After the AI boom of 2023 and 2024, industry specialists explain where investors should turn next for sustainable gains
artificial intelligence (AI) stocksmay have passed, but wealth managers and venture investors say it remains one of the most compelling multi-year themes for high-net-worth portfolios – provided investors shift from momentum-driven bets to selective, infrastructure-anchored positions.
Raymond Ang, global head of private, SME and affluent clients, and head of wealth and retail banking, Greater China and North Asia, at Standard Chartered, says that AI technology has become an inevitable topic.
“It is not something investors choose to opt into or out of,” he notes. “It is a structural shift that cuts across industries and asset classes.”
Ang’s remarks come despite sobering headlines around AI commercialisation. Cancellations of data centre developments have increased since late 2025, and several high-profile AI firms missed revenue targets ahead of planned initial public offerings.
While public markets are wavering, underlying data shows corporate spending on AI is doing the opposite. Generative AIcaptured nearly half of all private funding in the subsector, while organisational adoption climbed to 88 per cent. The Deloitte-HKU AI Adoption Index 2026 report found adoption highest in customer services (58 per cent), marketing (54 per cent) and IT (53 per cent), with more moderate uptake in R&D and operations (both 45 per cent).
The report also says that executives plan to invest in customer engagement while expanding into innovation-centric functions such as R&D, signalling a strategic shift from efficiency to discovery.
AI’s economic impactshould be seen as being in its early stages rather than plateauing.
He explains that the adoption pattern resembles previous technology cycles. “Infrastructure investment remains strong, but the faster growth is now in the application layer, especially in enterprise adoption,” Wang says.
He describes the pattern as “wide but shallow – exactly what I would expect early in the diffusion of a general-purpose technology”.
Wang goes on to draw a parallel with mobile phone technology, where chips, networks and devices came first before software and applications caught up and captured more incremental value. He adds that “AI application spend as a share of enterprise revenue” remains small but should rise quickly once AI systems begin replacing parts of workflows rather than merely augmenting human workers.
Samir Subberwal, Standard Chartered’s global head of wealth solutions, retail products, data and analytics, says the opportunity has evolved considerably, moving from a concept story to a tangible investible theme which reshapes how enterprises operate and allocate capital. “The most compelling opportunities are in the application and infrastructure layers including leading semiconductor companies and global power and electronification – data centres, power, connectivity and specialist semiconductors – which benefit regardless of which AI model ultimately dominates.”
A November 2025 KKR report said today’s data centre buildout differs from the 1990s fibre optic overbuild: projects are supported by pre-emptive hyperscaler offtake agreements, while power constraints and permitting bottlenecks naturally limit oversupply risk. The report concluded that investors who are focused on execution, unit economics and scarce inputs – power, land, grid access – will be best positioned as AI infrastructure matures.
High-net-worth investors today are more sophisticated and looking beyond the public markets, according to Ang. They are either seeking opportunities to access or are looking to increase their allocation to private assets.
“It is still too early to call clear application-level winners in AI,” Subberwal says, “This is why, rather than making narrow calls on specific AI applications, we encourage clients to think in terms of the entire value chain – from enablers and suppliers through to end users.”
He expects the next phase to reward resilience over speed. “Companies need to demonstrate that their products can be embedded deep into client workflows, supported by reliable infrastructure and recurring demand, not just rapid experimentation. The market will reward those companies with better network effects and return on investment strategy.
“AI requires a disciplined and systematic approach both in public and private markets,” Subberwal adds. “Investing in tech and tech-enabled business models today goes beyond passive exposure; it demands active management to navigate market volatility, business cycles and disruption risks.”