Building AI-Fluent Product Designers at DBS Business Design

The Challenge: Turning AI Interest into Applied Design Capability

DBS is one of the most AI-forward financial institutions in the region, and its design teams sit at the intersection of product, technology and user experience. As the bank moves quickly to embed agentic AI and automation across the organisation, designers are increasingly expected to understand, evaluate and contribute to AI-driven initiatives rather than simply observe them. Leaders recognised that interest alone was not enough — the team needed its designers to be able to apply AI confidently and responsibly in their day-to-day work.

Because the team works with sensitive product and customer context inside a regulated bank, any training had to stay directly relevant to real design workflows while respecting the compliance and data governance considerations of a financial institution. A generic, off-the-shelf AI course would not have addressed the specific realities of design documentation, UX research and stakeholder communication, nor the governance obligations that come with deploying AI inside DBS.

What the team wanted was a programme that moved beyond awareness into hands-on building — one that let designers design and deploy real workflows using their own professional context, and that treated responsible AI use as a core part of the learning rather than an afterthought.

Why Heicoders Academy: A Trusted, Contextualised Partner

Heicoders Academy came recommended from within the team itself, with the team's lead having completed both the AI and Python programmes at Heicoders and experienced the depth of the curriculum first-hand. From the first discovery conversations, the Heicoders team focused on tailoring the engagement to the design team's operational realities rather than delivering a standard syllabus. Microsoft Copilot was set as the primary prompt engineering tool throughout the foundational lessons, aligned to the M365 environment the team uses daily, and design-specific workflows and use cases were woven across the agentic AI and automation sessions.

GA100 also offered the depth the team was looking for. As an SSG-accredited programme built around real tools and real business scenarios, it gave the team a credible, structured path from foundational prompting all the way through to building and deploying agentic workflows, with responsible AI woven throughout.

The Solution: A Private, Customised GA100 Run for the Design Team

Heicoders Academy delivered a private, customised run of GA100 exclusively for the DBS Business Design Team. The programme ran across three training days in August 2026, beginning on 14 August, delivered in-person at DBS premises in Marina Bay for a cohort of 18 designers. Microsoft Copilot anchored the foundational prompt engineering lessons in line with the team’s M365 environment, before the cohort moved into building with agentic tools. The curriculum progressed deliberately across five core areas:

• Generative AI Basics and Prompt Engineering: How Large Language Models work, key AI tools (ChatGPT, Copilot, Gemini), advanced prompting techniques including chain-of-thought and few-shot prompting, and AI-powered media creation.
• Advanced Workflows and AI Agents: A hands-on lab using Manus AI to build and deploy multi-step automated workflows across 9 real-world business scenarios, including email automation, data analysis, wide research, spreadsheet automation, and slide generation.
• Agentic Workflow Automation with n8n: Building powerful automated pipelines by connecting multiple applications and services to automate common business processes such as data extraction and report generation.
• RAG for Business Data: Learning how to combine AI with the organisation's internal data to create reliable, factual knowledge bases and secure private AI systems.
• MCP and Managing AI Risk: Applying frameworks for safe, compliant, and ethical AI use in an enterprise setting, culminating in a hands-on Capstone Project where participants applied their full suite of newly acquired skills.

Throughout the run, examples and hands-on exercises were grounded in the design team’s real work, from UX research and design documentation to stakeholder presentation content and internal design system knowledge. Around the curriculum, Heicoders Academy provided end-to-end wraparound support — from enrolment and registration onto its Student eLearn portal, to handling the government funding administration on behalf of the organisation, coordinating venue logistics, and supporting eligible participants through the WSQ assessment component. This allowed the design team to focus entirely on the learning experience while the operational details were managed for them.

Results: A Full Cohort of Designers Trained and Engaged

The engagement brought together a full cohort of 18 designers for the complete GA100 programme, giving the Business Design Team a shared, hands-on grounding in applied and agentic AI. Throughout the run, participants worked directly with the tools, building and deploying workflows rather than simply observing demonstrations.

Engagement across the cohort was strong, and the sessions were well received by both participants and the team's leadership. By the end of the programme, designers had moved from understanding what generative AI can do to actively applying it, with a clearer view of how these capabilities could support design research, documentation and everyday product work within a responsible, compliant framework.

What's Next: Extending Applied AI Across the Design and Product Functions

With a first cohort now trained, the foundation is in place for DBS to continue building AI capability across its design and product teams. Heicoders Academy looks forward to supporting DBS on that journey, whether through further cohorts, deeper role-specific applications, or continued advisory support as the team embeds AI into its everyday work.

The DBS Business Design run reflects how Heicoders Academy partners with regulated, forward-leaning organisations: starting from the team's real operational context, keeping the learning practical and hands-on, and pairing it with the responsible AI practices that enterprise environments require.