{
  "id": 6941580,
  "title": "‘One of the worst outcomes for companies is reacting in a knee-jerk fashion before the rewards can be reaped’: How game engines, version control software, and AI are delivering new benefits and challenges to almost every industry",
  "url": "https://urgent.news/2026/09/12/one-of-the-worst-outcomes-for-companies-is-reacting-in-a-knee-jerk",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-12T14:30:00.000Z",
  "source": {
    "name": "TechRadar",
    "slug": "techradar",
    "url": "https://www.techradar.com/pro/one-of-the-worst-outcomes-for-companies-is-reacting-in-a-knee-jerk-fashion-before-the-rewards-can-be-reaped-how-game-engines-version-control-software-and-ai-are-delivering-new-benefits-and-challenges-to-almost-every-industry"
  },
  "original_language": "en",
  "account": "As companies increasingly adopt AI technologies, the challenge remains to demonstrate that these advancements yield tangible, measurable benefits. While the cost of AI implementation is clear, quantifying the gains in productivity and efficiency is a complex undertaking. Though businesses can easily assess expenses, gauging the impact on output is a different matter altogether. The success of AI in certain areas may hold valuable insights for other industries, paving the way for a more seamless integration of this transformative technology.\n\nDespite the growing adoption of AI, it is essential to recognize that game engines and real-time 3D engines have been widely embraced across various sectors beyond the gaming industry. These tools, once confined to the gaming realm, have found applications in aerospace and defense, the public sector, education, and even media and entertainment. The widespread adoption of these tools is evident, as they have proven to deliver productivity improvements backed by decades of success in the gaming industry. However, AI technology is still grappling with the challenge of sustained, measurable returns on investment for many organizations.\n\nIn addition to AI, version control software is experiencing a surge in adoption within the context of real-time workflows. As businesses grapple with handling a growing volume of assets and content within their projects, the need for visibility into changes becomes paramount. This shift is driven, in part, by the incorporation of AI agents into workflows, emphasizing the importance of knowing who made specific modifications, especially when AI is involved.\n\nWhile AI's adoption offers numerous benefits, concerns persist, particularly regarding job displacement. A significant portion of employees who have integrated AI into their workflows express apprehension about being replaced by the technology. Furthermore, 49% of these employees fear that AI-generated content may be of poor quality or inaccurate, and 48% raise ethical or compliance concerns about the use of AI tools. To navigate these challenges, it is crucial to address the perception of AI's impact on both employees and consumers.\n\nAccording to Brent Schiestl, the author of Perforce's report, the perception shifts when evaluating AI's role in source code versus binary assets. For instance, AI-assisted bug fixes in source code is generally more acceptable to consumers, as it involves a well-defined problem where creativity is less critical. However, when AI is used to generate binary assets such as images, audio files, and videos, it raises more significant concerns. Recent steps companies have taken to maintain trust include transparent disclosure policies regarding AI usage, emphasizing that human oversight remains integral to final asset creation, and maintaining comprehensive provenance data to demonstrate the origin of these assets.\n\nMoving beyond the tokenmaxxing approach to measure AI's value, businesses are now focusing on more effective metrics to demonstrate the cost-benefit ratio of AI deployment. These metrics encompass release frequency, the amount of content produced in each release, and telemetry to track the utilization of new features. Additionally, industry-standard metrics like DORA have gained prominence as organizations seek broader benchmarks of productivity. However, a fundamental challenge lies in isolating AI's contribution from other release activities, a hurdle that requires further exploration.",
  "summary": "I spoke to Brent Schiestl of Perforce to learn more about how AI is affecting real-time workflows, and the extra tools businesses are deploying to manage assets and measure productivity.",
  "key_points": [
    "Game engines and version control software widely adopted beyond gaming industry",
    "AI adoption poses challenges in quantifying productivity gains for organizations",
    "Concerns about AI job displacement and quality of AI-generated content"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}