Today's tech blogger: Mitra Heravizadeh, Chief Technology Officer and UBS Technology Fellow

A new era of intelligence

Agentic AI, marks a strategic inflection point in organizational transformation. At UBS, it’s not a trend we’re reacting to, it’s part of our clear, strategic ambition to become an AI-enabled institution.

This needs a uniquely coherent and comprehensive framework for value creation. One that extends far beyond automation, focusing instead on embedding AI into the very fabric of our operations, decision-making, and client engagement.

Mitra presenting on the stage
Agentic AI systems are capable of independently gathering data, making decisions, and executing multi-step tasks across digital environments. This shift is not incremental – it's foundational.

It requires rethinking digital architectures, operational models, and governance frameworks to fully harness the potential of autonomous AI agents.

These agents can autonomously manage processes such as market trend prediction, customer service resolution, and financial operations - functions that previously required significant human intervention. They’re not just tools; they’re intelligent collaborators.

As we move from experimentation to deployment, agentic AI is becoming a core component of our digital strategy. The pace of adoption is unprecedented, and the implications are profound.

Shaping architecture for agentic AI and human collaboration

To fully leverage agentic AI, we need to reimagine our digital architecture. Key elements of this shift involve:

  • Agent marketplaces: platforms where AI agents can be discovered, integrated, and orchestrated
  • Multi-agent systems: distributed networks of agents collaborating to achieve business goals
  • Composable infrastructure: modular systems that support dynamic agent coordination

These architectural changes require new design principles – ones that prioritize agility, interoperability, and continuous learning. It’s imperative to actively invest in these capabilities to ensure scalability and resilience.

As decision-making becomes embedded and automated, human roles will evolve. Execution will increasingly be handled by AI agents, while human teams focus on:

  • strategic oversight
  • innovation and design
  • relationship management
  • governance and compliance

This shift means we can move from reactive problem-solving to proactive opportunity creation, unlocking new levels of productivity and creativity across the organization.

Operational models for agentic AI

Implementing agentic AI requires new operational paradigms, meaning we need to explore models where IT functions evolve to manage AI agents. This includes:

  • defining agent responsibilities and permissions
  • monitoring agent behavior and outcomes
  • ensuring compliance

Such models are essential for maintaining control and accountability in autonomous systems.

Agentic AI is not a future trend – it's a present reality. We’re actively exploring its potential to transform, enhance client experiences, and drive operational excellence. It’s not about adapting – it’s about shaping the future.

The agentic AI center of excellence: enabling scalable transformation

To ensure responsible and scalable adoption of agentic AI, we’ve established an agentic AI center of excellence (CoE) that will drive innovation, ensure high-quality implementation, and maintain responsible and consistent practices across the organization.

It’s important that agents across the business communicate, collaborate, and operate together in a compliant, secure, and ethical manner. We have to maintain efficiency while upholding quality standards. Freedom without guardrails can lead to delays, rework and potential failures. With a clear blueprint, we can move faster and with confidence. Creating an agentic AI CoE and related standards creates a shared language across engineering, data science and compliance teams.

Digital interactive concept

I’m looking forward to the exciting opportunities ahead as we continue to grow and collaborate.

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