Why executive judgment decides who wins with AI. Published: October 16, 2026 At the Thoughtworks and Amazon Web Services (AWS) inaugural Technology Leaders Forum in New York City, CIOs, CTOs and senior technology leaders gathered to work through a question too many organizations still answer badly: now that AI has made outputs abundant, why hasn't value followed? Alex Moore, Thoughtworks' VP of AI Solutions, used his keynote, "Use your best judgment: how organizations are realizing compounding returns with agents," to argue that the answer has little to do with model quality or token prices. It's all about judgment: the scarcest resource in any AI-first organization, and the one most leaders are depleting without noticing. Alex's team surveyed more than 200 delivered AI use cases, strategies and roadmaps to find what separates programs that compound from programs that merely grow cost. The patterns, he told attendees, are consistent enough to act on today. The Petrov problem. Alex opened with Stanislav Petrov, the Soviet officer who in 1983 was told his nation's detection systems had identified five incoming US missiles. Protocol called for him to escalate toward retaliation. He didn't, because the data didn't match his judgment: a real first strike wouldn't look like five missiles, and the system was too new to trust completely. He was right. The data was wrong. His point drew a straight line to this year's Hugging Face breach, in which an autonomous agent swarm took more than 17,000 actions against the company with no human on the attacking side to slow it down. When defenders tried to use Claude Opus to understand what was happening, the model's own safety guardrails flagged their defensive prompts as malicious. There was no one to escalate to, on either side, fast enough to matter. As AI systems act at machine speed, human judgment becomes the thing standing between a sound decision and a catastrophic one. Most organizations haven't built the muscle to protect it. Three questions, and an accountability gap. Alex highlighted three questions that come up constantly in client conversations: * What should people and experts own in an AI-first organization? * What capabilities must a business own end-to-end? * How do you actually maximize return on AI investment? The research behind the first question is sobering. Across the datasets cited, roughly 90% of organizations can't name who is accountable for a given agent's behavior. About four in five lack clear rules of engagement defining what their agents are allowed to do unsupervised. A third override AI outputs case by case, with no formal criteria for when or why. The result, as found in its 2026 Global CIO Survey 2026, is that two-thirds of CIOs and CTOs are accountable for AI systems they don't actually control. Alex's prescription was three rules: 1. People must own unwritten decisions the first time they're made. 2. Those decisions must become the policy and guardrails that govern the next one. 3. Because conditions keep changing, trust has to sit with the experts closest to the work, with the tools to override the system when the data doesn't add up. Owning what matters, renting the rest. On capability ownership, Alex pointed to the unfolding dispute between OpenAI and mathematicians who allege their unpublished work was used to solve a 200-year-old problem, as a warning about intellectual property exposure. A recent Cisco study found 77% of organizations name IP protection as a top AI concern, but only about half have contractual terms in place to secure it. His advice wasn't to avoid frontier models. It was to deliberately choose a posture, whether renting frontier access through an API, routing traffic through a governed gateway, diversifying into open-weight models for stable workloads, or owning hardware outright for the most sensitive work - and to revisit that choice constantly, since the economics of any single use case shift with the market. The judgment line. Perhaps the most useful framework Alex shared was what he called the judgment line: the point in any business process where standard operating procedures run out and a case becomes genuinely bespoke. Today, people handle nearly everything above that line, often because the data needed to automate it never got captured in the first place. Programs that succeed, the research found, tend to share a few traits: outcomes a human can verify, fast feedback on whether something worked and gated generation, a mechanism where a machine checks the model's output before it ever reaches a system of record. Conversely, programs that fail share opposite traits: no clear definition of a good outcome, and agents left to invent their own objectives with no one measuring the result. Applied well, this discipline shows up directly in the numbers: organizations that build this kind of tiered, checked workflow into their software delivery lifecycle have seen coding price-performance improve by 50% to 80%, and delivery speed up by as much as 82%. The critical patterns. Alex's research also turned up a short list of use-case shapes that recur in the programs that succeed. Three were close to universal: adversarial ground truth, where an opponent such as a fraudster, attacker or spammer supplies the labels continuously and for free; queue prioritization, where a machine orders the work but a person still decides every case; and gated generation, where output must pass a machine that can refuse it before anyone looks. These are really one idea three times. Something outside the program decides whether a unit of work is correct, and nothing reaches the system of record until it is. A second tier of 10 patterns is less glamorous and mostly about making new use of data and tooling already in place, such as instrumented perception, in-line quality inspection, protocolized alerting and "abandoned work" that was never worth attempting at human cost. Because the data predates the model purchase, the returns are easy to prove. At the other end, seven patterns, including cognitive offload, drafting under a named approver and open-ended agentic autonomy, tend to fail the same two ways. No one can say whether an individual output was right, so the loop never closes, and no one measured what "good" looked like to begin with. They aren't off limits, but they are ones to enter with eyes open. The takeaway. Alex's final question cut straight to the point: now that you have the questions, what's your next move? For an audience under intense pressure to show AI results to the board, even as governance lags behind, this closing line outlined the tough task ahead. Recommended insights.

