The experience of a major international company shows that managing AI usage has become as important as expanding its applications.<\/p>\n
According to Steel World Review, as the use of artificial intelligence expands across large companies and organizations, managing the costs of this technology has become a new challenge for executives. Tools such as ChatGPT and Claude not only accelerate work processes but also impose costs on organizations that, without proper monitoring and planning, may exceed allocated budgets.<\/p>\n
This issue is particularly important for major industries, including the steel industry, where artificial intelligence is gradually being adopted in production, quality control, maintenance, human resources, and energy management.<\/p>\n
Accenture\u2019s Experience: When AI Costs Reach $1,000<\/p>\n
Accenture, one of the world\u2019s largest management consulting and information technology services companies, which provides digital transformation and advanced technology implementation services to major organizations and industries, has recently changed its approach to managing employees\u2019 AI usage costs.<\/p>\n
According to an October 2026 report by 404 Media, the company has stipulated that Claude usage costs exceeding $29 per month be charged to the budget of the relevant project or business unit. Reports indicate that some employees, particularly programmers, have spent between $500 and $1,000 per month using Claude Code.<\/p>\n
Accenture has clarified, however, that this policy does not prohibit greater use of artificial intelligence. Rather, its purpose is to improve cost transparency and allocate resources in line with project requirements.<\/p>\n
This decision raises an important question for executives: Does increased AI usage necessarily translate into higher productivity?<\/p>\n
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1. Establish Dedicated Budgets for AI Tools<\/p>\n
Companies should establish specific budgets for the use of AI tools based on the needs of different departments. The requirements of an administrative unit differ from those of specialized functions such as engineering, data analytics, or programming, and resource allocation should reflect these differences.<\/p>\n
2. Measure Return on Investment and Employee Productivity<\/p>\n
AI costs are economically justifiable when they lead to reduced task completion times, improved quality, fewer errors, or better organizational performance. Companies should therefore evaluate the outcomes of using this technology against measurable indicators.<\/p>\n
3. Provide Targeted Employee Training<\/p>\n
Monitoring the level of AI tool usage should be accompanied by the development of information security guidelines. Confidential information relating to production, contracts, customers, and employees should not be shared with public AI systems without authorization and appropriate safeguards.<\/p>\n
4. Monitor Usage and Protect Organizational Information<\/p>\n
Monitoring the level of AI tool usage should be accompanied by the development of information security guidelines. Confidential information relating to production, contracts, customers, and employees should not be shared with public AI systems without authorization and appropriate safeguards.<\/p>\n
5. Prioritize Applications with Greater Economic Value<\/p>\n
Companies should direct AI investment toward activities that have the greatest impact on performance. In the steel industry, applications such as equipment failure prediction, energy consumption optimization, quality control, and production planning can be important priorities, provided their results are evaluated under actual plant operating conditions.<\/p>\n
The Steel Industry\u2019s Path Toward the Economically Viable Use of AI<\/p>\n
In steel plants, AI costs should not be viewed solely as information technology expenses. When applications are selected appropriately and implemented effectively, this technology can become a tool for improving production performance and resource management.<\/p>\n
Nevertheless, Accenture\u2019s experience demonstrates that even organizations at the forefront of technology need clear mechanisms for controlling costs and assessing the economic value of artificial intelligence.<\/p>\n
The future competitiveness of industries will depend not only on the extent to which they use artificial intelligence, but also on their ability to translate this technology into tangible productivity gains, lower operating costs, and economic value creation.<\/p>\n
Source: 404 Media, October 15, 2026.<\/p>\n","protected":false},"excerpt":{"rendered":"
The experience of a major international company shows that managing AI usage has become as important as expanding its applications. According to Steel World Review, as the use of artificial intelligence expands across large companies and organizations, managing the costs of this technology has become a new challenge for executives. Tools such as ChatGPT and […]<\/p>\n","protected":false},"author":22,"featured_media":8425,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"rs_blank_template":"","rs_page_bg_color":"","slide_template_v7":"","jnews-multi-image_gallery":[],"jnews_single_post":[],"jnews_primary_category":[],"jnews_review":[],"enable_review":"","type":"","name":"","summary":"","brand":"","sku":"","good":[],"bad":[],"score_override":"","override_value":"","rating":[],"price":[],"jnews_override_counter":{"view_counter_number":"0","share_counter_number":"0","like_counter_number":"0","dislike_counter_number":"0"},"footnotes":""},"categories":[240],"tags":[],"class_list":["post-8428","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-world_steel_news"],"yoast_head":"\n