Executive & board briefings
The honest read on where AI is, where it's going, and what your organization actually needs to be doing about it this quarter — not in three years.
05 / AI
AI training & implementation — without the hype.
Practical AI guidance for businesses ready to move past the buzzwords. Executive briefings, team training, vendor evaluation, governance frameworks, and the question that actually matters: where does this earn its keep in your operation, and where is it a distraction?
Why me
Thirty years of "new technology will change everything." I've seen this movie.
I've spent three decades watching businesses adopt — and over-adopt, and mis-adopt — every wave of new technology since the public internet. AI is real and it matters, and it's also the most over-marketed category I've ever seen. The job is separating the signal from the pitch, picking the two or three places it actually moves your numbers, and putting governance around it so it doesn't quietly create new risk while it's solving the old ones.
Background that matters here: deep operational IT and cybersecurity, an MBA built around the management side, and years teaching technology and management at the university level. AI is a business problem with a technology layer underneath — both sides need someone who can speak both languages.
Engagement formats
What this looks like.
Team training
Hands-on workshops for staff. How to use the tools well, what to never put into them, where the productivity is real, and where it's wishful thinking.
Implementation roadmap
A prioritized list of the two or three highest-value places to apply AI in your operation, sequenced by risk and payoff. Not a fifty-page strategy.
Vendor evaluation
Sorting real capability from marketing. Data handling, lock-in, hidden costs, and which tools are doing what they claim.
Governance & policy
Acceptable use policies, data classification for AI inputs, and the lightweight controls that keep AI from quietly becoming a new exfiltration surface.
Skeptic-in-residence
The phone call when someone in the org wants to spend serious money on an AI initiative. Independent read, no vendor incentive.
Who this is for
Three audiences.
- Executives & boards who want a credible read on AI from someone with no AI product to sell.
- Small and mid-sized businesses ready to deploy AI in real operational work and trying not to step on a landmine in the process.
- Organizations with regulatory exposure (legal, healthcare, government, financial services) where the governance question is as important as the productivity question.
Client voices
On the trait that matters most for AI training.
The InfoStream pool predates this work, but the underlying posture — practical, no upsell, problem-first — is the same.
"I have done business with InfoStream for over 15 years. Alan was the go-to guy whenever we needed help; he treated us with respect and gave us quick service and solutions. It's like having a personal friend who is interested in helping you solve either simple or complex problems."
"Alan, you and your team provide a level of customer service that just isn't found in most companies these days. We are blessed to work with a company that values what we are doing for our children and our community."
FAQ
Common questions.
Which AI platforms do you advise on?
The major generative-AI platforms (Anthropic Claude, OpenAI ChatGPT, Google Gemini, Microsoft Copilot) plus the surrounding tooling — agent frameworks, retrieval-augmented generation, model context protocol, automation platforms, the practical landscape an organization actually has to choose from. Certified by Anthropic and Google AI.
Do you do AI governance and policy work?
Yes. Written AI-use policy, acceptable-use guidelines, data-handling rules for AI tools, board-level governance frameworks, and integration with existing cybersecurity and compliance programs. The governance gap is the single biggest exposure organizations have right now and most do not know it.
Do you train teams or implement systems — both?
Both, on separate engagements. Training is half-day to multi-day sessions for executive teams, professional teams, or full organizations, customized to the actual work the audience does. Implementation is hands-on advisory through tool selection, pilot, rollout, and integration with existing workflows.
How do you handle data-privacy concerns with AI tools?
Same way I handle them with any cloud service: read the terms, understand the data flows, distinguish between consumer-grade and enterprise-tier offerings, design the policy around what the contract actually says, and instrument for actual usage. Most AI privacy incidents are policy failures, not technology failures.
Is this generative AI specifically or broader?
Primarily generative AI and the agent ecosystem, because that is where the practical business question lives in 2026. Classical ML, computer vision, and other modalities discussed where they meet the engagement, with handoff to specialists where the matter warrants it.
Start
AI mandate from the top? Twenty minutes of clarity before you spend a dollar.
Executive briefings, team training, vendor evaluation, and governance — focused on where AI actually earns its keep in your operation.