How to Make Enterprise AI Work in 2026 ft. Tim Piemonte

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TL;DR:

• Many enterprises deploy AI without strategy, leading to failed initiatives despite strong tools and intent.
• AI success depends on aligning people, processes, and platforms, not just introducing new technology.
• Shadow AI usage is increasing as employees adopt tools faster than enterprises can govern them.
• The highest AI value comes from agentic systems that operate across multiple applications and workflows.
• Sustainable AI adoption requires measurable ROI, security-first governance, and executive buy-in from day one.

Before we dive into the key takeaways from this episode, be sure to catch the full episode here:

Meet Tim - President and Co-Founder of Tribeca Softech

Tim Piemonte is President and Co-Founder of Tribeca Softech, where he helps enterprises modernize infrastructure, security, and strategy to deploy AI responsibly. With decades of experience spanning Dell, EMC, Pivotal, and cloud transformation initiatives, Tim brings a pragmatic lens to enterprise innovation.

At Tribeca, Tim works closely with financial institutions and regulated enterprises to align AI adoption with real business outcomes. His approach starts with people and skills, moves through workflows and process readiness, and only then introduces platforms and technology.

A strong advocate for security-first AI, Tim emphasizes governance, explainability, and executive alignment as non-negotiables. His work helps organizations move beyond experimentation toward AI systems that deliver measurable impact without introducing unnecessary risk.

Why AI Fails Without Strategy

Tim Piemonte sees failed AI initiatives regularly, and the root cause is almost always missing strategy. “I go into companies and they talk about their failed AI initiatives,” Tim explains, pointing out that tools alone do not create value.

Enterprises often skip foundational work and rush into automation without alignment.

“You’ve got to look at the people, the process, and the platforms. If any one of those is not ready, the effort breaks down.” — Tim Piemonte

Tim emphasizes that AI should never be introduced in isolation. “If one of those fails, you’re really setting yourself up for failure,” he warns. Successful AI starts with clarity around outcomes, ownership, and readiness before technology is ever deployed.

People, Process, Platform as the Foundation for AI

For Tim, AI adoption always starts with people. “It definitely starts with the people,” he says, describing how he begins with CISOs, CIOs, and CTOs to understand priorities and concerns. Without skills and buy-in, AI becomes shelfware.

“If people aren’t using the tools, regardless of how great they are, you don’t have adoption,” Ankur notes, a point Tim fully agrees with. Process comes next. “Are the workflows in place? What does the infrastructure look like?” Tim asks.

Only then does platform selection matter. “If any of those three aren’t ready, you’ve got to figure that out beforehand,” he says. This sequencing is what separates scalable AI from stalled pilots.

Shadow AI and the Risks of Moving Too Slowly

One growing concern Tim highlights is shadow AI usage. “People are excited to use AI,” he says, noting how easy it is to get quick results without oversight. When enterprises move slowly, employees bypass governance.

“Employees are downloading AI tools without that security oversight,” Tim warns. This creates what Ankur calls “chaos disguised as progress.” While experimentation is valuable, Tim stresses that guardrails must come first.

“You’ve got to move quickly, but in a proper fashion,” he explains. Without security visibility, enterprises risk data exposure and compliance failures. The solution is not blocking AI but enabling employees to use it safely, so innovation happens inside the organization rather than outside of it.

From Pilots to Production With Measurable ROI

Tim distinguishes real progress from endless experimentation by focusing on outcomes. “Quick wins have to produce ROI,” he explains, especially for organizations new to AI. AI pilots must be clearly defined, or else they’ll fail. “What were we trying to achieve? Did we hit it?” he asks.

Once in production, Tim uses a quarterly “validate the value” approach. “Here’s where we were before, here’s where we are today,” he says, measuring efficiency, cost savings, and customer impact. This discipline builds executive trust.

“If you can’t measure something, you can’t get better at it.” — Ankur patel.

ROI-driven validation turns AI from a science project into a repeatable capability.

Security and Governance as Competitive Advantages

Security is not a blocker to AI for Tim. It is an enabler. “Security has to be part of the culture,” he says. CISOs must be involved early, not informed later.

“There is no room for black boxes,” Tim explains, especially in regulated environments. AI systems must be explainable and auditable, just like human employees. “If someone can’t show their work, that’s not going to fly either,” he says.

Governance also includes access controls.

“Why would you want to build RBAC when it already comes built into a platform?” — Tim Piemonte.

Enterprises that treat security as foundational move faster and with more confidence than those who treat it as an afterthought.

Would you like to learn more about AI in enterprise? Check out this episode on enterprise AI implementation commentary with Bjorn Austraat.