Bridging the Gap: From AI Buzzwords to Strategic Execution

How a six-week immersion into AI and business strategy shaped our approach.

AI is not just a technical shift. It’s a strategic lever - and many organizations are only just beginning to understand how to pull it.

So we decided to put our money where our mouth is and educate ourselves, then come back and tell you about it.

Why This Course Mattered

It's no secret that the AI landscape is saturated with hype - headlines touting breakthrough tools, endless startups, and “game-changing” use cases. But what happens when you slow down and ask: How do we actually use this responsibly and effectively inside real businesses?

That’s the question we brought to a six-week course on AI and Business Strategy at MSOE, taught by experts across computer science and business. Some nvisia consultants joined to deepen our AI fluency beyond tools - and into strategy, implementation, and organizational readiness.

The result? A clearer picture of what it actually takes to make AI work.

Three Essential Lenses to Bridge AI and Business Strategy

1. Intelligence = Automated Decision-Making

One of the expert guides, Dr. Jeremy Kedziora, Associate Professor and PieperPower Endowed Chair of Artificial Intelligence at MSOE, defined AI simply but powerfully: “An automated decision-maker.” This framing helped cut through the jargon and focus on what matters - intelligence as action.

We explored the structure of AI systems - from supervised to unsupervised to reinforcement learning - and the challenges posed by high-dimensional embeddings.

One key takeaway: LLMs are exceptional at interpolation (filling in the blanks within existing knowledge), but struggle with extrapolation (inventing outside the training envelope).

Dr. Kedziora predicted we may be approaching a plateau in LLM performance due to data and compute limit, but that’s not cause for panic. Instead, it’s a call to evolve how we apply what we have.

2. AI Is Not a Magic Bullet — It’s a Strategic Lever

Another expert, Dr. Scott Hrdlicka, Adjunct Assistant Professor at MSOE, took us into MBA territory, framing strategy as “the set of decisions that help us win, by creating value and realizing opportunity.”

We learned how to embed AI into both the formulation of business strategy (e.g., using ChatGPT for industry research or competitive landscape analysis) and its execution (e.g., applying AI to optimize operations or create new value).

One of the most actionable tools shared: the Impact vs. Feasibility Matrix for prioritizing AI initiatives:

• Low Feasibility + Low Impact: Drop it.
• High Feasibility + Low Impact: Quick wins to build momentum.
• High Feasibility + High Impact: Prioritize immediately.
• Low Feasibility + High Impact: Long-term moonshots.

This lens works beyond AI - it’s a smart framework for tech strategy overall.

3. Real AI Maturity Starts with Change Readiness

Dr. Hrdlicka emphasized that most AI initiatives fail not because the model is wrong, but because adoption was never baked into the plan.

We explored four pillars of AI readiness:

• Data
• People
• Technology
• Strategy

...as well as frameworks for successful rollout and stakeholder engagement (ADKAR, Kotter, McKinsey, and others).

One insight hit especially hard: “What we want to buy is adoption. But what we often pay for is installation.”

Sustained AI success requires governance, retraining, bias monitoring, and real user benefit - not just tech deployed with a login link.

Insights Worth Echoing

💡 “Generative AI is becoming the new Excel.” Accessible, flexible, misused, but deeply powerful when paired with skill.

💡 “Democratizing skilled creativity.” Generative AI has lowered the barrier to entry for creative expression, just like digital photography or desktop publishing once did.

💡 “Start with the problem, not the tool.” Don’t chase the shiniest model. Chase business value.

💡 “Stochastic grad student descent.” A tongue-in-cheek reminder that much of today’s frontier AI breakthroughs come from unlikely research sparks - not product roadmaps.

So… What Now?

This course offered us more than AI fluency. It gave us a lens for leadership.

Because using AI well isn’t just about writing better prompts or testing the latest model. It’s about integrating intelligence (machine or human) into strategy, structure, and service.

Whether you’re working in a regulated industry, leading a product team, or trying to modernize your platform - the real advantage isn’t the algorithm. It’s how intentionally you wield it.

Need a Strategic AI Partner?

At nvisia, we help clients integrate AI and data strategy into real-world execution - responsibly, efficiently, and creatively. From platform modernization and data readiness assessments to responsible AI implementation and executive workshops, our team brings both technical depth and strategic clarity.

Let’s build what’s next - wisely.

📩 Interested in bringing AI maturity to your organization? Hit one of the big, orange "Let's Connect" buttons on our site - you can't miss 'em.