AI Adoption is Stalling. Here’s Why Leaders Need to Rethink Their Strategy

Introduction

AI is no longer a futuristic concept. It’s here, it’s accessible, and it’s easier than ever to deploy. With off-the-shelf tools, businesses can quickly integrate AI into their operations, reducing workloads, accelerating research, and unlocking insights in seconds.

The conversation has shifted. It’s no longer about if companies should adopt AI, but how fast they can adopt.

Some AI-ready businesses are already seeing massive returns. Take Klarna, for example.

Klarna needed to handle growing customer service demands without sending costs through the roof. They launched an OpenAI-powered assistant that runs 24/7, operates in 35+ languages, and supports customers in 23 markets. To make AI a natural part of their operations, they paused hiring and empowered teams to reshape their workflows. No layoffs, no disruption—just a smarter way of working.

The results?

The AI assistant now handles two-thirds of customer chats, the equivalent of 700 agents.
Resolution times dropped from 11 minutes to 2.
Repeat inquiries fell by 25%.
It was projected to add $40 million in profits by the end of 2024.

This is AI done right. But for every Klarna, there are countless companies struggling to see results.

Why AI Adoption is Stalling

AI represents a $1 trillion investment opportunity, yet most businesses haven’t figured out how to turn that investment into real value.

Boston Consulting Group found that only 4% of companies are seeing significant, repeatable returns from AI. A staggering 74% still haven’t cracked it.

The problem isn’t the technology. AI itself isn’t the barrier. The real issue is how businesses approach adoption.

We keep seeing two big mistakes:

1. Leaders Assume Employees See AI the Way They Do

AI means different things to different people. Some see it as a game-changer. Others fear it will take their jobs.

A Microsoft survey found that:

90% of employees believe AI helps them save time.
85% say it helps them focus.
84% say it sparks creativity.

At the same time, many employees feel uneasy about AI. They don’t trust it. They worry it’s a “black box” making decisions they can’t control. Some don’t believe it will actually help them in their day-to-day work.

Leaders often assume employees will naturally embrace AI. That assumption is a major risk. If employees don’t understand or trust the technology, adoption will fail.

Instead of pushing AI onto teams, companies need to start by listening. What are employees’ biggest concerns? How do they see AI fitting into their work? Once leaders understand that, they can design AI initiatives that actually address people’s needs.

When employees feel heard, they don’t just tolerate AI. They take ownership of it.

2. Companies Move Too Fast and Lose Buy-In

The pressure to adopt AI quickly is huge. Nobody wants to fall behind.

But rushing implementation is one of the fastest ways to derail adoption.

When employees are thrown into unfamiliar workflows, many revert to old methods. Some avoid the technology altogether. Others use it incorrectly, leading to frustration rather than productivity. The result? A tool that was meant to boost efficiency ends up sitting idle, while teams go back to business as usual.

AI adoption takes time and trust. People need to understand why a new tool is being introduced, what’s in it for them, and how it will make their jobs easier.

This is exactly why Klarna succeeded. Instead of forcing AI into their operations overnight, they gave teams the freedom to adapt. Employees weren’t left behind. They were part of the process.

AI Success Comes From Putting People First

A 2024 study from BCG revealed that 70% of AI adoption challenges are about people and processes—not the technology itself.

This is why some companies thrive with AI while others struggle. It’s not about having the best algorithms. It’s about bringing people along for the ride.

One of the most effective ways to do this is by identifying Change Champions. These are people within the organization who are naturally excited about AI and can help others see its value.

Change Champions can:

Surface employee concerns early, before they become blockers.
Validate AI use cases to ensure they solve real problems.
Act as role models, showing colleagues how AI makes work easier.

“You basically take a selection of champions and then you design the process with them, and if it works for them, then you get broader acceptance”

Victor Hoong, CEO of Riverflex

When companies bring employees into the process, AI adoption doesn’t feel forced. It becomes something people actually want to use.

How to Keep AI Adoption Moving Forward

A lot of companies launch AI pilots. Far fewer sustain them.

Start Small, Think Big

AI isn’t a one-time transformation. It’s an ongoing evolution. The companies that succeed with it aren’t the ones making the biggest investments upfront, but the ones that start where it matters most and scale from there.

The key is minimal viable integration—focusing on the smallest, most impactful steps to embed AI into workflows. Starting small builds confidence. It gives teams time to adapt and refine solutions before expanding AI across the business. Leaders need to reinforce that AI adoption isn’t about reaching a “final state” but about continuous improvement.

Short-term goals (6-12 months) with clear benchmarks for success keep teams focused. It also prevents overinvesting in projects that take years to pay off. When employees see quick wins, it builds momentum, making further adoption easier. Change also needs to be part of the culture. Innovation shouldn’t feel like an occasional disruption—it should be the norm. When employees are equipped to adapt, businesses stay resilient, no matter how AI evolves.

Beyond the Pilot: Making AI Stick

Launching an AI pilot is an achievement, but it’s not the finish line.

Early excitement often comes from seeing how AI fits into daily workflows, but long-term success requires more than just a strong start. As AI scales, companies need to refine data, adapt workflows, and ensure AI aligns with broader business goals.

This next phase isn’t about what AI can do—it’s about how to scale it while keeping people at the center. Organizations that get this right will see AI adoption thrive. Those that don’t risk stalling out before they see the real impact.

Final thought: AI Isn’t the Challenge. Leadership Is.

The companies that get AI right aren’t just investing in technology. They’re investing in people.

They know that AI adoption isn’t about launching the most advanced tool or automating as much as possible. It’s about trust, alignment, and ensuring AI works for the people using it—not against them.

Leaders who succeed with AI take a deliberate, human-first approach. They create space for employees to understand and engage with AI rather than forcing change from the top down. They listen to concerns before pushing implementation. They identify early adopters who can champion AI across the business. They make AI a tool that empowers teams, not something that replaces or disrupts them.

The companies that struggle often rush in without addressing these human factors. They assume employees will adapt without support. They measure AI success purely in technical performance rather than how well it integrates into real workflows. They focus on short-term efficiency rather than long-term transformation.

The real challenge isn’t the technology itself. It’s how well leaders design AI to fit into the way people think, work, and collaborate. Get that right, and adoption follows.

What’s been your biggest challenge with AI adoption? Discuss with Riverflex in the comments.👇

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