Expand Energy selects Thoughtworks to scale AI across the enterprise. Oct 05, 2026, 08:00 ET Engagement combines AI strategy, enterprise AI platform development and production deployment to help Expand Energy scale AI across the business. CHICAGO, Oct. 5, 2026 /PRNewswire/ - Thoughtworks, a global technology consultancy that integrates design, engineering and artificial intelligence (AI) to drive digital innovation, today announced that Expand Energy (NASDAQ: EXE), the largest independent natural gas producer in North America, has selected the consultancy as its strategic partner to design and build an enterprise-wide AI capability. The multi-phase engagement covers AI strategy, use case prioritization, machine learning (ML) platform implementation, and the delivery of a production-ready solution aligned to Expand Energy's long-term strategic priorities. Expand Energy operates across exploration and production as well as energy marketing, areas with significant opportunity to unlock value through AI. Seeking to move beyond isolated pilots toward a coordinated, enterprise-scale approach, Expand Energy selected Thoughtworks to help connect strategy, platform development and delivery in a single program. The company's objective is to identify the highest-value AI opportunities across the business, build the capabilities required to support them, and deploy a production solution by the end of 2026. "AI has the potential to create value across multiple areas of our business, but realizing that value requires more than individual projects," said Josh Viets, executive vice president and chief operating officer at Expand Energy. "We selected Thoughtworks because of its ability to connect strategy, technology and delivery in a single engagement. Together, we're building the foundations needed to identify, deploy and scale AI solutions that support our long-term business objectives." As organizations move beyond AI experimentation, many are finding that continued success depends on the underlying platforms, governance and operating models that support adoption at scale. The engagement is designed to help Expand Energy build those foundations while delivering measurable business outcomes. Thoughtworks will lead the engagement across three connected workstreams: * AI strategy and opportunity prioritization: Thoughtworks will work with business and technical stakeholders across Expand Energy to identify, evaluate and prioritize high-value AI opportunities aligned to the company's strategic objectives. * Enterprise AI foundations: Thoughtworks will design and begin implementing the data, platform and governance capabilities needed to support AI adoption at scale across the organization. * Solution delivery and enablement: Thoughtworks will build and deploy a high priority AI solution, establish an operating model for ongoing AI delivery, and enable Expand Energy teams to adopt and scale AI responsibly. Unlike traditional AI programs that separate planning from implementation, Thoughtworks' approach combines strategy and delivery from the outset to create AI that works. Early-stage proof-of-concept development generates real-world insight into data readiness, integration requirements, adoption challenges and business value, allowing the roadmap and operating model to evolve based on evidence rather than assumptions. "This engagement reflects a challenge we're seeing across all industries: organizations want to move from isolated AI experiments to agentic AI that delivers business value," said Manish Sateeja, senior vice president and head of automotive and manufacturing for North America at Thoughtworks. "Expand Energy has the leadership commitment, domain expertise and ambition to make that transition. This work creates the operational backbone required to scale agentic AI directly into business operations and deliver value." The engagement draws on Thoughtworks' track record delivering AI strategy and enterprise ML platform programs across data-intensive industries including energy, financial services, life sciences, and global market research. The firm brings experience spanning end-to-end AI capability buildouts, MLOps platform implementations, responsible AI governance, and large-scale workforce AI enablement. Supporting resources: * Learn more about Thoughtworks' Data & AI capabilities. * Discover Thoughtworks' Agentic Development Platform, AI/works(TM). About Thoughtworks Thoughtworks is a global technology consultancy that integrates design, engineering and AI to drive digital innovation. We are over 10,000 people strong across 47 offices in 18 countries. For 30+ years, we've delivered extraordinary impact together with our clients by helping them solve complex business problems with technology and culture as the differentiator. About Expand Energy Expand Energy Corporation (NASDAQ: EXE) is North America's largest natural gas producer, powered by dedicated and innovative employees focused on expanding the value of natural gas by connecting scale to growing markets. Expand Energy's returns-driven strategy strives to create sustainable value for its stakeholders by leveraging its advantaged portfolio, financial strength and operational excellence. Expand Energy is committed to expanding America's energy reach to fuel a more affordable, reliable, lower carbon future. Media contacts: SOURCE Thoughtworks

