{"id":3893,"date":"2026-07-21T15:43:20","date_gmt":"2026-07-21T15:43:20","guid":{"rendered":"https:\/\/crosscountrymovingteams.com\/?p=3893"},"modified":"2026-07-21T15:43:20","modified_gmt":"2026-07-21T15:43:20","slug":"exclusive-kpmg-and-openai-bet-the-future-of-software-is-headless-and-the-future-of-work-is-mostly-talking","status":"publish","type":"post","link":"https:\/\/crosscountrymovingteams.com\/?p=3893","title":{"rendered":"Exclusive: KPMG and OpenAI bet the future of software is \u2018headless\u2019 \u2014 and the future of work is mostly talking"},"content":{"rendered":"
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The frontier lab hired KPMG to build an internal Supply Chain & Fulfillment Orchestration platform \u2014 essentially asking the consulting firm to design the kind of AI-native workflow system that KPMG now intends to sell broadly. <\/p>\n

Read more Current price of oil as of July 21, 2026<\/a><\/p>\n

That \u201cclient-zero\u201d deployment, as KPMG calls it, is the foundation of a new alliance between the two companies announced today, in which KPMG has been named an OpenAI Elite Partner \u2014 the highest tier in OpenAI\u2019s partner network. After partnering to design and deploy an AI-native Supply Chain & Fulfillment Orchestration platform, now they are taking that model to market together.<\/p>\n

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Colleen Kapase, Vice President of Strategic Global Partnerships and Ecosystems at OpenAI, told Fortune<\/em> that Elite Partner status is reserved for a \u201climited group of global partners\u201d that have the reach, scale and delivery capabilities to support enterprise AI adoption worldwide. <\/p>\n

\u201cWe\u2019re beyond experimentation,\u201d Chad Seiler, KPMG\u2019s U.S. industry leader for technology, media and telecommunications, told me in an interview. \u201cThis is about large-scale enterprise deployment.\u201d<\/p>\n

The core of what KPMG is selling is a bet on how enterprise software changes from here. Right now, most employees interact with work through applications: they log into systems, navigate screens, click through modules. Seiler\u2019s argument is that this is ending. <\/p>\n

\u201cWhen we say headless, we\u2019re really talking about decoupling the experience of work from the underlying systems and screens and modules while keeping those systems in place as a system of record,\u201d he said. <\/p>\n

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In the model he\u2019s describing, employees stop navigating software and start describing what they want done. AI agents interpret the intent, coordinate across backend systems, and execute \u2014 or escalate to a human when judgment is required.<\/p>\n

The endpoint, in his telling, is voice. \u201cOver time, you\u2019re going to be talking more than you\u2019re typing,\u201d Seiler said. \u201cInstead of just interacting with your ERP system or your CRM system in a traditional way with clumsy UIs that are limited in what they can do, you\u2019re kind of unleashed and you can have literally conversations with your systems and take actions with it and take actions not only within that system, but connect that to other data sets and other systems all through an intelligent agentic layer.\u201d <\/p>\n

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A KPMG blog post published on July 20, co-authored by Swami Chandrasekaran and Matteo Colombo, frames the shift more formally: \u201cTried and true SaaS isn\u2019t going away. Its user interface is evolving. More precisely, a new work surface is emerging.\u201d<\/p>\n

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The underlying databases and enterprise applications don\u2019t go away. They become infrastructure, invisible to the user, running underneath a layer of agents that handles translation between human intent and machine execution.<\/p>\n

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A sandwich, squashed<\/h2>\n

To make the abstraction concrete, the interview touched on a \u201csandwich\u201d framework from Princeton\u2019s Arvind Narayanan, whose \u201cAI as Normal Technology\u201d research breaks work into three layers: a decide layer on top, an execute layer in the middle, and a deliver layer on the bottom \u2014 what he calls the \u201cdecide, execute, deliver sandwich.\u201d <\/p>\n

Narayanan\u2019s argument is that AI compresses only the execute layer, which was never more than a third of the work to begin with, while the decide and deliver layers \u2014 judgment and accountability \u2014 resist compression and may expand.<\/p>\n

I showed Seiler the framework on a screen-share during our interview. He agreed immediately that it matched what KPMG was seeing in deployments \u2014 the image did look like a skinny hamburger patty. But he added a wrinkle: speed itself creates new verification burdens at the deliver layer, and a new kind of overhead that wasn\u2019t in Narayanan\u2019s original thesis \u2014 more talking about work rather than doing it. <\/p>\n

\u201cThe worker spends less time learning the geography of the software and more time focusing on the outcomes they\u2019re trying to achieve,\u201d Seiler said. In his reading, the decide bun doesn\u2019t just hold steady as the execute patty shrinks. It can expand, absorbing the coordination work that used to live in the middle.\u00a0But someday, headless work will get so good that it could shrink away.<\/p>\n

Read more Trump\u2019s $3.47 \u2018Freedom Fuel\u2019 gas network leans on an NFL kicking coach, a GOP fundraiser and a N.J. entrepreneur with a fuel theft rap sheet<\/a><\/p>\n

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When reached for comment, Narayanan argued that software engineers have always spent a surprising fraction of their time writing specifications and product requirements documents, which fits into the \u201cbun\u201d section of his metaphor. But it\u2019s not only that\u00a0judgment and accountability structurally resist compression, he argued, although to an extent, they do; it\u2019s also that \u201cAI is rapidly increasing the ambition and complexity of projects, so the *ceiling* of judgment and accountability moves up, even as AI moves the floor up.\u201d<\/p>\n

