Leveraging the 4 Vs of AI for Successful Integration

Eager to gain a competitive edge, many organizations rushed to implement artificial intelligence (AI) in recent years. For most, however, the results have been underwhelming, with some estimates suggesting that more than 80 percent of AI projects fail. But AI hasn’t failed because the technology wasn’t ready; it failed because businesses treated it like just another tech project.

The first wave of AI initiatives were mostly spearheaded by IT or data teams. These early projects were technology-centric and often disconnected from the broader corporate strategy. And while that might have worked for past tools, AI isn’t like other technologies. It’s different in that it affects how people work, how value is delivered, and how fast organizations need to move.

With that wave firmly behind us, the question now isn’t whether to use AI. It’s how to do it in a way that drives real impact. AI is no longer something to experiment with off to the side. It’s here, it’s moving fast, and it’s already making a difference for companies that know how to use it.

Leaders who are already grappling with a lot (including market uncertainty, tighter budgets, and rising customer expectations) can benefit from a practical guide for building AI into the way their organizations think, operate, and grow. The 4 Vs framework—vision, value, viscosity, and velocity—offers a path to move from experimentation to execution.

Vision: Embed AI in the Business, Not Beside It

Too often, AI is treated as a side project. But if it’s going to stick, AI needs to live inside the business strategy, not outside it.

This isn’t about building an “AI strategy.” It’s about making sure your AI efforts are clearly in service of your corporate strategy. When organizations think of AI as an enabler, rather than the destination, it becomes easier to connect investments to real outcomes.

Think about it like electricity. You don’t walk around thinking about it all day, but it powers just about everything you do. That’s where AI is headed. Successful AI integration is more than launching a shiny new initiative. Organizations that thrive in the coming years will seamlessly weave AI into how work gets done across the board.

How to get started: Integrate AI directly into your strategic focus areas, rather than managing it as a separate initiative. When corporate governance, resource allocation, and measurement frameworks reflect AI’s role as a core enabler, alignment comes naturally.

Value: Redefine How People and Organizations Create Value

When it comes to value, there are two sides to the story. First, you have the customer: What do they actually value from you? And how does AI help you protect, amplify, or reimagine that? AI is rapidly dismantling what were once believed to be highly defensible competitive advantages. Successful organizations will leverage AI to understand and meet their customers’ rapidly evolving expectations with speed and precision as a means to remain their preferred option.

Then there’s the employee side: Most people define their value by the tasks they complete every day, so when AI starts taking those tasks off their plates, it can feel destabilizing. People wonder, “Where do I fit now?”  Fully 47% of workers in a May 2025 study expressed concern that AI would threaten their current jobs

This is where leaders need to help teams zoom out. The goal isn’t to do the same tasks faster, it’s to move the organization closer to its vision. That will require rewriting roles, shifting incentives, and rethinking what success looks like. But it’s worth it, because when people feel like they’re part of something bigger, they show up differently.

How to get started: Write job descriptions for AI “teammates” just as you would for human roles. Define what they own, how success is measured, and how they support their human counterparts. This clarity helps teams move past the fear of being replaced and toward the opportunity to work differently.

Viscosity: Become Less Like Peanut Butter, More Like Water

Every organization has a certain viscosity—how easily change moves through it. Some companies are like water, with changes flowing smoothly. Others are like peanut butter, with changes getting stuck.

AI is moving fast, and organizations that want to keep up can’t afford to get bogged down by bureaucracy or habit. Sunk cost is one of the biggest blockers. People get attached to old ways of doing things simply because they’ve invested time or energy into them. To decrease viscosity, leaders need to create space and incentives for people to let go of the past and embrace better ways of working. Given the speed at which AI continues to evolve, successful organizations will recognize that they must adapt an unprecedented pace to remain relevant.

How to get started: Revisit incentive structures to encourage adaptability over tradition. Build rewards around outcomes that reflect a willingness to embrace new ways of working. And recognize individuals and teams who challenge sunk cost thinking and choose smarter approaches.

Velocity: Treat AI Like a Promising Teammate, Not a Perfect Machine

The last V is about speed. With AI evolving by the week, the ability to move fast is non-negotiable. But many organizations often expect AI to be perfect right out of the gate. When it’s not, they abandon it.

That’s like expecting a new college hire to do everything perfectly on Day One. It doesn’t work that way. College hires are smart, capable, and committed, but they need context, support, and coaching to succeed. AI is the same. The long-term value you receive from your AI initiatives will be directly correlated to the willingness of your team members to commit to their continuous improvement.

Instead of waiting for perfection, organizations should start with low-risk areas where the stakes are manageable but the learning is real.

How to get started: Designate “safe-to-fail” zones—internal use cases where the cost of a mistake is low but the learning potential is high. Meeting summarization, policy lookup, and early-stage idea generation are common entry points that allow teams to build confidence before scaling.

The Future Is Embedded

There’s a mindset shift that matters here, too. One oft-repeated story says it all: During a visit to NASA in the 1960s, President Kennedy reportedly asked a janitor what his job was. He said, “Well, Mr. President, I’m helping to put a man on the moon.” That’s the kind of alignment organizations should aim for. Whether it’s a frontline worker or an AI tool, everyone and everything should be working toward a shared purpose.

But getting there won’t be tidy. AI is moving fast, and the world around us is shifting just as quickly. It’s okay to feel excited one day and uncertain the next. That tension is real, and it’s normal. As Wharton AI professor Ethan Mollick says, you don’t really understand AI until you’ve had three sleepless nights thinking about it.

The truth is, we’re all figuring this out in real time. There’s no perfect roadmap. What matters is showing up with clarity, intention, and a willingness to learn. That’s how transformation happens.

The 4 Vs framework helps make that shift. When organizations connect AI to realization of their corporate vision, define its value, lower their internal viscosity, and build the muscle to move with velocity, they unlock change that sticks. The tech is ready, and the moment is now. Take a breath, embrace the discomfort, and get to work.