Thoughtworks supports SulAmérica's digital transformation through critical systems modernization. September 22, 2026 - São Paulo Project leverages artificial intelligence to modernize core technology systems, increasing agility, efficiency and innovation. Thoughtworks, a global technology consultancy that combines design, engineering and artificial intelligence (AI) to drive digital innovation, has been selected by SulAmérica, one of the largest insurance companies in Brazil, to modernize its core technology infrastructure. The project aims to accelerate the insurer's digital transformation by enhancing its ability to update systems, integrate new solutions and introduce new capabilities for customers and partners in a market increasingly shaped by artificial intelligence, data and open insurance. The initiative will focus initially on SulAmérica's mainframe environment, which supports the insurer's core business processes. The partnership will modernize the platform gradually and strategically without disrupting ongoing operations. "Modernizing core systems requires a balance of security, strategic vision and proven execution," said Viviana Tobar, vice president of markets, banking, financial services and insurance at Thoughtworks Latin America. "Our role is to guide SulAmérica through this transition, using artificial intelligence to better understand its existing environment and accelerate innovation in a responsible way." The multi-phase project begins with a comprehensive assessment of SulAmérica's technology ecosystem to map systems, dependencies, risks and priorities. Thoughtworks will then develop a Minimum Viable Modernization (MVM), a technical proof-of-concept that demonstrates how legacy systems can be updated incrementally with controlled risk and early, actionable insights. Throughout the project, AI will accelerate the analysis of legacy code and system architecture. By automating discovery, AI helps make the overall transformation faster, clearer and easier to execute. Partnership backed by legacy systems expertise The initiative includes collaboration with Mechanical Orchard, a specialist in legacy system modernization. This partnership combines Thoughtworks' expertise in digital transformation, software engineering and AI with Mechanical Orchard's deep technical knowledge of legacy infrastructure. For SulAmérica, this project supports a broader digital strategy. To continuously enhance its health, insurance and wellness platforms, the insurer requires a flexible, integrated technology foundation designed to adapt to emerging market demands. "We have a strong track record of leveraging technology to support our operations and enhance the experience we provide to customers. This partnership represents another step in that evolution, creating the conditions to modernize critical systems securely, with careful planning and a focus on innovation," said Paulo Henrique dos Santos Rodrigues, head of platform engineering at SulAmérica. Greater agility to evolve digital products and services As the project progresses, modernization is expected to drive efficiency gains, reduce technological complexity and increase agility in the development of new solutions. Over time, these upgrades will enhance SulAmérica's ability to launch products, integrate partners and deliver simpler, personalized experiences to its more than 7 million customers. The partnership comes at a time of significant transformation in Brazil's insurance sector. The expansion of Brazil's open insurance framework, which promotes greater data sharing and integration across the insurance market, along with advances in AI and growing demand for digital services, has led companies across the industry to rethink their technology foundations. "In this context, modernizing critical systems has become a strategic priority for companies seeking to maintain operational reliability while increasing their capacity to innovate," said Paulo Henrique. Legacy modernization is no longer just a technical challenge, but a primary driver of business competitiveness. "By modernizing its technology foundation, an organization can preserve system stability while unlocking new opportunities for innovation. In the insurance sector, this balance is critical for responding to a market that is increasingly digital, integrated and data-driven," said Tobar. About Thoughtworks Thoughtworks is a global technology consultancy that integrates design, engineering and AI to drive digital innovation. ThoughtWorks, Inc. is over 10,000 people strong across 47 offices in 18 countries. For 30+ years, ThoughtWorks, Inc. has delivered extraordinary impact together with its clients by helping them solve complex business problems with technology and culture as the differentiator. Media Contact Marsh Abraham Head of Public Relations, Americas Email: [email protected]