Why Are Successful Enterprises Embracing AI Disruption

Jan 5, 2026

Join Pete Foley, CEO of ModelOp and AI governance expert with over 25 years in enterprise software, as he dives into the challenges companies face with AI disruption. He discusses the critical need for AI governance and how to conquer production bottlenecks that can delay model deployment for months. Discover strategies to balance speed and risk, enhance visibility across AI projects, and ensure models translate into tangible business outcomes. Pete emphasizes the importance of a structured approach to scaling AI while protecting corporate integrity.

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INSIGHT

Binary Future For Companies

AI will create a binary split in five years between companies that embrace it and those that fail.
CEOs must act now to avoid permanent competitive disadvantage.

INSIGHT

Production, Not Creation, Is The Bottleneck

The real bottleneck is getting models into production, not model creation.
Pete Foley says models typically take nine to twelve months to reach production in large enterprises.

ADVICE

Begin With Inventory And Real-Time Monitoring

Start with comprehensive visibility: inventory every model, assign risk, and classify use cases.
Then enforce policies and monitor models in real time to catch failures quickly.

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Is your company's "AI disruption" happening with you—or quietly without you… and putting your business worth at risk?

If you're leading a mid-to-large company right now, you're probably feeling two pressures at the same time: move faster with AI and don't blow up the business while you do it. Because AI isn't a future trend anymore—it's already being built, tested, and used across departments, geographies, and teams (often without a single unified view). And that creates a real leadership headache: how do you scale AI for competitive advantage while still keeping guardrails in place?

In this episode, Jim Schleckser talks with Pete Foley (CEO of ModelOp) about what happens when AI spreads "like wildfire" inside an organization—and how to regain control without killing momentum.

You'll walk away with:

A practical way to get visibility into AI across your organization so you know what models exist, what they're doing, and where the biggest risks are hiding.
A framework for putting governance and guardrails in place without slowing innovation—so you can move faster than competitors and sleep at night.
A clearer path to scaling AI investments into real business outcomes (revenue, cost reduction, risk control) instead of letting models sit stuck in limbo for 9–12 months.

Hit play now to learn how to build AI guardrails that protect your brand and accelerate results—so you can boost business worth before the market decides who survives the disruption.

Check out:

[02:10] "In five years, there'll be two kinds of companies…" — Jim frames the stakes of AI disruption and why ignoring it threatens long-term survival and business worth.
[10:45] The real AI bottleneck: why models take 9–12 months to reach production — Pete explains what's slowing companies down and why that pace won't survive the next wave.
[23:30] The "air traffic controller" approach to AI governance — visibility, risk assignment, guardrails, and real-time monitoring so AI can scale without chaos.

About Pete Foley

With more than 25 years of executive and entrepreneurial experience in enterprise software and a track record of successful business exits, Pete Foley's leadership gives ModelOp customers, partners and employees a high level of trust and confidence in the company and its future. Prior to co-founding ModelOp, Pete held several chief executive roles, including CEO of RingCube Technologies, a desktop virtualization software solution provider acquired by Citrix in 2011; CEO of PortAuthority Technologies, a provider of data leak protection systems, from 2005 through its acquisition by Websense in 2007; and CEO of Infoblox (BLOX) from 2002 through 2005. In addition, Pete was the Executive Chairman of Graphite Systems, a low latency, flash-based big data appliance that was acquired by EMC, from 2012 to 2015.