Research: Singaporean enterprises need to rethink their AI strategy

Since 2019, the Singapore government has urged enterprises to “be at the forefront, setting the pace, and driving global innovation and conversations” in AI. The latest ServiceNow Enterprise AI Maturity Index suggests that most enterprises around the world, including those in Singapore, are struggling to keep pace with the speed of AI advancement.

On average, Singaporean enterprises are spending 11.5% of their technology budget on AI, down from 15.5% last year, according to our research. On the other hand, 84% of Singapore respondents say they plan to increase their AI investment next year, in line with the average for all countries in our study.

Only 7% of Singapore enterprises say they’re using AI to innovate or reimagine their business at scale, while 29% report zero return on their AI investments in the past year. For Singapore to firmly establish itself at the forefront of AI innovation and development, business leaders need to rethink their AI strategy.

Fix fragmentation first

Singaporean enterprise leaders are most likely to identify a lack of data security (21%), AI governance (15%), and clear metrics (15%) as their biggest barriers to realizing value from AI. These three hindrances are amplified by one common factor: enterprise silos and their fragmented systems, processes, and goals.

More than half (56%) of survey respondents haven’t made significant progress on connecting their data and operational silos for AI applications. Only 29% strongly agree their departments have aligned on a clearly defined AI strategy.

Unless Singaporean businesses break out of their silos, the race to adopt AI will create more problems than solutions. Already, 72% of Singaporean enterprises are building and deploying AI from multiple internal task forces across the organization.

This may seem like a good way to accelerate AI adoption, but it also traps any successful innovation and implementation within existing silos. That leaves teams competing for resources and duplicating efforts rather than collaborating on common priorities for the entire business.

Singaporean enterprises cannot expect to be at the forefront of AI if they continue hitting the accelerator without disengaging the brakes. They need to integrate their data, systems, processes, and people in ways that can withstand the current and future pace of AI change.

Connect departments

The integration process should begin with a clear, shared vision for AI, including defining specific goals and metrics for measuring holistic progress across the organization. This will require leaders to gain buy-in from all departments as a first step toward eliminating departmental silos.

Next, leaders will need to make the enterprise’s fragmented data, systems, and processes work together as a unified whole. That involves unraveling years, if not decades, of legacy complexity while keeping operations running smoothly for customers and employees.

Historically, this lift-shift-and-fix model has meant ripping out legacy technology and replacing it with all-new systems—the equivalent of open-heart surgery that can leave enterprises laden with technical debt and long-term underperformance, if not permanently crippled. It’s no wonder many Singaporean enterprises have left their silos alone: The risks and costs of such surgery are great.

There is another way: Use an AI platform such as the ServiceNow AI Platform to connect all data and systems on a single enterprisewide fabric, with governance and security built in. This can both minimize disruption to the enterprise and connect fragmented systems, enabling them to access data across the organization and deliver the value they were meant to.

Reinvent work

With a defined vision and a common platform, Singaporean enterprises can start using AI to reinvent work—without creating new silos and governance risks. This is crucial to realizing the full value of AI with a bimodal strategy that explores entirely new revenue generation models and makes existing work more efficient.

According to our research, enterprises that adopt new collaborative workflows across business functions for AI are more likely to experience significant revenue growth, improved customer and employee experiences, and increased productivity than those that simply enhance existing workflows with AI.

Enterprises that limit AI to existing workflows risk automating inefficiency and embedding fragmentation deeper into their operations. Those that reimagine workflows from the ground up can find it easier to streamline operations and create more profitable business models with AI while baking in proper governance from the start.

Gain more insights in our global Enterprise AI Maturity Index report.