways of working? Do our people feel comfortable and empowered, rather than threatened, by AI?
The technology might be ready, but I’m not always sure the people are. For businesses of all sizes, this gap isn’t just a missed opportunity; it’s a competitive risk. Failing to bridge it means leaving value on the table and potentially falling behind on innovation, customer experience and crucial growth opportunities.
Activating Your Workforce: Bridging The AI Adoption Gap
So, the real question becomes, how do we close this critical readiness gap and move from discussing AI’s potential to achieving AI-driven profit? Bridging this gap requires moving beyond simply deploying technology; it demands embracing core principles of organizational change management focused squarely on your team. Here are a few strategies I believe are key:
1. Start with practical productivity.
Don’t begin with massive, complex AI projects. The journey to AI adoption should begin where employees can see immediate, tangible benefits in their daily work.
A key aspect of effective change is clearly communicating the “why” and the personal benefit. Prioritize deploying user-friendly AI assistants within existing productivity suites—tools that help draft emails, summarize meetings, analyze data or generate creative first drafts. Let your team experience AI as a helpful collaborator first, allowing them to build comfort and acceptance organically. To really shift hearts and minds inside your enterprise, start with knowledge workers.
2. Cultivate an AI-ready culture.
Technology adoption is as much about mindset as it is about tools. Leaders must actively foster an environment where experimenting with AI feels safe and encouraged—what I think of as giving people the “license to feel it’s acceptable.”
This isn’t just about morale; it’s effective change management. Launch pilot programs for specific teams to explore relevant AI use cases. Encourage internal champions to share successes and learnings. Normalize AI experimentation and provide targeted support. Create safe spaces for asking questions and address concerns about AI’s impact on roles transparently.
Even technical experts can resist change if they don’t see the value or feel supported. Remember, initiatives incorporating robust change practices are significantly more likely to achieve their objectives and deliver real ROI.
3. Leadership must light the way.
Adoption flows from the top. Employees look to leaders for cues on what’s important, a cornerstone of leadership alignment in any change effort. If leaders aren’t visibly embracing AI tools, it sends a message that adoption isn’t truly a priority.
As executives and managers, we need to actively use sanctioned AI tools ourselves and share our experiences—the efficiencies gained, the insights uncovered and even the learning curves. Your authentic engagement demonstrates commitment and encourages broader adoption throughout the organization. These steps aren’t just soft skills; this is essential work required to ensure your AI investments translate into tangible results.
Turning AI Potential Into Performance
Ultimately, turning AI’s potential into performance hinges on recognizing that technology is only half the equation. The true differentiator will be the organizations that invest deeply in their people’s journey with AI. By actively managing the human side of this shift— building skills, fostering acceptance, leading by example, all on a trustworthy foundation, you create the conditions not just for adoption but for the genuine innovation and competitive advantage that define the next era of business.
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