Mitsubishi Heavy Industries Teams Up with AI Company PFN, Morgan Stanley Maintains Overweight

Overview

This is a brief company commentary by Morgan Stanley on Mitsubishi Heavy Industries (7011.T), focusing on the recently announced business alliance with domestic Japanese AI company Preferred Networks (PFN), along with explanations of the valuation methodology and risk factors. The firm believes that amid accelerated global AI adoption, this alliance is poised to become a significant initiative promoting domestic AI technology application in Japan's critical infrastructure and national security sectors, and maintains an 'Overweight' rating with a target price of JPY 5,700 for Mitsubishi Heavy Industries.

Core views

Alliance Content and Significance: The report indicates that Mitsubishi Heavy Industries and PFN have formed a business alliance aimed at enhancing the intelligence and autonomy of critical equipment and systems while reducing reliance on foreign technology. The firm believes this alliance brings two clear benefits—advanced edge AI capabilities and enhanced security and reliability. Based on the alliance progress, both companies plan to sign a capital and business alliance agreement within the F3/27 fiscal year. Assessment of Mitsubishi Heavy Industries: The report notes that Mitsubishi Heavy Industries has previously been promoting the application of its own AI technology in R&D, manufacturing, and operations across its businesses, and this collaboration with an AI-focused company is expected to bring more in-depth application and innovation. Rating and Valuation: The firm maintains an 'Overweight' rating on the stock with an 'Attractive' industry view and a target price of JPY 5,700. The current price (as of market close on June 2, 2026) is JPY 3,516, with a market capitalization of approximately JPY 1,181.47 billion. The valuation method applies a 40x NTM (next twelve months) P/E (based on the F3/26 annual average) to the EPS forecast for F3/28. The firm set the target P/E at the recent historical average (higher than earlier levels) and believes this valuation level can be maintained given solid order backlog and demand momentum.

Analysis framework

The firm employs the 'forward P/E × expected earnings' valuation approach: first establishing a reasonable P/E multiple (here 40x based on the F3/26 annual average NTM P/E, which is at the recent historical average), then multiplying it by earnings forecast for a future year (EPS for F3/28) to derive the target price. In justifying why this multiple is reasonable, the firm doesn't simply use the historical average but provides supporting logic: solid order backlog and demand momentum indicate high visibility of earnings performance, thus justifying the maintenance of the higher historical average valuation level. This approach of 'using orders and demand to support the valuation anchor' is a common analytical method for mechanical and heavy industry companies.

Methodology notes

• Valuation MethodologyPE/PEG valuation

  Deriving target price by using forward P/E (NTM P/E) multiplied by EPS forecast for a future year

  The core of P/E valuation is 'how many multiples × how much earnings'. In this report, the firm uses a 40x NTM P/E multiplied by EPS forecast for F3/28 to get the target price. The multiple is taken from the recent historical average, effectively using 'the valuation level the market is willing to provide' as the anchor.

• Industry/Industrial Analysis FrameworkSupply-demand framework

  Using order backlog and demand momentum as basis for earnings visibility and whether valuation can be maintained

  For companies driven by large orders in heavy industry and machinery sectors, a larger backlog of undelivered orders translates to more certain future revenues. In this report, the firm uses 'solid order backlog + demand momentum' to justify that the higher historical average valuation can be maintained, reflecting the approach of judging earnings sustainability from the demand side.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• Mitsubishi Heavy Industries (7011.T)

  As the alliance party, benefits from domestic AI technology implementation through collaboration with PFN, enhancing intelligence, autonomy, and security of equipment in critical infrastructure and national security sectors

  Strengths

  Previously promoted application of own AI technology in R&D, manufacturing, and operations; solid order backlog and strong demand momentum supporting higher valuation; 'Overweight' rating with target price of JPY 5,700

  Risks

  Energy throughput expansion slower than expected, project cost overruns, Middle Eastern geopolitical tensions and supply chain disruptions, structural decline in power demand due to advances in AI/semiconductor/server technology

Key data

• Target PriceJPY 5,70012-18 month target price corresponding to 'Overweight' rating
• Current PriceJPY 3,516Market close price as of June 2, 2026
• Target P/E40xF3/26 annual average NTM P/E, taken from recent historical average, applied to F3/28 EPS forecast
• Market CapApproximately JPY 1,181.47 billionBased on current basic share count
• Daily Average Trading VolumeApproximately JPY 123.1 billion

Impact & implications

The report believes that through its alliance with PFN, Mitsubishi Heavy Industries can gain stronger edge AI capabilities and higher security and reliability in critical equipment and systems, while reducing reliance on foreign technology. Considering the company has already applied its own AI technology in multiple businesses, collaboration with a specialized AI company is expected to further promote in-depth AI application and innovation. Based on this, the firm maintains a positive view on the stock.

Risks

• (Upside) Faster progress in defense exports
• (Upside) Increase in Japan's defense spending
• (Upside) Energy and defense capacity demand exceeding assumed levels
• (Downside) Energy throughput expansion slower than expected
• (Downside) Cost overruns at project level
• (Downside) Middle Eastern geopolitical situation and supply chain disruptions affecting production
• (Downside) Structural decline in power demand due to advances in AI, semiconductor, and server technology

What to watch

• Whether Mitsubishi Heavy Industries and PFN can sign a capital and business alliance agreement within the F3/27 fiscal year