While many ASEAN organizations believe that AI capabilities are especially important to their business, few have a solid organization-wide data strategy to support effective AI adoption.
Businesses have much to navigate when it comes to implementing AI today.
Having good data is a critical foundation for this. Yet many are still struggling to unlock the potential of their trapped and disconnected data — only 34% of respondents in a Forrester study said their organization has a formal data strategy integrated across the business.
To find out how organizations in ASEAN can effectively operationalize AI for productivity and customer experience, DigiconAsia posed some questions to Gavin Barfield, Vice President & Chief Technology Officer, Solutions, Salesforce ASEAN.
According to a Forrester report, 89% of global business leaders said AI strategy and capabilities are especially important when partnering with a CRM vendor. Where and how does AI-powered CRM help a business?
Gavin Barfield (GB): AI-powered CRM software can deliver significant value to businesses. It drives cost savings and grows the bottom line by enhancing operational efficiency and creating higher-value customer relationships.
For employees, AI-powered CRM boosts productivity and efficiency by automating repetitive tasks, predicting customer behaviors, and personalizing customer experiences at scale.
Take Salesforce Einstein Copilot, for example, which acts as an integrated assistant in the flow of work, providing users with accurate, trusted, and data-driven insights and responses without the need to toggle between systems. As a result, employees can resolve customer cases more efficiently, improving customer satisfaction and building lasting relationships that ultimately drive higher margins.
Further, when grounded in the right company and customer data, AI enables businesses to deliver hyper-personalized customer experiences. Beyond issue resolution, customer service cases have the potential to open the door for sales and marketing opportunities, like account expansion and upselling.
A strong data foundation is a prerequisite for successful adoption of AI. What is considered a strong data foundation?
GB: A strong data foundation consists of connected applications and secure data for AI to deliver relevant and contextual predictions and recommendations.
Yet, a recent Forrester report reveals that only 34% of businesses globally have a formal data strategy integrated across the business. Salesforce research shows that, for most businesses, 71% of their data sits in disconnected applications, resulting in trapped islands of data that provides little value.
Solutions such as Salesforce Data Cloud help businesses harmonize and unlock their trapped data – including structured data within their CRM and unstructured data such as Slack conversations, emails and audio files – into a unified view. This builds a foundation of trusted company data, which AI prompts can be grounded in to ensure useful and trusted outputs.
As voluminous data and AI come into play within an organization, building trust has become even more critical. What constitutes a trusted infrastructure and workflow for data management, data security, and AI-powered customer experience?
GB: Salesforce research shows that accurate, secure data and ensuring that humans are at the helm of AI will build trust and drive AI adoption within organizations.
To do this, businesses must start with a strong data foundation that provides a trusted and unified view of customers. This foundation also needs to be protected with enterprise-level privacy and security, ensuring data governance and security with features such as zero-data retention, data masking, and dynamic grounding.
The above combination creates an ecosystem where AI can be connected across all parts of the business, generating outputs that are secure, accurate, and personalized across different functions in the organization.
As AI becomes more sophisticated, we need more powerful, system-wide controls that put people in the driver’s seat of AI. We need to ensure people can focus on the highest-risk and highest-judgment outcomes. They need a bird’s-eye view of their AI systems, allowing them to spot and address larger issues. Trust across the enterprise is only possible with the right data and controls.
What are some examples of good AI strategies among ASEAN businesses that you’ve encountered?
GB: ASEAN businesses with great AI strategies all have one thing in common – a strong data foundation. Great data makes great AI. Having the right, unified data is critical to ensuring AI-generated outputs are useful and meaningful for businesses to act on.
Good AI strategies are also use-case-driven rather than technology-driven. Instead of blindly adopting the latest technologies, businesses must focus on bridging the AI value gap. This means taking a structured, progressive approach where AI can bring the most value or impact to the business.
ASEAN businesses that are still in the early stages of AI implementation, for example, can derive significant benefits and future value from first investing in predictive AI capabilities. They could then look at implementing generative AI in simple but high-value use cases, such as generating account and case summaries or sales follow-ups.
For this purpose, they could use out-of-the-box generative AI features before creating customized, embedded generative AI to tackle specific business needs. Further value could then be driven through conversational AI assistants embedded in the workflow.
