With 47 years of hands-on experience in computing and technology, combined with a proven track record in business management and ownership, I bring a unique blend of technical expertise and real-world business insight to the table.

I understand the challenges small businesses face—tight budgets, limited resources, and the need for practical solutions that deliver measurable results. That’s why my approach to AI implementation is not about “shiny new tools,” but about strategic, cost-effective solutions that improve efficiency, reduce costs, and open new opportunities for growth.

Having worked across every level of management—from junior manager to business owner—I speak the language of business as fluently as I do the language of technology. This dual perspective ensures that every AI solution I design is not only technically sound but also aligned with your business goals.

Whether it’s automating routine tasks, enhancing customer engagement, streamlining operations, or uncovering insights hidden in your data, I help small businesses harness AI in ways that are practical, sustainable, and transformative.

If you want a consultant who understands both the technology and the business realities—and who knows how to bridge the gap between them—I’m the partner you’ve been looking for.

Traditional companies are failing to implement AI effectively. Here are five principles to make the technology actually work for you…

1/ AI problems are rarely AI problems – they’re strategy problems disguised as technology problems. Most organizations fail at AI implementation not because they chose the wrong models or hired the wrong engineers, but because they never clearly defined what business problem they’re solving. They see competitors “using AI” and panic-buy solutions for problems they can’t articulate.

The successful AI implementations I’ve observed all started the same way: with a ruthless audit of core business challenges that existed long before AI was a buzzword. Identify your highest value problems first, then apply AI as an accelerant.

2/ Budget size is inversely correlated with AI success. The companies throwing millions at AI initiatives are systematically outperformed by teams running on shoestring budgets with clear mandates.

Why?

Because constraints force clarity. When you have an unlimited budget, you can afford to be vague about outcomes. When you have $100k and six months, every decision has to directly serve a measurable business outcome. Money is a strategy substitute: the more you have, the less you need to think clearly about what you’re actually trying to accomplish. Once you get traction (and demonstrated success), you can scale your spend and impact.

3/ The 10x rule is the only rule that matters for AI adoption. Anything less than a 10x improvement in speed, cost, or quality is organizational noise. Most AI projects deliver 20-30% improvements that get lost in measurement error and change management overhead.

But 10x improvements create undeniable business value that justify the disruption of implementing new systems.

Requiring a 10x hurdle requires you to start with an “AI-enabled” clean sheet solution. The math is simple: if AI doesn’t make something dramatically better, you’re just adding complexity for incremental gains. Skip the incremental improvements and hunt for order-of-magnitude changes.

4/ Competitive intelligence is your fastest path to AI advantage. While you’re debating whether to build or buy, your smartest competitors are already shipping AI-powered solutions.

The fastest way to close capability gaps isn’t innovation, it’s intelligent imitation. Map what your best competitors are doing with AI, reverse-engineer their approach, and implement your version with improvements. The AI era rewards fast followers more than first movers because the technology landscape changes too quickly for sustained first-mover advantages.

5/ Pirates beat committees every time. The worst way to implement AI is through enterprise-wide initiatives with steering committees and governance frameworks. Instead, empower your teams from the ground up. Recent studies indicate some alarming news:

• 42% of executives say the process of adopting generative AI is tearing their company apart
• 41% of Millennial and Gen Z employees admit they’re sabotaging their company’s AI strategy

What’s needed is to enable small teams, “pirate ships,” to move at startup speed (within enterprise contexts). Small teams are optimized to experiment and learn rather than aim for consensus. Give them a problem, a budget, and air cover, then get out of their way.

Here’s the key implementation insight: AI amplifies existing organizational capabilities (and dysfunctions).

If your organization is good at executing strategy, AI will make you dramatically better.

But if your organization struggles with execution, AI will make you fail faster and more expensively.

The AI Strategy Paradox

Organizations with clear strategic thinking, empowered employees, and efficient execution will see AI multiply their existing advantages. Companies with fuzzy strategy and bureaucratic processes desperately need AI to remain competitive, but their organizational DNA makes successful implementation nearly impossible.

Your AI advantage doesn’t come from having better models or bigger budgets. It comes from having clearer problems to solve and faster execution cycles to solve them.

Of course your company will use AI. The question is: will you use it to multiply strengths or to mask weaknesses?