Artificial intelligence (AI) is having a profound impact on the funds industry with widespread adoption of both generative AI and agentic AI speeding up processes and reducing costs. The former is being used to prepare and process documentation while the latter is being used to manage end-to-end workflows, particularly where the systems involved in the workflow are legacy and were not previously connected. “Artificial intelligence is no longer a peripheral tool in the investment ecosystem; it is becoming an important part of how firms manage information, documentation and decision-support processes. We are seeing its impact in areas such as investment documentation, regulatory workflows, due diligence, investor communications and internal process management,” says Chris Burge, cofounder of Spark Venture Funding. Generative AI is already helping to streamline the creation and review of complex documents, reducing some of the administrative burden that has traditionally driven costs. More advanced AI tools are also beginning to support faster, more informed decision-making across operational and analytical functions, particularly where teams need to review large volumes of information or carry out structured assessments.“The real value is not that AI replaces human judgment, but that it can make work more structured, more efficient and easier to monitor. As adoption deepens, AI should continue to drive efficiencies, with clear potential to reduce parts of the industry cost base, particularly in documentation-heavy and compliance-heavy areas,” Burge observes.Recent research on assets under management (AUM) by PwC posited that throughout the funds industry as AUM continue to grow the margins earned on those assets will continue to shrink. In an effort to mitigate this impact, asset managers see AI integration and automation as the most important actions they are taking today to transform and future-proof their business models. This is reflected in the rapid growth of AI investment, which is set to increase several-fold.“While many firms today still focus on isolated use cases, such as automating know-your-customer tools, the real opportunity lies in developing integrated AI strategies right across the business that transform portfolio performance, client engagement, and operations,” says Ray Daly, director of asset and wealth management at PwC Ireland. “Asset and wealth managers will be able to move beyond individual solutions to embed AI and other disruptive technologies into the core of their business models. This will help them deliver intelligent solutions for clients, improve outcomes and boost profitability.” Ray Daly, director of asset and wealth management, PwC Ireland An August 2025 report from BlackRock on how AI is transforming investment shows the technology has transitioned from an experimental theme for organisations into what it terms “a core structural buildout with specialised models that are now integrated into the market and equity strategy and equity portfolio construction”. This shift, it says, highlights the evolution of AI from general purpose tools to specialised applications within investment and business processes.Crucially, it says AI is now navigating the themes driving markets, producing powerful insights that inform investment decisions. “Themes can span a wide range of topics from secular trends to emerging mega forces and tend to drive meaningful returns across securities that may otherwise be unrelated. They often cut across traditional boundaries like industries, styles or geographies.”Nonetheless, the report observes that we are not at the stage where we can take the human out of the process entirely, noting that its own Thematic Robot tool uses a blend of human insight with the power of large language models and big data to build equity baskets with more efficiency and a greater breath of exposure.Daly agrees that all AI driven processes should have a “human in the loop”. “Ultimately, if organisations have not set the foundations around data quality coupled with a responsible deployment of the AI solution, then that organisation will be vulnerable to misguided insights and strategy decisions.” According to Aidan Connolly, chief executive of Idiro Analytics, AI can definitely be used to enhance returns in the funds industry. “You can fine tune an AI model so that it becomes an expert in a particular asset class, for example. Data is always the key. Larger players have access to a lot of data themselves and the resources to acquire third-party data too that will drive better investment decisions.”Aidan Connolly, CEO, Idiro Analytics Set against that, AI can also act as a leveller and heightens the possibility for disruption from newer and leaner operators, one clear way in which costs can be lowered and returns to customers could be enhanced. AI models can be built much cheaper and quicker now, Connolly notes. “The difference between the superpowers and the mere mortals has narrowed significantly,” as he puts it. “You could have a disrupter who is lean and nimble that focused on a very specific investment niche and double downs on it very successfully.”AI could put significant power in the hands of individual investors too but Daly cautions that this greater power also involves greater responsibility and heightened risk.“I think the prevalence of AI tools will enable individuals to access and analyse more data than previously was possible or cost effectively available to them. This comes with benefits for individuals who can trade/invest more freely than they may have been able to historically. “However, individuals may be exposed to greater LLM [large language model] risk such as hallucinations or bias based on the data used to train those LLMs. If individuals choose to use these tools to inform investment decisions they make, necessary due diligence and testing should be performed on those tools to understand how they were built, what data was used to train them etc so that the user understands what the tool is doing and how the outcome is derived,” he concludes.