Turning Gen AI into Business Success
Interest in AI is widespread, but turning that interest into results depends on execution and a focus on real business problems.
For many businesses, the conversation around generative artificial intelligence (Gen AI) has moved quickly from curiosity to action. According to our DBS Business Pulse Check Survey, about 67% of companies polled said that they are already applying some form of AI in their work processes. However adoption remains uneven across industries, with only 12% having fully integrated AI across their operations, indicating significant headroom for broader and deeper deployment.
The challenge now is whether businesses are able to turn experimentation with AI into tangible business impact. Many firms are still using isolated tools or informal pilots that deliver limited results. Businesses that are making progress tend to approach adoption differently. They start with a clearly defined business problem, focus on use cases that can deliver immediate value, and build confidence by starting small before scaling further.
Acting early also matters, as the gap between companies that move and those that hesitate continues to widen, with early adopters building advantages that become harder to close over time.
Taking the first step
Many businesses still lack clear direction on how to apply Gen AI meaningfully. While adoption is rising, only a small group of firms are seeing tangible gains, largely because they are able to translate ideas into execution.
Businesses that make progress tend to focus their efforts on specific challenges, whether in reducing manual work, improving customer engagement or managing operations more efficiently. This creates a clearer path to value and makes it easier to bring teams along.
Rather than viewing AI as a standalone initiative, businesses are starting to treat it as a practical tool that supports day to day operations and decision making.
Build momentum through real use cases
On the ground, the most effective applications of AI are often straightforward and closely tied to business needs. These early use cases may not be complex, but they deliver visible results and help build momentum.
One logistics company, for example, used Gen AI to process customer emails requesting transport quotations. The solution automatically extracted key information, flagged missing details and generated draft responses, reducing response times from hours to minutes while helping the business manage higher customer volumes without increasing headcount.
In another example, a financial services company adopted AI agents to speed up customer risk reviews. By analysing documents, reviewing past cases and highlighting potential risks, the solution reduced screening times from months to minutes while improving consistency and turnaround time.
Overcoming barriers to adoption
Even with clear use cases, many businesses face challenges in moving forward, particularly smaller firms with limited resources and in-house expertise. Our DBS Business Pulse Check Survey found that close to two in five businesses need expert guidance on how to start, accelerate or scale their use of AI. In particular, businesses need structured guidance, practical tools and support across different stages of their journey.
DBS Spark GenAI Programme aims to address these needs through a structured three-stage approach.
Start: Businesses that are beginning their AI journey can start with ready-to-deploy tools that address immediate operational needs.
Accelerate: Firms ready to move into more targeted use cases can access consultancy and more customised solutions.
Scale: Companies seeking deeper integration across operations can tap on support such as upskilling, tailored consultancy and backend system integration.
Complementing the programme is the “Implementing AI for Impact” playbook, which offers clear steps to assess readiness, identify relevant use cases and map out pathways for adoption.
Start small, then scale
A common thread among businesses that are seeing results is the importance of taking a step-by-step approach, starting with small, targeted use cases before expanding further. Attempting large scale transformation too early can stretch resources and slow progress, while smaller initiatives allow businesses to test ideas, learn quickly and build confidence.
Starting with a single use case also enables teams to see tangible benefits, whether in time savings, improved workflows or better customer engagement. These early wins create momentum and make it easier to expand adoption across the organisation.
Ultimately, the path forward is less about the technology itself and more about how it is applied. Businesses that focus on clear problems and build momentum through practical use cases are already seeing results. Those that delay risk falling further behind as the gap continues to widen.
