McKinsey’s analysis reveals shorter, more frequent market swings are reshaping commodity trading, favouring firms with advanced AI capabilities and strategic partnerships over traditional long-cycle approaches.
Shorter and more frequent swings in commodity markets are rewriting the rules for traders, concentrating returns among a narrower set of firms that combine deep balance-sheet firepower, operational control of physical flows and advanced digital tools, according to new analysis by McKinsey & Company.
McKinsey’s assessment finds that the era of extended supercycles is losing relevance as volatility compresses into quicker, repeated episodes that reward speed and optionality. Trading revenues across power and gas, metals and mining, agriculture, oil and products, and liquefied natural gas slipped to $69 billion in 2025 from $72 billion in 2024, yet remain roughly double pre‑pandemic levels, suggesting a permanently higher baseline for the business. The consultancy estimates around $20 billion of optimisation value across oil and gas products alone is still untapped. According to McKinsey, these dynamics are driving value capture toward firms with sophisticated capabilities while traditional, long‑cycle strategies become less effective.
Three structural shifts underpin the change. First, volatility cycles are accelerating, increasing the premium on rapid capital deployment and flexibility. Second, artificial intelligence is becoming central to differentiated trading performance: McKinsey highlights early results in which agentic AI automates post‑trade processes, compresses deal cycles and boosts support‑function efficiency by as much as 50–60%. Third, companies are investing more in trading capability, often through collaborative structures rather than outright acquisitions.
The firm’s January 2026 survey of more than 150 commodity‑trading professionals found a clear tilt toward partnership models: 49% favoured partnerships over acquisitions at 27% or organic builds at 24%. Support for partnerships was especially strong in Asia and the United States, where 78% and 80% of respondents respectively expressed a preference for collaborative approaches. Metals and mining, alongside oil and gas, were identified as the sectors likely to see the biggest rises in capability spending. According to McKinsey, many organisations now prefer joint ventures and joint‑book arrangements as a faster route to scale and access to physical flows than M&A.
Industry leaders are openly characterising the race to embed AI in trading as intense. Speaking at CERAWeek, Vitol Group chief executive Russell Hardy described the expansion of AI capabilities in oil trading as an “arms race” as algorithmic strategies become more prominent in futures markets. That competitive posture is mirrored in corporate technology roadmaps: McKinsey’s own guidance for 2026 urges firms to build scalable AI foundations, integrate AI into technology organisations and redesign product cycles around AI to convert potential into durable performance gains.
The shift towards partnerships dovetails with broader dealmaking trends. McKinsey’s M&A analysis shows global transaction value surged in 2025, with a notable rise in very large deals; while many firms prefer collaboration to buy‑outs in trading, strategic acquisitions and large transactions remain active across industries as companies reposition for an AI‑driven economy.
Capital allocation decisions are being reshaped by these forces. Industry observers point to sizable investment flows into the physical and digital infrastructure that supports advanced AI: Forbes has highlighted projections of substantial spending on AI data centres in 2026, underscoring how much has been committed to the compute and storage layers that underpin modern analytics. That investment, combined with access to physical commodity flows and trading capital, will determine which players can consistently monetise shorter volatility episodes.
“Shorter volatility cycles are creating a permanent divergence in the industry,” Roland Rechtsteiner, partner at McKinsey, said. The consultancy warns that firms that widen asset optionality through strategic partnerships and develop distinctive AI capabilities will secure advantages that are hard to replicate. As high‑volatility events occur more frequently, those combining capital, operational sophistication and control over physical supply chains are best placed to lock in long‑term value.
- https://www.mining.com/shorter-commodity-cycles-reshaping-trading-value-mckinsey/ – Please view link – unable to able to access data
- https://www.mckinsey.com/industries/energy-and-materials/our-insights/at-the-threshold-of-a-new-era-in-commodity-trading – McKinsey’s report discusses the evolving landscape of commodity trading, highlighting the shift from traditional supercycles to shorter, more frequent volatility cycles. It emphasizes the need for flexibility, rapid capital deployment, and access to physical flows. The report also notes the growing influence of artificial intelligence (AI) on trading models and the increasing importance of partnerships over acquisitions in capturing untapped value. The findings are based on a survey of over 150 commodity trading professionals worldwide, revealing a preference for partnerships, especially in Asia and the US.
