AI-Powered Market Positioning for Startups

Introduction

In the rapidly developing AI landscape, it is widely recognized that a strong data strategy is critical to the success of AI initiatives. However, despite this understanding, only a third of leaders are integrating a unified data strategy across their companies. To shed light on these gaps and more, Salesforce commissioned Forrester Consulting to conduct a research study with 773 business leaders in 14 countries.

The Current State of AI-Powered CRM

The research conducted by Forrester Consulting reveals that organizations worldwide are embracing AI across various CRM use cases. However, there are critical gaps that could impact the success of AI adoption in CRM. For instance, only half of the respondents were able to correctly define both predictive and generative AI when presented with both side by side.

Predictive AI analyzes existing data to make forecasts, while generative AI creates new content based on learned patterns. Given that an AI strategy likely encompasses both types of AI models, this highlights the need for more comprehensive education on the specific use cases and business outcomes associated with each type.

Another significant finding is the gap in data maturity and readiness. While 92% of leaders emphasize the importance of a robust data strategy, only 34% claim to have one implemented across their business. Bridging this gap is crucial for effectively using AI.

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

Three Foundations for Strong AI-Powered CRM

1. Ready your data

Data quality and availability are key to successful AI implementation. Over 50% of survey respondents agree that improved data quality is essential, but they also indicate challenges with data quality issues and a lack of data skills within their organizations. Companies with a higher degree of data maturity are more likely to have adopted AI and use a unified CRM, resulting in greater front-office productivity and 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. Work to understand the specific data requirements needed to deliver your AI use cases in a phased approach. Keep data quality and availability at the forefront as you build a strategy in tandem with AI.

2. Build trust in AI

Building trust is essential when implementing AI. Almost all respondents (96%) consider trust important when partnering with an AI vendor. Concerns about unintentionally exposing private customer data and violating data regulatory compliance requirements raise questions. Organizations seek vendors with security protections baked into their tools, such as data masking. Choosing a vendor that offers AI as part of their core CRM offering can also mitigate potential risks and complexities.

Our recommendations: Work with a trusted AI vendor that provides meticulous management of both AI inputs and outputs. Ensure your data is masked when shared with any large language models. When considering a vendor-hosted or external model, ensure you maintain control over the use of your data. Scan prompts and outputs for harmful content. Consider keeping a human in the loop for quality assurance.

3. Make space for education and upskilling

As AI becomes embedded in organizations, continuous upskilling is necessary. Nearly half of the survey respondents agreed on the importance of upskilling. However, there is a lack of understanding around AI concepts, and a lack of data skills is a primary challenge with current CRM systems.

Our recommendations: Provide employees with a general understanding of your AI strategy and goals. Start with employee training to create and refine prompts, which are detailed instructions provided to a large language model. This training will maximize the potential benefit of AI while helping employees work more efficiently. Establish corporate policies that educate employees to evaluate AI outputs for accuracy, bias, toxicity, and potential harm.

Conclusion

To position startups for success in the AI-powered market, it is essential to prioritize a strong data strategy, build trust in AI, and make space for education and upskilling. By focusing on these foundations, companies can effectively leverage AI in their CRM initiatives and drive growth. For more insights and recommendations, refer to the full study conducted by Salesforce and Forrester Consulting.