From SaaS to AI: the technological and cultural shifts leaders must confront

When cloud computing moved from “interesting experiment” to “default expectation,” you could almost feel the ground tilt. Those old systems that once felt rock solid suddenly looked heavy. Slow. Out of sync with how people actually worked.

Cloud-based platforms became the norm. On-prem systems faded. And teams got good — many too good — at centralizing work in ways that felt efficient, even innovative.

Now, here comes another shift. And it’s bigger. Generative AI is a new way of thinking, deciding and building. Gallup’s already seeing it; employees are using AI at nearly twice the rate they were just a year ago.

AI tools are helping them work smarter and move faster. And, just as important, it’s rewriting their expectations for how they solve problems and create what’s next.

But every leap forward brings friction. And this one challenges the very heart of culture.

The cultural friction leaders can’t ignore

AI brings obvious upside: productivity, efficiency and innovation gains. Gartner found that nearly two-thirds of leaders see AI materially improving innovation, and a significant portion are already reporting EBIT impact.

Yet the same technology that promises so much value also introduces new cultural tensions.

First, there’s fear. A recent Reuters/Ipsos poll revealed that 71% of workers worry AI could replace their jobs. Whether or not that fear is justified isn’t the point. It’s present, and leaders have to acknowledge it.

Second, AI is exposing performance gaps. High-clarity thinkers, strong communicators and people with deep subject-matter mastery tend to get better results with AI.

Meanwhile, those with less clear thinking or less confidence often struggle. AI becomes a mirror. It reflects differences in competency and confidence that were previously hidden.

Friction shows up when AI reveals things the organization isn’t ready to face. Clarity gaps. Uneven capabilities. Hidden assumptions about how work actually gets done.

What complicates the transition

Some companies are still operating primarily SaaS-driven workflows. Only a handful have truly integrated AI into their business operating system (BOS). AI adoption is happening around the edges. Leaders often remain hands-off, hoping the organization will “figure it out.” But that approach leads to uneven adoption, fragmented workflows and silent frustration.

Swinging too far in the other direction can be even worse. Push AI without a clear why, and you ignite resentment. Talk about efficiency without talking about growth, people assume “efficiency” is code for “cuts.” They tense up instead of leaning in.

Harvard Business Review highlights this gap: While 80% of executives believe they’ve communicated an AI strategy clearly, only 30% of employees agree. That divergence is where distrust grows and where retention risk skyrockets. If people don’t see a role for themselves in what’s next, they’ll start to question whether they belong at all.

How forward-thinking leaders smooth the transition

Successful leaders won’t sit back and wait. They’re the ones who’ll reframe AI from a threat to a development opportunity. They see AI as a catalyst for helping people grow in competency, clarity and confidence. And they communicate that clearly.

Here’s what that looks like:

1. Dial in the messaging

Humans are motivated by different things. Someone striving to grow into a role cares about different things than someone refining a craft they’ve spent years honing. The message that energizes one group may fall flat for another.

So you can’t just say, “AI will make you more productive.” As leaders, we have to connect AI to real growth, which is better problem solving, more time for high-value work and clearer thinking. When people understand how AI supports their goals, resistance drops dramatically.

2. Invest in training

Training is a flywheel that builds employee confidence and deepens commitment. The more we invest in people, the more they invest in the work. Training improves work output and increases resilience. Teams that feel capable stick around. AI training is the cost of staying competitive.

3. Lead by example

If our employees don’t know how we’re thinking about AI, they’ll default to what they’ve always done. That’s human nature. And even when they do understand the vision, the harder part is helping them see how AI can actually move them toward it. This is one of those moments where founders have a chance to lead from the front.

Use AI in the open. Let people watch you wrestle with a real issue or streamline a piece of work with its help. When your team can see what’s possible, the message lands. It sinks in more deeply. And it sparks the kind of curiosity and confidence that make AI adoption feel natural.

The opportunity in front of us

This transition from SaaS-centric operations to AI-powered work is both technological and cultural. It separates organizations that evolve from those that cling to outdated expectations.

Leaders have a choice: let AI adoption unfold in a scattered, informal way and allow uncertainty to undermine performance. Or lead with clarity, communicate openly, invest in training and help employees see how human creativity and AI capability complement each other.

One path leads to churn. The other leads to a more productive, humane and resilient organization.

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