The 5 Must-Have Capabilities for GenAI Success

We're not constrained by AI—we're constrained by the limits of our imagination.

I see this play out in organizations every day. Leaders look at their current capabilities and work backwards: "This is what we can do, so this is what our strategy will be." Or worse: "There's so much we don't know, so we can't do these things."

That’s the wrong approach entirely.?

If we can imagine the value AI could create, we should focus on developing the capabilities to get there. Start with your aspirations, decide where you want to play and how you'll win, then build what you need to succeed.?

The challenge, of course, is figuring out what's feasible and which gaps you need to close. That's why I've developed a framework for examining the five critical areas of AI readiness.?

If you’re looking to assess where you are today—and more importantly, what you need to develop to achieve your goals—start here. ?

Area 1: Skills and Workforce Development?

This is often the hardest capability to develop. Most organizations have pockets of AI knowledge scattered throughout their teams. But what does an advanced AI-ready workforce really look like?

Three key elements matter:

? Skills Availability: Do your employees have the required technical and strategic skills? Advanced organizations ensure their workforce knows how to use AI, with continuous training and development keeping skills current.

? Formal Training: Whether developed internally or through partners like Coursera or LinkedIn Learning, you need structured ways to build and certify AI skills.

? External Talent Access: AI moves fast. You need a strategy for accessing specialized skills through partnerships or contracts, with clear ways to integrate external talent into your teams.

Area 2: Leadership and Culture?

In my 15 years of digital transformation work, one truth stands out—leadership and culture are the number one determinant of transformation success. Consider three critical aspects of AI adoption:

?? Leadership Alignment: Leaders need to understand and actively support AI adoption. In advanced organizations, they don't just stand back—they champion AI from the front, use it themselves, and drive transformation.

?? Innovation Mindset: The strongest organizations have a culture that's proactively innovative, with processes that support (not block) innovation. They can pilot new ideas with appropriate guardrails but without excessive overhead.

?? Change Management: Can your organization move seamlessly from one change to another? The best ones do, without change fatigue, because their change management capabilities are deeply integrated into their strategy.

Area 3: Processes and Operational Models?

AI capabilities fundamentally change how organizations operate. You need processes that support innovation, not block it.

Focus on:

?? Process Flexibility: Can your current processes adapt to new AI workflows? Advanced organizations have processes that aren't just adaptable—they already have built-in AI capabilities. This makes implementing new features straightforward.

?? Cross-functional Collaboration: AI rarely impacts just one department. The strongest organizations excel at pulling together project teams across functions, with strong support from all departments. This is crucial because AI often challenges traditional departmental silos.

?? Agile Frameworks: AI requires experimentation—trying something, seeing if it works, refining, and trying again. Organizations with established agile frameworks are far ahead because they already have this capability.

Area 4: Data Readiness and Governance?

Having data is one thing, but making it useful for AI is a different story. You’ll want to assess:?

? Data Quality and Access: If you put low-quality data into an AI model, you'll get low-quality results. But even if you have clean data, can you actually access it through APIs? Is it well managed over time? Do you have clear safeguards in place?

? Strategic Prioritization: One CEO I spoke with takes a smart approach: They greenlight initiatives where high-quality data is ready. When faced with a choice between an important initiative with messy data or a smaller one with clean data, neither choice is inherently better—what matters is making these decisions strategically.

? Governance: Proactive governance frameworks are crucial. You need to define who can access that data (and for what purpose), what permissions and guardrails exist, and how these controls can evolve over time.??

Area 5: Technology Infrastructure?

I often see organizations with great AI strategies, data, and processes... but systems that can't handle any of it. Many are still paying 'technical debt' - a backlog of updates needed before AI integration is even possible.

The reality is, you need your infrastructure to be flexible. Think of it as creating hooks throughout your organization. When I talk to leaders, they often ask, 'Which AI model should we use?' But that's not the right question. The key is building systems that let you plug in new models as they emerge, without rebuilding everything.

For this to work, you need three things working together:

?? An agile culture

?? Adaptable processes

?? High-quality data

Next Steps: From Assessment to Action

Once you've assessed your capabilities across these five areas, you face a critical decision for each gap: Build, buy, or partner?

Many leaders rush to buy or partner. But here's my strong recommendation: Learn to build first. Not because you'll build everything—you won't (and shouldn't)! But building experience makes you a smarter buyer and partner.

Let your capability assessment inform your roadmap, but don't let it define it. If a strategic initiative requires capabilities you won't have for months, develop them in parallel while working toward your goal. The key is to start now—you might be surprised by what's possible.

If this information was helpful, there’s plenty more!?

?? Sign up for updates and early access to my upcoming book , co-authored by Katia Walsh, which is all about creating a winning generative AI strategy.

?? Catch my most recent webinars:

• “Unlocking The Power of Generative AI.” I explain how to set up a generative AI “playground,” three ways to elevate your leadership with step-by-step instructions, and the broad outlines of creating a strategy. Get the recording and slides here.

• “Developing a Winning Generative AI Strategy for Competitive Advantage.” I walk through the steps needed to create a cohesive AI strategy that will last. Get the recording and slides here.?

Your Turn How are you assessing your organization's AI capabilities? Which areas present the biggest challenges for your team?