One visualization makes all the difference
This matrix of targets allows for prioritization, but also is a great learning opportunity for the rest of the organizational leaders to engage in.
How to identity the AI opportunities
This matrix of targets allows for prioritization, but also is a great learning opportunity for the rest of the organizational leaders to engage in.
Enterprise architecture experience plays in
AI model experience also required
- We work together to ascertain the key opportunities that comprise a well-conceived strategy for implementing AI across the org.
- We qualitatively assess with finance and technology how the projects impact the business.
- Project targets are framed in time, cost, involvement levels, ROI timelines, and subjective improvements to customer journey.
- Senior management leverages the artifacts and visualizations to plan, formulate, and strategize.
Hands-on AI expertise across data, models, and adoption.
I specialize in helping organizations establish AI capabilities that drive measurable business value.
- Model Discovery, Evaluation, and Deployment
- Predictive Analytics & Forecasting
- Intelligent Automation (RPA + ML)
- NLP & Document Intelligence
- LLM Training & Fine Tuning
- AI Governance & Risk Management
Designing an AI opportunity matrix for a typical organization
Challenge: Most organizations today are excited about AI but paralyzed by choice. Every department has ideas — automate this, predict that, personalize here, reduce manual work there. Leadership wants a unified AI strategy, but the landscape is chaotic: disconnected ideas, unclear ROI, mismatched priorities, and no shared criteria for deciding which opportunities matter.
The real challenge isn’t a lack of imagination. It’s a lack of structure. Companies need a way to identify, evaluate, and prioritize AI opportunities systematically — not reactively.
Solution: I guide organizations through a structured AI Opportunity Journey, culminating in the creation of an AI Opportunity Matrix — a strategic decision model that helps leaders see where AI can create the most leverage.
For one client in particular, I architected, built, and deployed an automated nightly tuning framework that injected customer-specific and precisely formatted tuning / training data directly into the model as an automated retraining cycle. The result was a continuously improving ecosystem — one where existing Python and C# developers on the teamThe journey begins with discovery. I dissect how the business actually operates: key workflows, data inputs, customer touchpoints, failure points, handoffs, and the hidden friction that employees often know but can’t articulate. This often includes interviews, shadowing sessions, mapping exercises, and reviewing existing systems and analytics.
Next comes translation — taking raw, informal AI ideas and converting them into technically meaningful problem statements. What data would this require? What systems would it touch? What decisions would it influence? What would success look like in measurable terms? Most AI ideas die here — not because they're bad, but because clarity reveals whether they’re feasible, valuable, or premature.
Then I build the Opportunity Matrix itself: a weighted scoring framework that evaluates each potential initiative across critical dimensions — business value, impact on margin, data readiness, architectural fit, feasibility, time-to-value, risk, and cost.
The result isn’t just a list. It’s a ranked portfolio of opportunities, color-coded and sequenced, forming a clear strategic roadmap.
But the deeper value comes from alignment. The matrix becomes a shared lens for the entire organization — a way to strip emotion, hierarchy, and politics out of prioritization. Teams stop arguing from preference and start deciding from evidence. Leaders get clarity. Developers get direction. The company gets a blueprint.
I’ve learned that the real power of an AI Opportunity Matrix is cultural: it establishes a disciplined way of making AI decisions. It turns innovation from guesswork into a repeatable process. As the company grows, the matrix evolves with it — a living strategy engine that updates as data pipelines mature, workflows change, and new possibilities emerge.
At its core, the Opportunity Journey reframes AI not as a scattered set of projects, but as an architected path — a sequence of decisions that compound. When companies have a structured method for recognizing what not to build, they finally gain the clarity to build what truly matters.
"Anyone can deploy a model; the real work is aligning it with human intent, business value, and measurable improvement. My role is to architect systems that don’t just run, but learn — that tune themselves, refine themselves, and deliver more tomorrow than they did today."
Automated self-training AI model for content platform
Learn more on a recent engagement, where I architected, built, and deployed an automated AI model training and tuning system for an AI-based content creation platform.
"I have worked with Shawn and I know his talent and leadership can have an enormous impact in a consulting engagement. I have seen it first-hand."
