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About

I’ve been the entrepreneur and the CEO. I’ve been the advisor. I have my own AI lab.

That is not a credential stack. It is a single vantage point: the operator’s view of a technology decision, checked by someone who can test the technology.

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Ivan Ruzic, Ph.D., principal of Analytical Outcomes

Ivan Ruzic, Ph.D.

Principal, Analytical Outcomes. Based in Knoxville, Tennessee. Engagements nationwide.

Background

What twenty-five years actually looks like.

I started as an operator. I have held leadership roles, including CEO, across industries that rarely overlap: a research firm, an open-source intelligence company, an online technology portal, and a financial-data provider. Each one meant owning the technology decisions and the outcome.

That is why, where I can, I test technical claims directly in my research lab rather than reading them back from a deck. Ten years of software and IT-services M&A sits behind it, not as a service I sell now but as a framework for judging risk, value, and what is real versus market hype.

I am independent. I do not sell the implementation, and I do not act as banker on either side of a deal. In diligence my job is to tell the buyer what the technology can and cannot do. In market readiness it is to tell the seller before a buyer does.

In plain terms

The background, without the adjectives.

  • M&A

    Ten years advising on software and IT-services transactions. The foundation for how technology claims are evaluated.

  • Operating

    Multiple leadership roles, including CEO, with more than thirty years of international corporate experience in total.

  • Technical

    Current AI implementation advisor, a quantitative modelling background, and a secure AI research lab.

  • Intelligence

    An open-source intelligence background that shaped the evidence discipline used in diligence.

How I think

A few things worth knowing before we talk.

  • I am skeptical of AI hype by default. That is not cynicism, it is the right prior given how much noise there is in this market.
  • I approach most problems quantitatively. A strategy without a financial model is a hypothesis.
  • I would rather take a small number of engagements and do them in depth. That is a choice, not a limitation.

Practice boundaries

  • Advisory, diligence, and market-readiness work only. No investment-banking mandates, sourcing, valuation, or negotiation.
  • No implementation or remediation attached to a diligence engagement.
  • Confidential material is handled under NDA and a conflict check.
  • All engagements are subject to availability and conflict check.

Speaking

Keynotes and roundtables.

Available for PE conferences, CEO roundtables, corporate M&A events, and board offsites. Comfortable at technical depth or boardroom level. Send an inquiry and choose “Speaking”.

  • AI technical due diligence: what acquirers are missing

    The technical risk patterns most deal teams do not evaluate, what “AI-powered” really means across company types, and how to structure AI-specific risk provisions.

    Audience: PE principals, M&A advisors, corporate development
    Format: 45 minutes plus extended Q&A

  • AI strategy for mid-market CEOs: signal versus noise

    How to evaluate AI opportunities with the rigour of any capital allocation decision, and the patterns that separate real value from expensive theatre.

    Audience: CEOs, C-suite, business owners
    Format: 45–60 minutes plus Q&A

  • The AI confidence gap: why executives get bad AI advice

    Most AI advice given to executives is biased toward implementation and overstates capability. How to spot it and what to demand from advisors.

    Audience: Senior executives and board members
    Format: 30–45 minutes

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