As businesses invest trillions of dollars into artificial intelligence, one question is becoming increasingly important: where is the return on investment?

In this NYSE Live interview, Steve Lucas, Chairman and CEO of Boomi, discusses enterprise AI adoption, infrastructure spending, AI agent governance, data readiness, and the growing challenge of turning AI investments into measurable business value.

Kristen Scholer spoke with Lucas about AI spending, enterprise software, data infrastructure, AI agents, cloud computing, governance, and the future of intelligent automation.

A major theme throughout the conversation is the unprecedented scale of global AI investment. Organizations continue pouring capital into data centers, software platforms, cloud infrastructure, and AI-enabled business applications as they position themselves for the next wave of digital transformation.

The interview also explores a growing disconnect between AI spending and realized returns. While investment levels continue climbing, many organizations are still working to translate AI adoption into measurable earnings growth and operational improvements.

Another key topic is enterprise data readiness. Lucas argues that successful AI initiatives depend on access to trusted, well-organized, contextualized data capable of supporting intelligent decision-making.

The conversation further examines Boomi's role within the AI ecosystem. The company focuses on data integration, data activation, and governance capabilities that help organizations connect enterprise information to AI systems and AI agents.

A significant focus of the discussion is trust. Businesses increasingly want AI systems that can do more than generate content. They want systems capable of supporting operational decisions while adhering to governance standards and organizational controls.

The interview also highlights Boomi's Control Tower capabilities, which are designed to help organizations monitor and govern how AI agents operate across enterprise environments.

Another major theme is the difference between AI assistance and AI autonomy. Many organizations are comfortable allowing AI to support human workflows, while fewer are willing to fully delegate high-stakes business decisions.

The discussion also explores the impact of AI infrastructure spending. Demand for cloud services, computing power, and AI capacity continues to expand as organizations increase investments in generative AI and intelligent automation.

Additionally, Lucas discusses why today's AI environment differs from past technology cycles. Unlike previous
xinfrastructure booms, demand for AI services continues to exceed available supply in many segments of the market.

The interview further examines how local policy decisions, permitting processes, energy availability, construction timelines, and investment incentives can affect future AI infrastructure deployment.

Another key topic is return on investment. Finance leaders increasingly expect AI initiatives to demonstrate measurable business outcomes rather than simply generating experimentation and pilot activity.

The conversation also highlights Boomi's acquisition of Elementary Data, which helps provide context, metadata, and organizational understanding that can improve the quality and reliability of AI-driven insights.

A significant focus is the concept of the AI agent trust gap. Organizations are still navigating the difference between AI systems that assist employees and fully autonomous agents capable of making operational decisions independently.

The discussion further explores how enterprises are progressing through different stages of AI maturity. While many companies have embraced AI-assisted workflows, most remain cautious about fully autonomous business operations.

Looking ahead, Lucas expects future AI success to be driven by high-quality data, governance frameworks, trustworthy AI agents, and architectures that balance automation with enterprise oversight.

Throughout the discussion, Lucas shares insights on artificial intelligence, enterprise software, AI governance, data infrastructure, intelligent agents, cloud computing, digital transformation, technology investment, automation, and organizational trust.

Disclaimer: Informational content only. NYSE does not endorse or recommend investments, strategies, companies, products, or services discussed.

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