

Why AI Is Creating Financial Risk
Faster Than Most Companies Realize

Only 1 in 5 AI initiatives deliver sustained financial impact. Most executives assume the biggest challenge with AI is the technology. It isn't.
The real gap is decision governance. AI is already influencing pricing, forecasts, and capital allocation at most companies, often without anyone defining where a human needs to be in the loop or what the guardrails should be. By the time the problem surfaces, it's already on the financial statements.
The executives who get ahead of it ask the hard questions before they invest. That's what we help you do.
Our Engagement Approach:
Three Simple Steps
1
Clarity Call
One 30-minute conversation to assess your situation and show you what's possible. Even if we're not the right fit, you'll walk away with clarity on your next move.
2
Engagement Design Session
We map your specific situation and design the exact scope, timeline, and investment… together. You know what you're getting before signing anything.
3
Guided Implementation
We work alongside your team to execute the plan—no handoffs, no surprises, just measurable results that show up where it matters.



Meet Clyde Calhoun
FOUNDER • CEO • ENTERPRISE AI ADVISOR
Clyde Calhoun spent more than 30 years leading enterprise transformations at Lockheed Martin, GE, and Owens Corning across R&D, operations, supply chain, sales, marketing, and HR where the only results that mattered were the ones that showed up in the financials.
That cross-functional experience matters because AI is an enterprise challenge, not a departmental one. The decisions AI influences in pricing affect operations. The assumptions it makes in forecasting ripple into capital allocation. Clyde understands how those connections work and where the exposure hides.
He founded Root Idea to help finance executives establish visibility and control over AI-influenced decisions before they become board-level problems.
THE MOMENTS EXECUTIVES CALL US

SOUND FAMILIAR?
When your board asks how much a business-critical decision was influenced by AI, and you don't have a clear answer.
When a project team has started scaling an AI pilot, and no one has defined decision ownership or financial controls.
When you need to isolate which AI initiatives are actually moving the numbers from those just creating activity.
When your largest customer asks how you're managing AI risk, and you don't have a credible answer.
When a key forecast misses shortly after AI was introduced, and no one can tell you why.
When your leadership team is aligned that AI is a priority but no one can agree on where to focus first.

In Their Own Words

Practical Support for AI Decision Makers
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