Strategies for AI Adoption – Insights from SS&C’s Zeynep Hizir

Dr. Zeynep Hizir, Senior Director at SS&C GlobeOp, drives clients’ AI adoption and integration by aligning AI strategy with operating-model design and embedding governance, security and compliance across enterprise transformation programs. In this Q&A, Zeynep outlines the realities of AI adoption, the common patterns behind success and failure, and how SS&C helps clients move beyond experimentation to achieve measurable, compliant and operationally robust outcomes.

What was the biggest challenge for you in 2025?

The biggest challenge has been cutting through the noise and hype to focus on real value. AI is evolving faster than most governance, strategy and regulatory frameworks can keep up with, and even experts are recalibrating what “success” truly looks like. At the same time, the pressure to update data foundations, lineage and traceability is exposing gaps many firms weren’t aware they have.

Yet the fundamentals haven’t changed: without high-quality data, consistent processes and a clear operating-model design, AI cannot deliver measurable outcomes, no matter how advanced the technology becomes. Technology accelerates value, but it cannot compensate for structural gaps.

It’s been estimated that around 95% of enterprise AI projects still fail to show a tangible return on investment (ROI). It would be easy to blame the technology, but failure is usually because of leadership misalignment, scattered objectives and inconsistent data readiness. Scaling AI requires clarity of purpose, disciplined use-case selection and a shift from isolated pilots to enterprise-level execution; and many firms are still early in that transition.

And we’ve seen this dynamic before. When RPA first emerged, expectations were sky-high, but early wins were limited to narrow, rules-based tasks. As firms tried to scale, the constraints became clear; the technology could only go so far without integrated data, process redesign and human oversight.

It wasn’t the technology that failed; it was the way it was implemented. The same pattern applies to AI, and as we move into 2026 the real challenge for firms is no longer experimentation, but disciplined execution—grounding AI in measurable, compliant and scalable business value.

What innovations does SS&C have in play, and what impact will they have on client operations?

SS&C’s innovation strategy focuses on building AI that is usable, governed and scalable across financial operations. Instead of isolated tools, we are developing an enterprise AI architecture that brings together agentic automation, finance-grade models and a governance layer designed for regulated environments. This is how clients move from experimentation to real operational value.

A major area of progress is SS&C Blue Prism’s agentic automation framework and the introduction of Agent Workflows. These AI-enabled agents can interpret data, reason and act across processes—far beyond traditional rules-based automation. Agent workflows allow agents, humans and legacy systems to operate in a coordinated, decision-led sequence, reducing manual intervention and operational drag.

Alongside this, we are investing in finance-focused models and the “product layer” that sits above raw large language models (LLM); the guardrails, auditability, security controls, and explainability that make AI viable inside regulated institutions. SS&C’s AI Gateway is central here; it provides policy-driven oversight, role-based access and model-agnostic safeguards aligned with expectations under the EU AI Act and operational-resilience requirements reinforced through the EU’s Digital Operational Resilience Act (DORA) and related regulatory updates.

The underlying belief is simple: enterprise AI is not a model-selection exercise, it is an operating-model redesign. AI creates value only when governance, workflows and decision rights evolve alongside technology. Our innovations reflect that reality, enabling measurable, compliant and scalable outcomes across core financial operations.

How are you helping clients make the most of their investment in AI?

Our approach is to focus on a small number of high-impact opportunities rather than trying to deploy AI everywhere at once. Most firms don’t have the capacity to run dozens of initiatives in parallel, and spreading effort too thin dilutes measurable value. Concentrating on three to five priorities creates clarity and momentum.

We help clients pinpoint where AI can meaningfully improve execution quality or strengthen controls, then design business cases that scale safely. This includes assessing where agentic workflows can streamline end-to-end processes and where AI Gateway guardrails are needed to ensure security, auditability and consistent governance.

Across functions such as fund accounting, reconciliations and compliance, the focus is on embedding AI into the operating model. Agentic automation takes on mechanical work, while AI Gateway keeps every interaction governed and transparent. When technology, governance and people evolve together, firms move beyond pilots into measurable, compliant transformation.

What advice do you have for fund managers looking to make the most of their investment?

Start with the foundations, but don’t wait for perfection. Better data, clearer processes and a coherent operating model accelerate value, and AI can support that improvement rather than simply exist behind it. Resource-light firms in particular benefit when AI and process enhancement run in parallel, supported by governance and clear decision rights from the outset.

Focus priority on a small number of use cases that can scale and materially improve execution quality, liquidity insights, reporting accuracy or unit cost per AUM. Rather than layering AI onto legacy workflows, redesign the process for how it should work end-to-end, then deploy agentic workflows to orchestrate those steps. This is where AI reduces friction and cycle times without demanding large transformation budgets upfront.

Be pragmatic about build versus buy. Firms accelerate faster when they partner with specialist AI providers who bring domain expertise, governance frameworks and proven technology. Keep human judgment in the loop for oversight, escalation and exception handling, and address governance guardrails early, even if full deployment is further out.

Where do you think AI will have the greatest influence on operations over the next five years?

The biggest shift will be the rise of agentic operations; intelligent digital workers embedded directly into workflows, able to observe, decide and execute defined tasks end-to-end. They won’t just support processes; they will run large parts of them. Trade lifecycle processing, reconciliations, onboarding, KYC, liquidity reporting and other high-volume decision flows will become faster, more consistent and more resilient as machines take on the mechanical work.

As this happens, explainability and accountability will become non-negotiable. Regulations such as the EU AI Act and operational-resilience expectations under DORA will push firms away from black-box models and toward transparent, auditable systems built to withstand scrutiny.

AI governance and AI security will emerge as disciplines in their own right, integrating alongside cybersecurity and data protection. With fraud and financial crime growing more sophisticated, firms without AI-enabled protection will be outpaced by both competitors and attackers.

We are also seeing a shift from competition to partnership in the AI ecosystem. The future will be built on collaboration between providers, clients and regulators; shared learning rather than isolated development.

AI is no longer an innovation project; it is an operating mandate. The firms that will lead are those moving now—strategically and securely—letting machines do the work while humans stay firmly in command of the outcomes.

Contact us to learn more about how SS&C can help you implement AI strategically.

About Dr. Zeynep Hizir: With a doctorate focused on Robotic Process Automation (RPA) and a long career at the heart of financial services, Zeynep brings a rare 360-degree perspective across front, middle, and back-office operations, and a deep understanding of how AI can transform them.