AI in the Enterprise - Managing AI with Intention
Purpose as the North Star for AI Integration
As reaffirmed by a TechRadar article from just two days ago, businesses must ground AI adoption in purpose. The piece reports that only 31% of organizations have a documented AI strategy, and many rush into AI simply out of fear of missing out. Without clearly defined objectives—what you're improving, why it matters, and how you'll measure success—you risk poor outcomes, security pitfalls, and even reputational
What strikes me most from my own projects and what I’ve seen leaders around me do well is: successful AI starts with clarity. When you define the “why”:
Teams focus on solving real pain points—not chasing novelty.
There's alignment across stakeholders and clear evaluation criteria.
You can build trust; AI becomes a tool, not an unpredictable wildcard.
In projects where crafting that “why” was part of leadership’s initial framing, AI consistently accelerated workflows, solved real user issues, and built organizational momentum.
What Happens If It's Ignored
When "why" gets skipped, I've seen several predictable consequences:
Aimless deployment—teams experiment with gen‑AI because it's hot, pouring hours into prototypes that never meet a specific need.
Trust erosion—stakeholders stop believing in the outcomes after early experiments fail to show value.
Governance blind spots—no defined goals often mean no clear policies, leading to unchecked use, security risks, or ethical gray zones.
Contrast that with cases where “why” was clear. In those, even small wins built credibility over time—AI tools became trusted co‑pilots rather than suspect intruders.
A Real-World Example
Take the McKinsey insight from early 2025: it found that almost all companies invest in AI, but just 1% feel they’ve reached maturity. The biggest obstacle isn't employee resistance but leadership hesitation—leaders aren’t steering fast enough toward purpose-driven use.mckinsey.com
The message is clear to me: mature, impactful AI isn't about tools—it’s about direction. Without leadership clearly communicating why AI matters for business strategy and operations, adoption flounders.
Final Reflection
In my experience, the most transformative AI projects begin not with technology, but with intention. Start by asking—and aligning on—the real change you're after. Build your strategy around that.
Takeaway for leaders and managers: Before deploying AI, pause to ask—and answer—the "why." Defining your purpose isn’t optional—it’s foundational. Once that’s settled, you can build meaningful, measurable, and trust-worthy AI adoption, rather than chasing uncertainty.