AI Losers Get Another Chance at Janus Henderson Sustainable Fund
AI-driven volatility has washed out parts of the market that trade on data and ratings. The manager of Janus Henderson's Global Sustainable Equity Fund is buying into the weakness, arguing proprietary data and defensible IP can carry earnings power through the cycle.
Experian and S&P Global have fallen to multi-year lows in early 2026. "These are the ones that are considered the 'AI loser' category, but we've been leaning into some of those because we see attractive valuations," said Hamish Chamberlayne.
Where the value is
Experian trades around 17x forward earnings-more than 30% below its 10-year average. S&P Global sits near 21x, a 21% discount to its historic norm.
Investors have been sorting AI winners from the rest for a year. Media, software, and staffing were hit first; recent stress spilled into finance, professional services, and logistics. Chamberlayne has cut software exposure over the past year.
How the fund is positioned
The fund is classified as Article 9 under the EU's SFDR, making sustainability an explicit objective. Information technology is the largest sector weight-over one-third of the portfolio-and AI is a core theme.
Positioning spans three buckets: AI beneficiaries, AI bottlenecks (the physical infrastructure in short supply), and businesses where AI barely moves the needle. Biotech and sustainable building materials largely fall into that last bucket.
Recent adds include Micron Technology and Seagate Technology, both strong performers over the past six months. The focus: semiconductors, memory, storage, power, and electrification-areas tied directly to data center demand.
EU SFDR Article 9 sets the disclosure bar high, so allocations are built to meet both return and sustainability targets.
Why this matters for finance teams
- Proprietary data and IP can buffer earnings against AI headwinds. Screen for moats, switching costs, and pricing power.
- Use relative valuation. Compare current P/E to decade averages to spot dislocations in information services.
- Treat AI infrastructure as a multi-year capex cycle. Bottlenecks in chips, memory, storage, power gear, and grid upgrades can sustain cash flows.
- Stress-test software and media names for AI-related pricing pressure and margin compression; right-size exposure.
- Operate within Article 9 constraints. Track impact metrics and adverse indicators as you rotate into AI-linked names.
- Watch power availability near data center hubs. Capacity constraints can determine winners across electrification and transmission.
The bigger picture
Chamberlayne expects AI to overtake the energy transition as the top priority for sustainability-focused investors. The concern is broader than emissions-poverty and social equity are in play, echoing recent comments from Bill Gates.
Data center build-out is a multi-year theme, with conservative cost estimates above $3 trillion. "We talk about investing in the AI bottlenecks, the physical bottlenecks around the AI infrastructure trade," he said.
Key tickers mentioned
- Experian Plc (EXPN LN)
- S&P Global Inc. (SPGI)
- Micron Technology Inc. (MU)
- Seagate Technology Holdings Plc (STX)
Actionable checklist
- Run a screen for data/IP moats with depressed multiples versus 10-year averages.
- Map exposure to AI infrastructure demand across semis, memory, storage, power systems, and electrification.
- Re-underwrite software names for AI cannibalization risk; adjust position sizes and hurdle rates.
- In Article 9 mandates, link AI theses to measurable social and environmental outcomes.
For hands-on training on how AI affects investing and portfolio construction, see AI for Finance. ESG teams digging into AI's impact can use the AI Learning Path for Sustainability Analysts.
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