Bernard Aceituno, StackAI co-founder, was recently featured in CIO.com to explore what successful enterprise AI deployments look like within IT teams, diving deep into the top use cases driving ROI.

The piece draws on patterns Bernard has observed across thousands of workflow runs with enterprise customers. The core insight: IT teams are leading AI adoption inside the enterprise, not because they were told to, but because they are under real pressure to deliver measurable results. A recent survey found that nearly three-quarters of CIOs say their role is at risk if they can't demonstrate business value from AI within two years.

Bernard walks through real deployment examples, from automated ticket triage systems that process hundreds of support tickets without human intervention, to advanced chatbots that pull from multiple knowledge bases simultaneously, to security review workflows where multiple LLMs cross-check each other's analysis for reliability.

One key point? The highest-performing deployments use multi-model architectures. Rather than relying on a single LLM, the most effective workflows break complex tasks into defined steps and run multiple models in parallel, comparing outputs to reduce blind spots. This is especially critical for security reviews and compliance analysis.

Additionally, read-write integrations are making workflows truly transformative. Agents that can both read from and write back to systems of record like Jira, ServiceNow, or Zendesk deliver compounding value over time, far beyond what a read-only chatbot can achieve.

Bernard's takeaway for CIOs: the best IT use cases are not novel. Ticket triage, document review, audit prep, internal Q&A and more are all things IT teams have done manually for years. But the fastest ROI comes from automating what is already well-understood and high-volume, then expanding from there. Ultimately, the teams getting the most out of AI agents right now are the ones who did the unglamorous work first by mapping their processes, organizing their knowledge bases, and building integrations that fit how their teams actually operate.

Read the full piece on CIO.com.