- https://www.bloomberg.com/news/articles/2025-03-10/-arms-race-for-ai-driven-oil-trading-is-underway-vitol-ceo – Vitol Group CEO Russell Hardy highlighted the intensifying competition in AI-driven oil trading during the CERAWeek conference. He noted that the expansion of AI capabilities is augmenting algorithmic trading in oil futures markets, describing it as an ‘arms race’ for that type of trading. This underscores the growing role of AI in reshaping trading strategies within the commodity sector.
- https://www.mckinsey.com/about-us/new-at-mckinsey-blog/tech-resolutions-to-turn-ais-potential-into-performance – McKinsey’s blog post outlines three key resolutions for organizations to effectively harness AI’s potential in 2026. It emphasizes the importance of building scalable AI foundations, integrating AI into the tech organization, and redesigning product development cycles around AI. The article provides insights from McKinsey partners on how to make AI work sustainably and at scale, highlighting the need for leaders to adopt AI within their organizations to drive performance.
- https://www.mckinsey.com/capabilities/m-and-a/our-insights/top-m-and-a-trends – McKinsey’s analysis reveals a significant uptick in global mergers and acquisitions (M&A) activity, with deal value increasing by 43% in 2025 compared to the previous year. The report highlights a shift towards larger transactions, with deals valued at $10 billion or more taking center stage. It also notes that M&A activity accounted for 4.2% of total market value in 2025, up from 3.3% in 2024, indicating a growing trend in large-scale corporate consolidations.
- https://www.forbes.com/sites/petercohan/2026/01/23/whether-to-follow-602-billion-flowing-to-ai-data-centers-in-2026/ – Forbes discusses the substantial investment flowing into AI data centers, with $602 billion projected for 2026. The article highlights the record gold capital flows in 2025, with global gold ETF inflows reaching $89 billion, the largest annual inflow ever recorded. It also notes that gold prices soared in 2025 and are forecasted to remain flat in 2026, reflecting the growing interest in AI and its impact on various sectors, including commodities.
- https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-telco-reinvention-how-ai-can-fuel-value-creation – McKinsey’s report explores how artificial intelligence (AI) is reshaping the telecommunications industry. It discusses the critical role of telcos in laying the foundation of the digital economy and how AI, combined with maturing 5G and fiber buildouts, is transforming connectivity and the economics of the sector. The report emphasizes the need for operators to reinvent themselves to compete and share in the rewards of the AI economy.
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emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed
below. The results are intended to help you assess the credibility of the piece and highlight any areas that may
warrant further investigation.
Freshness check
Score:
8
Notes:
The article was published on March 3, 2026, and reports on a McKinsey & Company analysis. The earliest known publication date of similar content is March 3, 2026, indicating freshness. The article is not republished across low-quality sites or clickbait networks. The narrative is based on a press release from McKinsey & Company, which typically warrants a high freshness score. No discrepancies in figures, dates, or quotes were found. The article includes updated data without recycling older material. Overall, the content appears original and timely.
Quotes check
Score:
7
Notes:
The article includes direct quotes attributed to Roland Rechtsteiner, partner at McKinsey. A search for the earliest known usage of these quotes indicates they originate from McKinsey’s own publications. No identical quotes appear in earlier material, suggesting originality. However, the quotes cannot be independently verified outside McKinsey’s publications. Unverifiable quotes should not receive high scores.
Source reliability
Score:
9
Notes:
The narrative originates from McKinsey & Company, a major and reputable consulting firm. The article is published on MINING.COM, a specialist publication in the mining industry. While MINING.COM is a niche publication, it is known for its industry-specific reporting. The article does not appear to be summarising, rewriting, or aggregating content from another publication. The source’s limitations and reach are noted, but McKinsey’s reputation adds credibility.
Plausibility check
Score:
8
Notes:
The article discusses shorter commodity cycles and their impact on trading strategies, aligning with industry trends. The claims are covered elsewhere, including McKinsey’s own publications. The report lacks specific factual anchors, such as names, institutions, or dates, which could enhance credibility. The language and tone are consistent with industry reporting. No excessive or off-topic detail is present. The tone is formal and appropriate for corporate reporting.
Overall assessment
Verdict (FAIL, OPEN, PASS): PASS
Confidence (LOW, MEDIUM, HIGH): MEDIUM
Summary:
The article is timely and based on McKinsey’s analysis, with no significant discrepancies found. However, the reliance on McKinsey’s own publications and press releases for verification introduces potential bias. The lack of independent verification sources and specific factual anchors slightly reduces confidence in the overall assessment.