AI Trends from Singapore and the World Reveal Keys to Success

Nine out of ten leaders know a strong data strategy is critical to AI success – so why are only a third of them integrating a unified data strategy across their company? In January 2024, LIKE.TG commissioned Forrester Consulting to find answers to these gaps and more in the rapidly developing AI landscape.

The research, conducted with 773 business leaders in 14 countries, including Singapore, sheds light on global business decision-makers’ mindsets around AI-powered CRM. These trends prove that regardless of fast shifts in AI, there are certain foundational principles that companies must prioritise for growth.

Before we explore these key success factors and recommendations, let’s understand the current state of AI-powered CRM in Singapore. Compared to the global average, business leaders in Singapore are generally more aware of the importance of data strategy and employee trust in AI but are less likely to have a formal data strategy or the data skills necessary for success.

Gaps in basic AI understanding reveal room for growth

The research reveals Singaporean organisations are embracing AI across various CRM use cases. But, it’s not all smooth sailing. The research uncovers critical gaps that could impact the success of AI adoption in CRM.

Here’s a striking revelation: Despite all respondents making plans to adopt AI, only half were able to choose the correct definition for both predictive and generative AI when presented with both side by side.

• Predictive AI: analyses existing data to make forecasts
• Generative AI: creates new content based on learned patterns

Considering that an AI strategy likely encompasses both types of AI models – which serve specific purposes and goals – this signals an opportunity for more comprehensive education. People need to know the specific use cases each type of AI enables, the anticipated business outcomes, and how to design a strategic plan for AI grounded in those goals.

Another key finding is the significant gap in data maturity and readiness. While 96% of Singaporean leaders emphasise the importance of a robust data strategy, only 30% claim to have one implemented across their business. Bridging this gap is crucial to using AI effectively.

Trust also emerges as a primary concern, with respondents citing security issues and scepticism about the output quality of generative AI. Fear of unintentionally exposing private customer data and potential damage to brand reputation looms large as barriers to purchasing generative AI.

Three foundations for strong AI-powered CRM

1. Ready your data

Data quality and availability is the crux of successful AI implementation. Over 62% of Singaporean survey respondents agree that improved data quality is essential – significantly higher than the 53% global average. Despite its importance, they indicated that their top challenges with their organisation’s CRM include data quality issues and a lack of data skills.

On the flip side, companies with a higher degree of data maturity are not only more likely to have adopted AI already but also are more likely to use a unified CRM across their business, thus realising greater front-office productivity and impact to customer satisfaction.

Our recommendations: Focus on cleaning your data, eliminating silos, and ensuring a holistic view of customer data. Take a balanced approach to data maturity aligned with your strategic goals. Knowing it’s not realistic to improve everything at once, work to understand the specific data requirements needed to deliver your AI use cases in a phased approach. Most importantly, keep data quality and availability front and centre as you build a strategy in tandem with AI.

Data readiness in action: Lotus’s, a prominent retail brand with over 2500 outlets across Thailand and Malaysia, underwent a technological infrastructure transformation with LIKE.TG. Prior to this overhaul, the company grappled with fragmented and monolithic systems that affected its ability to understand customer behaviours and deliver personalised experiences, Leveraging Data Cloud for Marketing, Lotus’s successfully unified data from diverse sources, reduced its customer record volume by half, and gained a complete view on its 9 million-strong customer base. With the integration of Marketing Cloud, the brand now adeptly crafts tailored customer experiences through automated journeys.

2. Build trust in AI

Building trust is a must in AI. Almost all Singaporean respondents (92%) said that trust is important – or even critical – when partnering with an AI vendor. Genuine concerns about unintentionally exposing private customer data, infringing copyright, or violating data regulatory compliance requirements raise a lot of questions. Specifically, organisations are seeking vendors who already have security protections – such as data masking (the practice of anonymising sensitive data) – baked into the tool. Another way to protect from potential risk is to choose a vendor that offers AI as part of their core CRM offering, so there are no extra hoops or complexities with trying to integrate an outside source.  

Our recommendations: Work with a trusted AI vendor that provides meticulous management of both AI inputs and outputs. Your data should be masked when shared with any large language models. When considering a vendor-hosted or external model, ensure that the context of inputs and prompts will not be stored and you never lose control over the use of your data. Beyond privacy and security concerns, prompts and outputs should be automatically scanned for harmful outputs. Finally, depending on the AI use case, consider keeping a human in the loop to ensure quality, accuracy, and trust.

Trusted AI in actionWith trusted AI and data, LIKE.TG is increasing customer trust and improving experiences for Indonesia-based end-to-end delivery service Lion Parcel. Service Cloud helps it understand customer behaviours and drive personalisation with customer segmentation, leading to a 73% reduction in resolution times. And with Einstein 1 making it easier for customers to self-serve, 90% of WhatsApp interactions are now handled by AI, leading to a 40% improvement in cost efficiency.

3. Make space for education and upskilling

As AI becomes embedded in organisations, 42% of Singaporean respondents agreed that continuous upskilling is necessary. This, paired with the general lack of understanding around AI concepts, highlights the opportunity for a thoughtful approach to AI education. Additionally, they noted that a lack of data skills is a primary challenge with the current use of their CRM systems.

Our recommendations: Beyond ensuring employees have a general understanding of your AI strategy and goals, start tactically with employee training to create and refine prompts. A prompt is a detailed instruction provided to a large language model to help it generate an output. A better prompt yields a better, more relevant output from the AI model. Every employee can be a prompt engineer – this training will maximise the potential benefit of AI while helping people work more efficiently. In addition, establishing corporate policies that educate employees to evaluate AI outputs for accuracy, bias, toxicity, and potential harm is essential.

Upskilling in action

Internal communication can be a barrier to the successful implementation of any new systems, so when Lion Parcel embarked on its digital transformation with LIKE.TG, it also made sure to optimise internal workflows and connect teams with Slack. Customer segmenting from Service Cloud also means agents can be trained to provide specialised service for critical interactions, with AI able to handle more routine contacts.

See how top leaders make the most of their AI investments by creating strong data practices, a culture of continuous learning, and unwavering trust. These insights and more can be found in the full study, so your team can create a foundation of excellence with your own AI-powered CRM.

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