Within 10 years, artificial intelligence is expected to learn how to identify asset correlations that human analysts can never detect.

Artificial intelligence (AI) is no longer a futuristic abstraction for the asset and wealth management industry. It is already reshaping how firms analyse markets, construct portfolios and manage risk. From high-frequency trading to robo-advisory services, AI is transforming financial decision-making at an unprecedented pace.

But how will this evolution unfold over the next decade? It is important for forward-thinking asset managers to start thinking about how their business model will be impacted in the by AI in the short, medium and long term.

Incremental automation

In the immediate term, AI’s influence will manifest primarily in efficiency gains and automation. Asset managers are already leveraging machine learning to process vast datasets, automate routine reporting, and streamline compliance functions. AI-driven natural language processing tools are also being deployed to scan regulatory changes, ensuring firms remain compliant in a rapidly evolving legal landscape.

Risk management, too, will see short-term improvements. AI algorithms can analyse millions of data points in real-time, identifying market anomalies or shifts before human analysts can. This allows firms to mitigate exposure to sudden market downturns or liquidity risks — essentially serving as an early warning system for financial turbulence.

Meanwhile, robo-advisers are becoming more sophisticated, helping investors with portfolio rebalancing and trade execution based on predefined parameters.

Despite these advancements, human oversight remains critical. While AI can process information faster, strategic decision-making continues to rely on human intuition and experience. The challenge for asset managers in the short term will be integrating AI without over-relying on its outputs — because, as we all know, the last thing we need is an AI with a gambling problem running a hedge fund.

Predictive analytics

Looking further ahead, within a five-year plan, AI will become increasingly integral to investment strategies. One of the most significant developments will be refinement of predictive analytics, allowing asset managers to anticipate market movements with greater accuracy.

Machine learning models will continuously refine themselves, leveraging alternative data sources — ranging from satellite imagery to social sentiment analysis — to detect subtle market signals before they become apparent through traditional financial metrics. For instance, if an AI can figure out that increased pizza deliveries in Silicon Valley mean tech stocks are about to boom, we should probably listen.

AI-driven personalisation will also become a dominant theme. Investors, particularly high net worth individuals, will demand bespoke solutions tailored to their unique risk appetites and financial goals. AI will enable asset managers to construct hyper-personalised portfolios, dynamically adjusting them based on real-time market conditions and individual preferences — because nothing says ‘cutting-edge finance’ like an algorithm that knows your latte order and your risk tolerance.

Regulatory compliance will continue to evolve alongside AI adoption. As algorithms take on a greater role in investment decisions, regulators will likely introduce stricter oversight to ensure transparency and mitigate the risks of algorithmic bias. Asset managers will need to invest in explainable AI — systems that provide clear reasoning behind their decisions — to maintain investor trust and regulatory compliance.

Autonomous asset management

By 2035, AI could redefine the very nature of asset management. Autonomous investment platforms — capable of managing entire portfolios without human intervention — may become the norm. These systems will not only execute trades but also develop investment theses, continuously adjusting strategies based on shifting macroeconomic conditions, geopolitical events and market sentiment.

At the same time, AI’s role in fundamental analysis will evolve. Instead of merely optimising existing strategies, AI may develop entirely new investment paradigms, identifying asset correlations that human analysts would never detect. This could lead to the emergence of novel asset classes and trading strategies, potentially reshaping financial markets — because if we’ve learned anything, it’s that technology always finds new and exciting ways to make things weird.

However, such a transformation will bring significant challenges. Questions around accountability, transparency and ethical considerations will need to be addressed. As AI-driven funds gain market dominance, concerns about systemic risk will intensify —particularly if multiple firms rely on similar algorithms that could inadvertently amplify market volatility.

The industry’s workforce will also undergo a transformation. While AI will eliminate some traditional roles, it will create new opportunities for professionals skilled in data science, AI ethics, and financial engineering. The future asset manager will not simply be an investor but also a technology strategist, navigating the intersection of finance and machine learning. So, if you’re not already brushing up on your Python programming skills, now might be a good time.

The road ahead

For firms which specialise in data-driven investment insights, the coming decade represents both an opportunity and a challenge. Successfully integrating AI requires more than just technological adoption. It demands a strategic rethink of business models, investment philosophies, and regulatory engagement.

In the short term, asset managers should focus on leveraging AI for operational efficiency and risk management. Over the next five years, they must embrace predictive analytics and personalised investment solutions while ensuring regulatory alignment. In the long run, those who position themselves at the forefront of autonomous asset management and AI-driven innovation will emerge as industry leaders.

The asset and wealth management industry is on the cusp of a revolution. Whether AI becomes an enabler of superior investment performance or a destabilising force will depend on how firms navigate its rapid evolution. But one thing is certain: ignoring AI is no longer an option. And if you think you can, well good luck competing with an algorithm that doesn’t sleep, doesn’t take coffee breaks, and definitely doesn’t get emotional over a bad earnings report.

Giuseppe Sette, co-founder and president, Reflexivity