AI is not a strategy…It’s a lever. Here’s where to pull.
“A strategy based upon just the technology is not a strategy. It’s a distraction!” — Jim Carroll
In our previous newsletter about marching with determination, we discussed teams piloting AI tools across marketing, finance, and operations. Some pilots succeed, while others fade without measurable impact. The challenge is not innovation, but momentum.
As I recently told a business leader, if your AI project is in IT, you are doing it wrong. IT is a part of the team, but AI should not be just another system to provision servers for or plug into your cloud. AI should be paired with a strategy that is integrated into your:
Decision-making
Products
Customer experience
Operations
Risk assessment(s)
Anywhere you can drive leverage or a competitive advantage is where you should implement AI to see results.
While one company tests small pilots for months, its competitor announces a full AI rollout in 18 months. Investors reward clarity. Customers reward speed. The difference is discipline.
Explore why AI is not a replacement for strategic thinking or real collaboration, but is a lever to remove friction and strengthen performance.
4 Principles To Implement AI & Make It Stick
AI should not replace strategic thinking. If it does, you did not have much to begin with. The best leaders do not ask “Where can we use AI?” They instead ask, “Where are we wasting time, sanity, or money?”
1. Start Where Friction Is Highest, Not Where It Is Flashiest
Avoid "innovation theater" by skipping the flashy announcements and solving real problems first. Identify where your teams spend hours on manual workflows like invoice processing, inventory tracking, or quality checks. Automate what is repetitive, measurable, and adaptable. When you solve for friction first, the business case builds itself.
2. Design The Smallest Viable Pilot
Small pilots reduce risk, shorten timelines, and surface integration challenges before you scale. You can do this in 3 simple steps by:
Selecting one high-friction process, and limit your scope intentionally
Using a clean dataset and an engaged team
Defining a single, measurable output that proves value without overcomplicating implementation
A focused pilot that works is worth more than an ambitious rollout that stalls.
3. Secure Buy-In Before You Deploy
Technical execution fails without emotional investment from the people who will use the system daily. Include your teams in the AI conversation early so they understand how AI supports their most time-consuming tasks. Invite feedback and allow them to help define their success. AI adoption follows ownership. Knowing your buy-in strengthens your approach. Even technically “sound” implementations can fail if it is misunderstood or unsupported across your organization.
4. Quantify ROI Before You Begin
Treat every AI pilot like a capital investment. Define metrics such as hours saved, error reduction, or faster decision-making before launch. If results cannot be measured within weeks, revisit the problem. Clear metrics build credibility, which means you can direct your resources to your highest priorities.
Time To Start Where The Friction Is Greatest
AI is not a destination. It is a tool that multiplies capability when applied with focus. Design small, measurable pilots, engage your people early, and track outcomes relentlessly.
Next, explore how to scale what works, retire what does not, and integrate AI into core operations responsibly. Sometimes, it takes a fresh perspective to help you identify where their real leverage lies. This is why business owners team up with Tamika Tyson to see where AI can transform their operations into advantages.
At SCALE, we make the improbable possible – Strategically Cultivating Acceleration Leveraging Expertise using our GPS Framework. Expect to break through barriers, scale your company, and maximize value so you can successfully exit or transition on your terms.