AI is evolving beyond simple inputs and outputs. Today’s most advanced systems aren’t just reactive, they’re agentic, designed to plan, reason, adapt, and act independently to accomplish goals.
In the latest episode of The High-Growth Equation, TD SYNNEX’s Lawrence Roberts sits down with Evan Unrue, Chief Technologist for Data and AI, to unpack what agentic AI truly is, how it’s already being applied in the real world, and what organizations need to consider as they adopt these intelligent systems.
Watch Now: Agentic AI Explained with Evan Unrue
Get a firsthand look at what makes agentic AI different, and how it’s helping businesses move faster, think smarter, and operate more autonomously.
Video Timestamps:
- What is Agentic AI? (01:13)
- Real World Applications (02:31)
- Why Observability Is Crucial (04:59)
- Tools That Help You Stay in Control (07:31)
If you missed the first episode, The High-Growth Equation kicks off with a deep dive into Large Language Model (LLM) Jacking, featuring AI security expert Matt Bingaman, who explains what it is, why it matters, and how to stay protected.
What Is Agentic AI? (01:13)
Agentic AI refers to systems that function more like intelligent collaborators than passive tools. These agents are goal-oriented, capable of executing multi-step workflows with minimal human intervention.
Unlike traditional automation, agentic AI systems can:
- Interpret objectives in context
- Select the right tools for the task
- Adjust in real time as conditions shift
- Continuously learn and improve
As Evan explains, “Rather than directing every step, you give the agent a goal, a persona, and a toolkit, and it figures out how to get there.”
Real World Applications (02:31)
From creative use cases to enterprise transformation, agentic AI is already delivering results.
Evan shares personal experiments with agentic storytelling, but the business impact is even more compelling. A standout example? Automated proposal generation.
Through tapping into unstructured content, like customer histories, vendor data, and service catalogs, agentic AI can generate highly personalized proposals or insights in moments, accelerating time to value and decision making.
Why Observability Is Crucial (04:59)
Autonomous systems require oversight. Without it, even well-designed agents can go off track.
“Think about it,” Evan says. “You wouldn’t let interns run finance unsupervised. Why would you let AI?”
Observability is essential to:
- Ensure actions align with business goals
- Catch deviations or unexpected behaviors early
- Maintain ethical standards and compliance
With the right visibility in place, teams can trust their AI systems while staying in control.
Tools That Help You Stay in Control (07:31)
As agentic AI becomes more common, governance and monitoring tools are stepping up to support it.
These tools help organizations:
- Track agent workflows in real time
- Measure success and detect anomalies
- Enforce policies and protect sensitive data
Strong observability doesn’t slow down innovation, it enables it. With these practices in place, businesses can scale their use of agentic AI with confidence.
Getting Started, Build Your Agentic AI Foundation
Agentic AI isn’t just on the horizon, it’s already here. Whether you’re exploring new capabilities or building for scale, TD SYNNEX offers support at every stage.
Tap into:
- AI-focused training through GSS enablement courses
- Structured learning journeys via the Destination AI™ program
- Expert advisory and technical guidance
Explore More in The High Growth Equation
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We focus on the most powerful, high-growth technologies shaping your business, from hybrid cloud and AI to cybersecurity, data, and IoT, providing the expert guidance you need to stay ahead and make the most of every opportunity.
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