Jonathan Wellum says AI is disrupting markets unevenly, creating both real threats and selective value opportunities. He remains constructive on moat-protected businesses, energy/infrastructure, and gold, while warning that expensive markets, tariff noise, and large drawdown risk justify caution, cash, and discipline.
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This Wealthion interview features Maggie Lake asking Jonathan Wellum, CEO/CIO at Rocklink, about how to invest through AI disruption, elevated valuations, tariffs, energy demand, and precious metals. Wellum’s main framework is that AI will be disruptive, but not every company is equally exposed. He argues investors should focus on businesses with durable moats: high switching costs, network effects, brand trust, regulatory barriers, capital intensity, and protected data. He gives examples of businesses he thinks the market may be mispricing on AI fear, such as ServiceNow and Thomson Reuters/Westlaw, while cautioning that some software and service models may face more pressure. He then uses several value-investing examples to show why patience matters. …
The immediate setup favors selectivity over aggression: AI-related selling can still create pockets of opportunity, but crowded growth names remain fragile and broad index exposure looks vulnerable. Cash, sizing discipline, and avoiding pure-play AI exposure are the main tactical defenses.
Over the next few months, the market likely continues rotating toward businesses that can use AI as an incremental boost rather than depend on it entirely. Confirmation would come from fundamental improvement in moat-protected names; the main invalidation would be a sharp reversal in the quality/value rotation or an unexpected macro shock.
Structurally, this points to a more active, moat-focused market where AI acts as an amplifier for some incumbents and a threat to others. Gold and hard assets stay relevant as long as debt, deficits, and currency-debasement pressures remain unresolved.
AI will be disruptive, but the market is likely overreacting in some names and underreacting in others.
He repeatedly says AI has both benefits and business-model damage, and that the market has sold off some companies too indiscriminately.
Businesses with high switching costs, network effects, brand trust, regulatory barriers, capital intensity, and protected data are more defensible in an AI world.
He explicitly lists these moat characteristics as the filter for selecting durable companies.
ServiceNow is an example of a business he bought during the AI selloff because it became unusually inexpensive and still has a strong moat.
He says they started buying around 130 down to 100 and that insiders were buying too.
How should value investors redefine a wide economic moat in an AI-disrupted market?
He says investors should focus on businesses with strong switching costs, network effects, brand trust, regulatory barriers, capital intensity, and specialized patent-protected data. He argues AI will hurt exposed models while leaving more protected businesses intact, though the full impact is still uncertain.
How do you stay disciplined and patient when markets swing between AI euphoria and AI doom?
He says the key is being patient through volatility and trusting the process. He gives an example of Tora, where a major write-down hammered the stock, but the business was fundamentally safe and the company remained intact.
Where do you see the best value in the AI and electrification ecosystem?
He says the best value is where they understand the business and can do the research. He highlights unregulated utilities, Brookfield Renewable and Brookfield Infrastructure, uranium through Cameco, data-center-adjacent real estate like Prologis, equipment makers such as Eaton and Schneider Electric, and small exposure to copper through Power Metallic.
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