The Gap Between AI Spending and AI Value

The Gap Between AI Spending and AI Value

Author: Software Engineering Daily August 25, 2026 Duration: 54:42

It is widely reported that a gap has emerged between enterprise spending on AI and the durable value captured from that spend. Individual employees have enthusiastically adopted coding assistants and chatbots, yet those gains do not seem to be transforming businesses at an organizational level. One of the most important questions in the tech industry today is understanding why AI is not yet delivering returns that match the investment, and what separates the small number of enterprises succeeding from the many that are not.

Scale AI is known for supplying the human-labeled data behind many frontier models. It now also builds AI applications and agents for large enterprises. That combination of working alongside frontier labs and inside enterprise deployments gives the company a rare view of why enterprise AI may be stalling.

Emily Xue is the Head of Enterprise AI at Scale AI, and previously spent over a decade at Google. In this episode, Emily joins Kevin Ball to discuss the three layers where enterprise AI breaks down, why frontier model benchmarks miss what enterprises actually need, the data foundation problem, how the most successful companies combine internal domain expertise with outside AI specialists, and more.

Sponsorship inquiries:
sponsor@softwareengineeringdaily.com

The post The Gap Between AI Spending and AI Value appeared first on Software Engineering Daily.


Dive deep into the conversations shaping the future of artificial intelligence with the Machine Learning Archives-Software Engineering Daily. This curated collection pulls from the broader Software Engineering Daily library, focusing entirely on the intricate world of ML engineering. Each episode features a detailed, technical interview with engineers, researchers, and architects who are building the systems behind today's most advanced AI. You'll hear them break down complex topics like model deployment, data pipeline challenges, and the practical trade-offs involved in taking research from a notebook into production. The discussions are grounded in real-world implementation, moving beyond theoretical concepts to explore the tools, failures, and successes that define the field. For developers and technical leaders looking to understand the nuts and bolts of applied machine learning, this podcast offers a valuable archive of knowledge. It's a direct line to the practitioners who are solving hard problems every day, providing insights you can apply to your own work. Tune in to gain a clearer perspective on how machine learning is integrated into modern software, one detailed conversation at a time.
Author: Language: en-us Episodes: 50

Software Engineering Daily
Podcast Episodes
Hype and Reality of the AI Coding Shift [not-audio_url] [/not-audio_url]

Duration: 57:05
AI coding tools have gone from novelty to core infrastructure in under three years. Today, many devs use AI daily, a substantial share of new code is AI-generated, and expectations for automation are rapidly increasing.…
Unlocking the Data Layer for Agentic AI with Simba Khadder [not-audio_url] [/not-audio_url]

Duration: 49:04
AI agents are increasingly capable of reasoning and performing autonomous work over long periods. However, as agents take on more complex, longer-horizon tasks, keeping them supplied with the right information becomes th…
Agentic Mesh with Eric Broda [not-audio_url] [/not-audio_url]

Duration: 47:23
AI agents are evolving from individual productivity tools into distributed systems components inside enterprises. The next frontier is coming into focus, and it involves large-scale ecosystems of collaborating agents emb…
New Relic and Agentic DevOps with Nic Benders [not-audio_url] [/not-audio_url]

Duration: 46:18
Observability emerged from the need to understand complex software systems, and involves tracking metrics, logs, and traces so engineers can detect and diagnose problems before they affect users. However, modern applicat…
Mobile App Security with Ryan Lloyd [not-audio_url] [/not-audio_url]

Duration: 54:52
Mobile apps have become a primary interface for critical services, including banking, payments, and healthcare. Unlike web applications, much of the logic and intellectual property in a mobile app lives directly on the u…
FastMCP with Adam Azzam and Jeremiah Lowin [not-audio_url] [/not-audio_url]

Duration: 1:06:06
The Model Context Protocol, or MCP, gives developers a common way to expose tools, data, and capabilities to large language models, and it has quickly become an important standard in agentic AI. FastMCP is an open source…
SED News: OpenCode, AI Code vs. Shipped Code, and the LiteLLM Breach [not-audio_url] [/not-audio_url]

Duration: 56:42
SED News is a monthly podcast from Software Engineering Daily where hosts Gregor Vand and Sean Falconer unpack the biggest stories shaping software engineering, Silicon Valley, and the broader tech industry. In this epis…
FreeBSD with John Baldwin [not-audio_url] [/not-audio_url]

Duration: 1:03:31
FreeBSD is one of the longest-running and most influential open-source operating systems in the world. It was born from the Berkeley Software Distribution in the early 1990s, it has powered everything from high-performan…
Cilium, eBPF, and Modern Kubernetes Networking with Bill Mulligan [not-audio_url] [/not-audio_url]

Duration: 57:30
Modern cloud-native systems are built on highly dynamic, distributed infrastructure where containers spin up and down constantly, services communicate across clusters, and traditional networking assumptions break down. L…