The “wait and see” era for AI on the buy side is over. In this new survey of 50 buy-side firms across Asia-Pacific, Bloomberg and WatersTechnology reveal an industry that has moved decisively past experimentation and into live, production-grade adoption of AI and automation. From research desks leveraging AI at scale to API-driven dashboards consolidating portfolio, risk, and market data into a single view, firms are retooling their operations to compete in a market that rewards speed, accuracy, and efficiency. The report also charts a growing appetite for private markets exposure — the technology and workflow demands that come with it.

AI adoption moves into production at scale

Various flavors of artificial intelligence have, for some time now, been moving inexorably from proofs of concept and experimental use-cases to live production environments supporting a range of buy-side functions. Nearly three-quarters (72%) of respondents are already using AI moderately and plan to extend their use of the technology in the future. Conversely, only 2% of respondents are not using AI and have no plans to do so, underlining the extent to which the technology has been embraced across the buy side.

Unsurprisingly, research and market analysis are the two business processes most widely supported by the application/adoption of AI, and for good reason: these are functions where speed, scale, accuracy and pattern recognition tend to yield measurable advantages across the buy side. They are also functions into which buy-side firms have traditionally been forced to commit significant resources to make the most judicious, transparent, repeatable and defendable business and investment decisions.

APIs and automation to the fore

In recent years, application programming interfaces (APIs) have emerged as a crucial enabling technology across the buy side, allowing firms to streamline access to data, automate trading workflows, enable application interoperability and generally improve operational efficiency. According to the findings from this survey, buy-side firms most frequently use APIs to support their reporting functions and the creation of custom dashboards (28%), underscoring their role as enablers of real-time analytics and efficient information exchange. That only 16% of respondents do not use APIs demonstrates their widespread acceptance as key components of buy-side firms’ tech stacks and digital ecosystems.

Workflow automation emerged as the principal area impacting respondents’ portfolio management and trading teams, highlighting the importance buy-side firms place on enhancing traditionally manually intensive tasks, not only in the interest of operational efficiency but also to ensure high levels of accuracy and transparency. This drive for operational efficiency is in part fueled by the sector’s shift toward private markets—currently the “darling” of the buy side as firms seek alpha, diversification and yield. Given that these tend to be illiquid assets, portfolio and risk analytics has emerged as a key function for enhanced workflow efficiency.

Key findings

• 72% of firms already use AI moderately, with research and market analysis leading implementation.
• 84% of firms use APIs across the investment life cycle, and 66% are prioritising workflow automation for portfolio management and trading teams.
• 62% of firms plan to grow their private markets exposure, led by private credit, intensifying the need for integrated analytics and reporting platforms.

Operating models under pressure

As buy-side firms confront rising cost pressures, tighter regulatory scrutiny and increasingly complex multi-asset strategies, AI and automation is no longer a future aspiration—it is a strategic imperative. Bloomberg’s technology enables firms to move beyond fragmented systems and manual dependencies toward an integrated, scalable operating model that supports the full investment lifecycle. By streamlining front-to-back workflows, reducing operational risk and embedding robust compliance and reporting controls, firms can replace reactive processes with proactive oversight.

Advanced portfolio construction, risk and data management capabilities deliver the transparency and precision required to support defensible investment decisions across public and private markets. At the same time, centralising data and research within a unified, AI-ready environment allows organisations to eliminate manual bottlenecks in the front and middle offices while ensuring client and regulatory reporting is both seamless and audit-ready.

In an operating environment where efficiency, agility and governance define long term success, adopting Bloomberg’s automation tools can help firms transform complexity into a sustainable competitive advantage.

Benchmark your firm

Whether you’re benchmarking your firm’s AI maturity, evaluating how peers are deploying APIs across the investment life cycle, or building the case for workflow automation in the front office, this report offers important data-backed regional insights.

Access the full survey findings here to find out how your firm’s technology and operational priorities compare to 50 peers across Singapore, Australia and the wider APAC region, and where the industry is heading next.