3 Tips to Prepare Your Data for the AI Era

The world of data and artificial intelligence (AI) is constantly evolving, making it challenging for organizations to keep up, or even get started. With the rapid growth and advancement of generative AI, it has become crucial for companies to skill up their teams with AI expertise. But, having a skilled team is only part of the equation; it’s also about having the right data in place to use it efficiently. In fact, 94% of business leaders believe their organizations should be getting more value from its data. Good AI needs good data. So, where do you start?

1. Architect your technology for data and AI readiness

A well-architected technology solution is an essential step to successfully adopt AI. It sets the foundation for a platform that can handle large volumes of data, workflows, and users without compromising performance. Organizations that don’t prioritize building a solid foundation may face a variety of challenges that can affect their competitive edge. These can include difficulties in adopting new tools, a decline in customer retention, and increased costs due to technical debt. A well-architected solution should be: 

• Trusted: Protects your business and stakeholders
• Easy: Delivers value fast
• Adaptable: Evolves with your business

Strong solutions allow for scalability, flexibility, and security. They also ensure the quality and reliability of data and processes. This leads to time and resource savings, as well as reliable and accurate reporting. By adhering to best practices and minimizing customization, you can set the stage for long-term potential. 

Before you can begin the architectural process, it’s important to have a clear understanding of your desired outcomes. Align with your organization’s leaders about what you’re hoping to achieve with technologies, such as Data Cloud or the Einstein 1 Platform. You’ll need to also assess your technology stack, identify any obstacles, and collaborate with industry experts and architects to develop a detailed implementation plan.

2. Unlock your data to get the full picture

Your AI use cases are only as good as the data they’re based on. Connected and clean data is critical to developing effective AI algorithms. 

Without access to connected data, AI algorithms will struggle to identify patterns and provide accurate recommendations. For example, if an AI system is only provided with data from one source, it may not be able to detect correlations or patterns that exist in other datasets. This can result in biased or inaccurate predictions. But, when data is connected and integrated, AI algorithms can learn from a wider range of data and make connections and predictions from different sources of information. 

Unlocking data that’s siloed in different databases gives you a better understanding of your business, customers, and market trends. This includes organized data like CRM and transactional data, as well as unstructured data like documents, emails, and social media. By unlocking your data, you’ll be able to:

• Make informed, data-driven decisions
• Improve processes and efficiencies
• Drive innovation and collaboration

Yet, it’s not enough to simply have access to data. It’s equally important to foster a data culture within your organization. This means having skilled teams to access and understand data, as well as the ability to interpret and use it to make informed decisions. Trailhead is a great place to start learning about data. From there, your team can expand their knowledge and validate skills with instructor-led training and certifications.

3. Think big, start small

With AI, the possibilities of knowledge and efficiency are endless. But, achieving the results you want requires a well-defined strategy. This means focusing on achievable use cases that can deliver immediate results.

This method allows you to gradually implement AI and show its value through quick wins, which will help you secure leadership support for larger investments. Some of the ways organizations are achieving these types of results with AI include:

• Sales representatives using AI to write cold emails to potential customers
• Customer service representatives getting suggestions on the next steps to take when resolving a case
• Marketers using AI to deliver personalized experiences to their audiences

As your teams gain experience, you will incorporate more complex use cases. Over time, this organic growth will result in a comprehensive and effective AI strategy that can generate significant value for your organization. 

By starting small and growing steadily, you can benefit from AI while minimizing risks and ensuring sustainable success. And as you achieve success, be sure to define and build a system to measure your progress. Without a clear understanding of metrics and tracking methods, it can be difficult to measure the effectiveness of your AI efforts, identify areas for improvement, and make informed decisions.

Tap into our resources

We know that approaching AI can feel overwhelming — building a scalable solution, managing data, and training your teams. That’s where the Signature Success Plan comes in. With Signature, you get the deepest level of partnership and fastest access to expertise to help make the most of your business investments. 

With a designated Signature Expert who has deep knowledge of your business, you get advocacy and strategic guidance, along with insights on using CRM + AI + Data + Trust. Our experts also offer ongoing Architecture Guidance, Technical Health Reviews, and use industry best practices to help you envision and build the most effective solution to achieve your goals.

And when it comes to measuring success, Signature customers can look to their personalized Customer Success Score. Built on Data Cloud, the Score helps customers understand how they’re performing with Salesforce and provides personalized, actionable insights to help them get the most out of their investment.