When reached for comment, Narayanan referred Fortune<\/em> to another blog post where he tackled the SaaS issue, saying it\u2019s slightly distinct from the decision sandwich. On LinkedIn, he warned about \u201clock-in,\u201d where the AI agent will become \u201cthe main queryable repository of all \u2026 tacit knowledge, creating dependence and stickiness,\u201d meaning it is effectively a coworker \u201cthat you can\u2019t fire without *every* team losing workflows and know-how.\u201d <\/p>\n

On timelines, Seiler and Narayanan are more aligned than their respective positions might suggest. Narayanan frames organizational adaptation to AI as a decades-long process \u2014 closer to factory electrification than overnight disruption. KPMG offers an implicit hedge in the same direction, cautioning against wholesale reinvention: \u201cThe most successful organizations will be deliberate about where they reinvent \u2014 and where they do not,\u201d noting that \u201cthe same workflows that have been in place for years may continue to be the best fit.\u201d <\/p>\n

Meanwhile, Narayanan said he doesn\u2019t think AI is urgent to the extent that frontier labs portray it to be, e.g., superintelligence by 2027, \u201cbut nonetheless it is more urgent a shock than most organizations are used to dealing with.\u201d In other words, it takes a long time to reinvent the sandwich.<\/p>\n

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Why KPMG says humans still matter<\/h2>\n

The most interesting point Seiler makes isn\u2019t about the technology. It\u2019s about why a consulting firm is well-positioned in a world where the technology is commoditizing.<\/p>\n

His answer: decades of client-specific institutional knowledge that no frontier model has. \u201cWe know their business models, their people, their culture, their systems, their data, their politics, their silos,\u201d he said, \u201cin an intimate way at scale that some of these frontier models don\u2019t.\u201d <\/p>\n

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Kapase agreed that KPMG brings \u201cdeep enterprise transformation experience,\u201d particularly across highly regulated industries, the public sector and cybersecurity, where governance and implementation expertise are critical. She pointed to public-sector modernization and a product called Daybreak Cyber as key aspects of the partnership, inaddition to KPMG\u2019s client-zero work within OpenAI. OpenAI is committed to broad access across its ecosystem, she added, so KPMG is not receiving exclusive access to unreleased OpenAI capabilities.<\/p>\n

Seiler, for his part, described the OpenAI alliance as additive rather than exclusive: KPMG maintains parallel partnerships with other frontier labs, including Anthropic, and doesn\u2019t expect large clients to standardize on a single AI provider.<\/p>\n

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\u201cWe don\u2019t think we\u2019re going to see a lot of cases where we\u2019re going to have one client that\u2019s completely just using one frontier model to run everything,\u201d he said. Some clients, he acknowledged, are already using cheaper alternatives \u2014 including open-source models from China \u2014 for narrower tasks, as a cost and resilience hedge.<\/p>\n

Regarding the rise of open-source models, Kapase said OpenAI\u2019s focus is on \u201chelping customers get greater value from OpenAI.\u201d She noted that GPT\u20115.6 delivers more intelligence from every token and stronger performance per dollar, with\u00a0Sol 54%\u00a0more token-efficient on agentic coding tasks. KPMG employees on their Advisory and internal teams have been using OpenAI capabilities daily since the firm integrated it into the internal AI tool aIQ Chat in 2023, Kapase noted, with KPMG identifying Codex-related use cases as it builds AI-enabled capabilities for clients.<\/p>\n

What distinguishes the OpenAI deal, in Seiler\u2019s telling, is the go-to-market dimension. \u201cIt\u2019s one thing to work with the labs, and then it\u2019s another thing to also work with them and go to market with them.\u201d The client-zero deployment is the proof point: if KPMG could build this for OpenAI itself, the pitch to every other enterprise client becomes considerably easier to make.<\/p>\n

Narayanan also referred Fortune<\/em> to a blog post where he tackled the SaaS issue, saying it\u2019s slightly distinct from the decision sandwich. On LinkedIn, he warned about \u201clock-in,\u201d where the AI agent will become \u201cthe main queryable repository of all \u2026 tacit knowledge, creating dependence and stickiness,\u201d meaning it is effectively a coworker \u201cthat you can\u2019t fire without *every* team losing workflows and know-how.\u201d<\/p>\n

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KPMG closes on a note that sounds less like a technology announcement and more like a management consulting memo \u2014 which is probably the point. Agentic AI adoption, the firm writes, is \u201ca portfolio of business decisions to be made, not a technology migration.\u201d For a firm whose value proposition has always been helping large organizations make hard decisions carefully, that is less a hedge than a positioning statement.<\/p>\n

Read more Alaska pilot takes six-pack plane seizure case to Supreme Court, citing \u2018duty\u2019 to make sure the Bill of Rights \u2018actually means something\u2019<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

“You’re going to be talking more than you’re typing,” KPMG U.S. TMT leader Chad Seiler told Fortune about the future of work.<\/p>\n","protected":false},"author":1,"featured_media":3892,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[311],"tags":[],"class_list":["post-3893","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-consulting"],"yoast_head":"\nExclusive: KPMG and OpenAI bet the future of software is \u2018headless\u2019 \u2014 and the future of work is mostly talking - Cross Country Moving Team<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/crosscountrymovingteams.com\/?p=3893\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Exclusive: KPMG and OpenAI bet the future of software is \u2018headless\u2019 \u2014 and the future of work is mostly talking - 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