Mark Lovett, Head of Investments at Stanlib Asset Management
A structural shift, not a passing trend Artificial intelligence has entered the global economy with unusual speed and conviction. For investors, this is not a marginal technology story. AI is a structural force that is reshaping how capital is allocated, how industries compete and how risk is priced. Its significance lies not in novelty, but in its capacity to alter productivity, margins and long-term business models.
The asset management industry has lived through major transformations before. The Japanese commercial property boom of the 1980s, the dot-com surge of the 1990s and the US housing bubble that culminated in 2008 were all fuelled by optimism, rapid capital deployment and compelling narratives. Each cycle ultimately tested the discipline of investors as much as the promise of the underlying idea. Viewed through this history, the rise of AI is not an isolated technological shift, but the next major test of investor judgement that demands both perspective and discipline.
Lessons from past cycles
AI inevitably invites comparison with the internet revolution. The scale of infrastructure investment is similar, and the sense of inevitability is familiar. Yet the difference this time is the quality of the foundations. Much of today’s AI investment is taking place within established businesses with real revenues and scalable operations. This makes the opportunity more credible, but it does not eliminate risk. And because bubbles rarely announce themselves while they are forming, it becomes essential to look back at previous cycles to help frame the right questions rather than simply fuel enthusiasm.
From an investment perspective, the question is not whether AI will matter, but how value will be created and sustained. History suggests that technology alone is never enough. What matters is whether capital is supporting robust business models rather than narrative momentum.
Productivity, margins and competitive advantage
The most immediate impact of AI is being felt through productivity. Unlike earlier disruptions that centred on manufacturing, this wave is reshaping the services economy. Advertising, finance, logistics, legal services and customer engagement are already changing as AI tools compress cost structures and accelerate decision-making. Even creative industries are being redefined as machine learning augments human output.
For investors, this has clear implications. Companies that integrate AI effectively can improve operating leverage, enhance margins and strengthen competitive positioning. Those that fail to adapt risk structural pressure on profitability. Over time, these dynamics will redraw the competitive landscape within sectors.
Discipline in an efficient market
AI also changes how markets behave. Faster data flows and sharper signals leave less room for sentiment to obscure fundamentals. While this can improve efficiency, it raises the stakes for error. Misjudgements are exposed more quickly, and volatility can increase as information is absorbed at speed.
In this environment, discipline becomes the anchor. Every innovation cycle brings hype, and AI is no exception. New announcements and ambitious claims surface almost daily and for investors, the challenge is to separate durable value from clever marketing. A familiar warning sign remains relevant: when capital starts backing unproven or weak business models, it usually signals that a cycle is nearing its peak. While we have not yet crossed that line, the pace of development makes continued scrutiny essential.
The changing nature of investment judgement
AI is also reshaping the investment profession itself. Entry-level roles that once relied on manual analysis are disappearing as machines take over repetitive tasks. While this improves efficiency, it changes how future investors are trained. Learning becomes more self-directed and less structured. For established professionals, the implication is clear: AI must be embraced as a tool that enhances judgement, not as a substitute for it.
The future of asset management will be hybrid. Data-driven models will accelerate analysis and surface insights, but human judgement will remain essential in interpreting uncertainty and allocating capital responsibly. In a world saturated with information, discernment becomes the true advantage.
Risk is not removed, only redistributed
AI does not eliminate risk. It redistributes it. As markets become more efficient and competition intensifies, the consequences of poor capital allocation grow. This places a premium on strong management teams, disciplined processes and long-term thinking. Flexibility and adaptability become core investment attributes rather than optional extras.
A test of investor response
AI may prove to be the defining disruption of this generation. Whether it delivers sustainable growth or becomes another cautionary tale will depend less on the technology itself and more on how investors respond. The market may be moving faster than ever, but the principles of sound investing remain unchanged. Human insight, applied with discipline and perspective, still determines outcomes.
ENDS
