LAS VEGAS -- Trace3 Evolve this week was mainly about riding the AI wave, which the consultant and service provider described as “The Ultimate Reset.”

“We believe the rate of change is going to accelerate like we've never seen before, as AI gets adopted across the world and across enterprises,” Trace3 CEO Rich Fennessey said in his opening keynote. “This represents an incredible opportunity, but also a big risk. The time is now for us to work together to seize the opportunity. The time is now for us to act. Time is now for us to lead. And in some cases, the time is now to reset our businesses to ensure we're ready for the future.”

Fennessey left it to CTO Tony Olzak to outline the best way to prepare for that future with a Day 2 keynote. Olzak outlined four things for companies to focus on now to succeed with AI initiatives.

• Get your data right. “There are easier ways to do that than we've ever had before, with the least cost, the least amount of time and the least amount of people.”
• Think about your AI platform. “How are you going to standardize repeatability, scalability and cost control?”
• AI governance and risk. “Right now, there are startups out there that are in our sponsor room who have technology that will scan all your data and tell you what all the sensitive information is, who owns it, what to do about it. We've never had an easier time to think about the risk posture to your data itself.”
• Ultimately reworking of your strategy. “Create things that work in sequence, and create a bigger budget for what comes after the deployment of the AI versus what comes before.”

Trace3 executives and their customers who spoke at Evolve emphasized these are still early days for AI. “This next 18 months is going to become pivotal in how you think about the transformation of your company, and preparing yourself to create an engine of innovation that will allow you to move at light speed and do it in a way that's completely safe, that you could scale and become enterprise grade,” Olzak said.

And he spoke of challenges that remain. These include legacy systems with messy data, budget constraints that impact analytics and engineering, shadow AI that produces fragmented systems and lack of compliance.

To overcome these challenges, he laid out what he calls the four pillars for success.

Data Foundations: Olzak emphasized that enterprises must stop treating all data equally and prioritize based on AI governance requirements. New metadata standards, including the OSI (Open Source Initiative) interchange format, enable organizations to define data once and have those definitions propagate across all systems. Startups have technology that allows companies to ingest, organize, and label data with "almost no people, maybe no people, in the very near future."

AI Infrastructure: The fragmentation that plagued cloud adoption is repeating with AI. He cited a Trace3 customer with 50,000 employees across 45 countries that wound up with a dozen separate AI platforms after 18 months, resulting in runaway costs and zero reusability. "If you could solve this with yesterday's technology, you would have already," Olzak noted. The solution: unified AI platforms or "AI fabrics" that standardize for repeatability, scalability, and cost control. After implementing such a platform, that same client achieved record speed in building and reusing components.

AI Governance and Security: Drawing a Formula One analogy, Olzak argued that proper guardrails enable speed rather than hindering it. "There hasn't been a death in 10 years, but they're driving faster than they ever have before," he said of Formula One racers. The key is continuous monitoring—not point-in-time compliance checks.

Strategic Use Case Roadmaps: He warned against implementing disconnected one-off projects that fail to build organizational momentum. Olzak instead advocated for sequential projects that build capabilities cumulatively. "You don't have to be sure of what the use cases are yet," he said. "But what you have to do right now as technologists is build an engine that allows your organization to experiment at record speed."

“New technologies and learnings we've had over the last couple of years are starting to create a path forward and we can see it's becoming very clear what those next steps need to be to reach the end point,” Olzak said. “Which is, how do you completely reimagine end-to-end technology functions, or reimagine the way business functions, and how do you take technology and turn that into the driver of change.”