The experimental AI era is coming to an end. As we move into the second half of 2026, it’s time to turn questions into a clear path forward and ideas into action.
If you’re struggling with where to start, you’re not alone. It might feel as if every leader has their foot on the gas, accelerating AI across the enterprise. But from what we’re seeing in the industry and in conversations with our own clients, that’s not the case.
Many leaders still feel as if they are running in place. It doesn’t have to be the reality for them, or for you. Rising above the market noise and moving from AI questions to AI momentum begins with these three steps.
1) Solve for the right questions, not all the questions
Move from “How?” to “Now!” by narrowing your focus
If you’re still asking “where do I start?” or “what do I prioritize first?” you’re focusing on the wrong questions. Take a step back and instead ask: “Where can AI deliver the most value today?” or “what business outcomes are most important to the organization right now?”
Armed with this answer, you can narrow down to one high-impact use case or area of critical need. This gives your team a common, immediate goal that becomes the foundation for your broader AI strategy.
2) Find the friction, build your momentum
Proactively solve for issues before they impact progress
Once you’ve identified your use case, it’s important to think through what could hold you back. Both opportunities and obstacles need to be mapped for a strong AI strategy.
Consider:
- Which repetitive tasks, if eliminated, could free up teams for more value-added work?
- Where (whether teams or functions) might downstream AI training be needed?
- Where do most departments currently experience process bottlenecks?
Use this information to prioritize processes and build an AI strategy that will help minimize friction from the start.
3) Reframe Your Approach to Deliver Results
Think differently to think strategically
Once you’ve identified your AI north star and what could stall progress toward reaching it, you’re ready to begin building your AI strategy. The strategy itself will be specific to your unique business setup and desired outcomes, but at a high level should include: key stakeholders, outcomes-based KPIs to measure progress and success throughout the journey, detailed timelines, change management protocols, and technology integration roadmaps.
What we’ve seen work best with our own clients is to reframe your thinking to establish a best-fit strategy:
- Think workflows, not tools. Recognize AI as a crucial component of workforce and business transformation rather than simply a software tool.
- Think centralized ownership: Organizations that centralize AI ownership and governance versus appointing task forces or siloing responsibility are finding greater success.
- Think small to win big: Focus on an initial, high-impact, use case you can accomplish in months, not years to prove. Creating immediate value you can scale rather than struggling with unmeasurable ROI.
Jump-Start Your AI Strategy to Finish 2026 Strong
AI is moving fast. If your strategy needs a push, LaSalle is ready to help with our JumpStart AI engagement: we deploy AI experts to work alongside your team to assess your readiness, identify high-impact use cases, and stand up a live proof-of-concept. Reach out anytime to get started.
