Buy-Side AI Adoption Jumps: From Pilots to Front-Office Standard in 2026
AI is now embedded in day-to-day investment work. A new SimCorp survey shows about seven in ten (70%) buy-side firms are successfully using AI to support the front office. A year ago, only ~10% were actively exploring tools, even though 75% saw the potential. The study covers 200 executives at asset managers, pension funds, and insurers worldwide, fielded by WBR Insights for the 2026 InvestOps Report.
"AI adoption has dramatically shifted from pilots to business-critical applications in the front office," Peter Sanderson, CEO, SimCorp, said. The focus has moved from experimentation to measurable impact. Use cases span staff productivity, regulatory support, data management, and client reporting.
What leaders should take from the data
Two priorities stand out: consolidating vendors and platforms (58%), and modernising architecture and data infrastructure (54%). Both are prerequisites for scaling AI, automating workflows, and keeping tech stacks clean. In other words: fewer tools, better data, tighter controls.
Investment drivers are shifting too. For the first time in three years, competitive differentiation through innovation (55%) outranks operational efficiency (33%) and cost control (44%) as the top reason for tech and ops spend. As AI matures, vendor stability (57%) now matters more than feature breadth when evaluating solutions.
Translate the findings into action
- Consolidate your vendor footprint. Reduce integration overhead, simplify security, and free up budget for the data work AI depends on.
- Modernise data and architecture. Invest in clean data pipelines, lineage, access controls, and model monitoring before chasing new features.
- Prioritise vendor durability over bells and whistles. Validate financial health, roadmap clarity, security posture, and client references.
- Focus on front-office outcomes. Target idea generation, risk flagging, execution support, and client personalisation-paired with strong supervision and audit trails.
- Tighten compliance and model risk. Document models, ensure explainability where required, and keep humans in the loop for high-impact decisions.
- Upskill teams where the work happens. Analysts, PMs, risk, and operations need practical training, not theory. See role-based AI learning paths.
- Measure business impact. Track cost/income improvement, time saved per task, error rates, STP rates, and client responsiveness.
Why vendor consolidation isn't optional
Multiple overlapping systems choke AI's value. Each extra platform adds data silos, conflicting models, and maintenance drag. A tighter stack lowers latency, improves data quality, and makes governance manageable.
The priority shift: innovation first
With 55% citing innovation as the primary driver, boards are signalling a clear mandate: use AI to create differentiated strategies and client experiences. Efficiency and cost still matter, but they're no longer the headline. Budget requests should tie to new revenue, faster time-to-insight, and client retention-then show the cost wins as a byproduct.
A practical example: flipping the 80/20
Switzerland-based Linvo says it has integrated AI across asset management operations and aims to flip the 80/20 split-less time on admin and compliance, more time with clients. Claims of 10x productivity deserve healthy scrutiny, but the direction is right. If AI cuts administrative time in half, the cost/income impact alone is material, even before better client outcomes land.
90-day execution checklist
- Inventory all AI pilots in the front office. Rank by business value and risk, and pick two to scale with clear controls.
- Stand up a lean data and model governance framework. Define owners, approval paths, documentation, and monitoring.
- Rationalise your vendor stack. Remove duplicative tools and negotiate enterprise terms with the platforms you'll scale.
- Run vendor stability diligence. Review financials, security certifications, SLA history, and reference clients.
- Launch targeted training for PMs, analysts, risk, and ops. Focus on workflows and prompts they'll use daily.
- Set KPIs and a monthly review cadence. Tie results to P&L, client experience, and risk metrics.
Source organisations: SimCorp and WBR Insights.
Your membership also unlocks:
