AI Without Strategy Is Just Expensive Chaos
As we approach Salesforce’s TDX conference in San Fransisco, I’m energized by the prospect of new AI innovations and technical showcases. Yet before we immerse ourselves in demos and announcements, I want to emphasize something often overshadowed by the hype:
AI, on its own, is not a magic wand.
Over the years, I’ve worked with various SaaS companies and enterprise implementations. I’ve seen what happens when teams jump into AI without clarifying what they want to achieve. For example, a company rushed into digital transformation only to discover three months later that their data was incomplete and their sales process unclear. The result? Expensive chaos rather than true business transformation.
The Hard Truth About AI Implementation
The reality is straightforward but vital to understand: If your underlying business process is broken, AI will simply help you fail faster. It amplifies what’s already there—both your strengths and your weaknesses.
Without a clear, measurable goal, AI often becomes a solution in search of a problem. Sure, it can impress in demos or POCs. But in production environments, it fizzles because no one has fully defined the real-world need it’s supposed to address.
Strategy First, AI Second
The most successful AI initiatives I’ve witnessed always begin with a clear vision of desired outcomes. Leaders map out the specific processes they want to improve and develop a thorough understanding of the current state. Only then do they bring in AI to optimize those processes.
This mindset ensures AI remains the enabler, not the end goal. It might mean holding off on flashy new capabilities until you’re certain they align with your broader roadmap. However, in my experience, that discipline pays off. Instead of being tossed around by every AI trend, you harness precisely the right technology at the right time.
The AI Adoption Scorecard Approach
A tool I’ve found invaluable is a simple AI adoption scorecard. It keeps you honest about whether a potential AI project aligns with your strategic priorities—or if it’s just an appealing piece of tech.
A basic scorecard might include:
- Strategic Alignment: How directly does this initiative support our core objectives?
- Process Readiness: Is the underlying process well-defined and consistent, or still evolving?
- Data Quality: Do we have the necessary data, and is it trustworthy enough to feed AI effectively?
- Change Readiness: Is the team prepared to adapt workflows around this new capability?
- ROI Clarity: Can we clearly articulate and measure the expected business impact?
For example, if you’re considering rolling out a new AI-based lead-scoring feature, you might rate it against each of these criteria. This simple exercise could save you from costly rework by revealing whether you’re truly ready—or just dazzled by the promise of AI.
The Real Questions That Drive AI Success
Before diving headfirst into any new AI tool or feature at TDX, ask:
- What business challenge are we really trying to solve?
- Which outcomes matter most—customer satisfaction, sales efficiency, product innovation?
- How do our current processes help (or hurt) these goals?
Focusing on the business case first changes everything. Organizations that last in the AI space tie each new initiative to a concrete objective. They see AI as a powerful amplifier—one that only works if the core process is well-defined and strategically sound.
Let’s Connect at TDX
I’m excited to continue this conversation at TrailblazerDX. If you’ve tackled these same questions—maybe you’ve found success by starting with clear objectives, or maybe you’ve faced frustrations—let’s swap insights.
Comment below, send me a message on LinkedIn, or find me at TDX. Sometimes, the conversation about what AI should and shouldn’t do is more valuable than analyzing what it technically can do. I’m looking forward to learning from your experiences and seeing how we can make AI a true driver of business transformation. Let’s push beyond the hype and make meaningful progress together.