When Should You Use AI Agents? Autonomous IT, Risk & Governance | Agents of IT Ep. 26
When should enterprises use autonomous AI agents, and when is deterministic automation the better choice?
In Episode 26 of Agents of IT, Resolve Chief Product Officer Fran Fernandez and Director of Product Marketing Zach Austin sit down with Nelson Vega, SVP of Customer Solutions at Resolve, to discuss how enterprises can adopt agentic AI while managing risk, governance, consistency, and accountability.
The conversation explores a critical question for IT leaders: Where does autonomous decision-making create real business value, and where do predictable, repeatable workflows remain essential?
The team breaks down why AI agents still need a deterministic execution layer, how organizations should evaluate use cases before introducing autonomy, and why governance becomes increasingly important as AI gains the ability to take action across enterprise systems.
They also discuss the changing expectations of employees, the risks of shadow AI, human oversight, compliance, and the growing pressure on CIOs to demonstrate measurable returns from AI investments.
For IT and operations leaders, the path forward starts with selecting the right technology for each use case, establishing clear governance, and connecting intelligence to reliable execution.
Learn more about Resolve and the journey toward autonomous IT: https://resolve.io/
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00:00 Why autonomous AI needs accountability
00:34 Welcome to Agents of IT
01:05 Meet Nelson Vega
02:30 Is enterprise AI overhyped?
03:10 What IT practitioners think about autonomous agents
04:23 Managing autonomous AI risk
05:18 Moving from AI experimentation to business outcomes
06:12 Proving ROI from AI investments
08:08 AI agents and deterministic automation
09:02 Why AI agents still need an execution layer
10:37 Building an automation discipline
11:28 Why consistency matters in enterprise AI
13:10 How employee expectations are changing
15:13 The CIO challenge with agentic AI
17:29 Three types of employee requests
18:05 Where deterministic automation works best
19:17 Choosing the right technology for the use case
20:38 AI agents in highly regulated industries
21:37 Accountability for autonomous AI
24:11 Governance, trust, and human approval
24:56 Setting autonomy by use case and workflow
25:29 AI risk in access provisioning
27:28 How AI could change approval workflows
32:03 Why transparency and auditability matter
33:41 Hallucinations and autonomous execution
34:31 Building the right AI foundation
35:21 The importance of an experienced automation partner
37:59 What comes next for enterprise AI?
39:01 Why organizations need an AI center of excellence
40:13 AI at the end-user level
41:23 The growing risk of shadow AI
43:13 Choosing the right AI for the right use case
44:33 Final thoughts
45:30 Closing and Zero Ticket IT
#AgenticAI #AIAgents #AutonomousIT #itautomation #AIGovernance #EnterpriseAI #ITOperations #Resolve