AI governance and strategy backed by thirty years and evidence.
Independent, evidence based AI leadership for boards and executive teams: governance, security, vendor and stack audits, and a clear business case before any software is bought. Everything below is the proof behind that advice.
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Apply the four tests to me. Then to anyone else.
Thirty years in enterprise technology as a senior operator, not a commentator: large scale systems integration, data and infrastructure modernization, security and compliance programs, and enterprise architecture delivered inside Fortune 500 environments. I publish a daily AI briefing that takes no money from the vendors and model providers it covers, so nothing I recommend is bought. I run fifteen AI staffed roles in production, which means I have personally handled model selection, prompt and retrieval architecture, evaluation, human in the loop controls, monitoring, and failure modes rather than reading about them. I hold four governance certifications covering AI risk management, privacy, security, and controls, so I can audit the architecture, data lineage, and policy posture behind my own recommendations. And every technical claim I publish clears a three gate verification chain against primary sources before it airs.
The four criteria.
Unbought
PassNo vendor pays me to say anything.
DX Today publishes seven days a week. No sponsored content. No pay to play coverage. No affiliate links. No paywall, ever. Every claim is traced to a primary source and fact checked before it airs.
The publication is free and stays free. It is funded by my advisory practice, not by the industry it covers. That is the entire reason I can afford to tell you a product does not work.
Built
PassI ship the thing. I do not just have opinions about the thing.
Fifteen AI staffed roles running in production under human supervision: receptionist, SDR, inbound response, reactivation, expansion, referral, renewal, invoicing, collections, billing recovery, quote chaser, publisher, sales ops, GTM analyst, and chief of staff. On the job in five days. Month to month, no annual lock in.
When I tell you what AI can and cannot do inside a revenue operation, it is because mine are running right now and I see what breaks.
Certified
PassI am credentialed to audit what I recommend.
CISA, CISM, CGEIT, PMP, ITIL, and CobiT. That is an audit vocabulary, not a technology vocabulary. It means I come at AI oversight the way a risk committee does, which is a different job from building a model and a different job again from selling one.
Behind it: thirty years and roughly $1.2 billion of delivered enterprise solutions, into Fortune 500 manufacturing and financial services. Nineteen published titles.
Sourced
PassEvery claim is traced to a primary source before it airs. Pick any story and check it.
DX Today runs a verification chain on every claim it publishes, before publication rather than after. Three independent gates, each a different model, plus corroboration against the original source. Nothing airs on one source and nothing airs on my say so.
I run the same verification discipline on my own publication that I would put on your AI systems. If I could not govern my own output, you should not let me near yours.
Comparative assessment.
| Who is giving you AI advice | Unbought | Built | Certified | Sourced |
|---|---|---|---|---|
| Industry analyst firms | ~ PartialSell research services to the vendors they rate | ✕ No | ✕ No | ✓ YesGenuine research rigor, credit where due |
| Global consultancies and integrators | ✕ NoSell the implementation they recommend | ✓ Yes | ✓ Yes | ✕ No |
| AI thought leaders and course sellers | ✕ NoSponsorships, courses, affiliate revenue | ✕ No | ✕ No | ~ Rarely |
| AI product founders | ✕ NoSell their own product | ✓ Yes | ✕ No | ✕ No |
| Independent enterprise veterans | ✓ Yes | ✕ NoAdvise, do not operate | ~ Sometimes | ✕ No |
| Rick Spair | ✓ Yes | ✓ Yes | ✓ Yes | ✓ Yes |
Verification protocol.
Anyone can say they are accurate. Here is the process that has to clear before something goes out under my name, so you can check whether I actually follow it.
- 01Primary source or it does not run.
A claim is traced back to the original document, filing, or announcement. Reporting about reporting is not a source.
- 02Three independent verification gates.
Each claim is checked by three separate models, not one, then corroborated against the original. Agreement across independent checks is the bar, not a single confident answer.
- 03Verified before it airs, not after.
The chain runs at production time. Nothing gets published on the assumption it can be walked back later.
- 04Corrections are visible and prompt.
Errors go to rick@dxtoday.com and get fixed in the open, not quietly edited.
- 05The same gate governs every channel.
Daily brief, podcast, newsletter, video. One shared verification process rather than a different standard per format.
No sponsored content. No paid editorial coverage. No thought leadership partnerships at any price. No exclusive vendor partnerships and no referral fees. No paywall, no tiers, no gates.
This is the part I would point at first. I am asking you to trust my read on AI systems you are about to spend real money on. The reasonable response to that is to ask what discipline I hold my own output to. This is the answer, it is published, and you can test it against any story in the archive.
Pick a story. Follow the sources. That is the whole invitation.
Track record.
- Sector coverage
- Enterprise, mid market, and SMB. Financial services. Healthcare. Retail. CPG. Manufacturing. Legal. Professional services.
- Delivered
- Approximately $1.2 billion in enterprise solutions
- Certifications
- CISA · CISM · CGEIT · PMP · ITIL · CobiT · CMC · CITMC
- Education
- MBA · BS Computer Science · Executive Education, Business Management
- Published
- Nineteen titles on AI and digital transformation · 700+ podcast episodes
- Current
- Publisher, DX Today · Founder, AIXF
I reject the avalanche of AI marketing fluff.
Enterprise AI strategy requires clear, unembellished technology communication.
Evidence backed implementations
I do not deploy technology for the sake of technology. Every AI initiative is backed by a quantified business case and a realistic return on investment.
Pragmatic governance first
Before a single model is trained or Axiom deployed, the guardrails are in place. Data privacy, compliance, and risk mitigation come before speed to market.
Independent of any vendor
I do not sell software seats. My guidance is entirely independent, separating genuine technological capability from hollow vendor promises.
Strategic leadership for the AI era.
Fractional Chief AI Officer
Embedded executive leadership to build and run your internal AI steering committee, audit current capabilities, and define the eighteen to twenty four month AI roadmap.
Organizations that need C suite AI expertise without the full time executive compensation package.
AI Governance and Risk Architecture
Developing the corporate policies, compliance frameworks, and data security protocols required before employees are granted access to generative AI tools.
Boards and executives prioritizing risk mitigation, intellectual property protection, and regulatory compliance.
Vendor and Stack Auditing
An unvarnished, technical audit of your proposed AI vendor contracts and technology stack. I cut through the hype to tell you what the technology can actually do.
IT and procurement leaders evaluating major AI platform investments or platform migrations.
AI Strategy and Roadmap
A structured diagnostic of where AI creates real economic value in your business, translated into a sequenced, budgeted roadmap with clear owners, success metrics, and build versus buy decisions.
Leadership teams that need a defensible plan and prioritized use cases before committing capital or headcount.
Three decades in enterprise technology. Two disciplines. One focus.
Strategic advisory requires more than understanding algorithms or pipelines. It requires knowing how enterprise architecture, governance, and revenue operations actually behave under pressure. Across thirty years of enterprise technology leadership I have led transformation programs, stood up governance structures, and separated durable AI capability from vendor narrative as a fractional Chief AI Officer. That same enterprise deal making experience, operationalized through a deployed fleet of Axioms, is what powers the Precision Revenue Framework for lean revenue teams. As a nineteen time published author on AI and digital transformation, my focus is singular: pragmatic, evidence based leadership that holds up in production, on the revenue line, and in front of a board.
$1.2B
Delivered
30+
Years enterprise tech
19
Books on AI and DX
4
Governance certifications
1,000+
AI systems reviewed
15
Axioms live
Bring the AI budget and the pilot list.
Thirty minutes is enough to know whether the Chief AI Officer seat is empty, and what it would cost, in writing, before anything begins.