How IT leaders can use generative AI to bridge the data divide

~~~Jacob’s Column——Focus on the research on the business model of the first brand in the industry~~~

Rewritten content is as follows: Source: Lisa Ginther Huh

Generative AI has become a common topic in IT leadership and CIO discussions recently. This is also discussed extensively at the Gartner IT Symposium, but this path forward can be confusing. While 86% of IT leaders believe that generative AI will soon play an important role in their organizations, recent research shows that 33% of business leaders report being unable to derive insights from data. Yet three-quarters of business leaders are already worried about missing out on the benefits of generative AI

To successfully use generative AI tools, employees need a solid understanding of data, but across organizations, employees report not knowing how to safely use generative AI at work, including 49% of sales professionals personnel.

So, how can IT leaders bridge this gap? The answer is to use generative artificial intelligence.

Give employees managed, AI-driven insights into their workflow

Generative AI can help business users who need to quickly and easily get the most from their data, delivering intelligence directly in the applications where employees work, such as email, mobile, or apps like Slack and Salesforce. Streamline and democratize data analysis with personalized, contextual insights.

Proactively deliver your team’s most important drivers, trends, forecasts, and outliers and provide employees with customized summaries of the metrics that matter to them, while leveraging natural language processing capabilities for conversational, contextual data queries. With a professional visual analytics platform that helps provide new guided questions or prompts, you can filter results, drill down for more information, or explore possible actions with just one click. All details can be shared with colleagues in collaboration apps like Slack or Teams to speed up informed business decisions

For example, marketers can measure the effectiveness of marketing campaigns and track engagement for new products, while sales leaders can quickly identify upsell and cross-sell opportunities, and service teams will be able to monitor customer loyalty and identify areas for improvement. .

These cases demonstrate how generative AI capabilities can be leveraged to support businesses. When considering deployment, keep in mind that 63% of salespeople want their employers to provide them with opportunities to learn how to use generative AI. Training is another integral element of developing a strong data culture. Everything must be built on trust, including trust in data, tools and processes. At this critical time, it is smart to use artificial intelligence to drive business success. Act of

Use trusted artificial intelligence with platform-agnostic integration

When introducing generative AI, prompts should be built on a foundation of proprietary customer data. When sharing this data with large language models (LLMs), you need to ensure data security and support role-based access to organizational data. Using a zero-retention architecture like the one in the Einstein Trust Layer, data can be masked, meaning that when tips are shared with LLM, none of the data is stored outside of Salesforce (this feature is coming soon). Zero-copy data sharing quickly and securely virtualizes information in other databases without having to move or copy it, so it is available immediately. With the professional visualization data cloud, you can use end-to-end encryption to unify data across public clouds and Salesforce, and call in compliant, trusted data from Snowflake, Google BigQuery, Amazon Redshift, Microsoft Azure, etc.

For example: When you use a visualization platform or the Salesforce Einstein trust layer for data analysis, you can use the Einstein Copilot auxiliary tool corresponding to the analysis platform to enhance the security of natural language queries. This conversational AI assistant is built into every Salesforce app out of the box to help your team be more productive. Copilot features an easy-to-use natural language interface that gives your team the space to ask questions and get relevant, trusted answers based on your company's proprietary data. Einstein can act as a colleague during brainstorming sessions, helping people quickly explore data in easy-to-understand terms and then create visualizations.

Build AI and data fluency to make the most of your investment

Cloud computing and artificial intelligence solutions can provide a 360-degree view of the customer so each department knows the next best action to take to achieve better business results. With the right tools in place, businesses can make data insights accessible to everyone, regardless of their data background

Operating procedures:

• For accurate analysis, a complete, clean and up-to-date foundation of trusted data should be established.
• To provide a single source of truth that employees and AI-generated technologies can leverage, this data should be made centrally available.

• To put powerful analytics at the fingertips of every employee, deploy user-friendly tools that provide natural language queries.

Help employees gain business insights using consistent data, such as a complete record of customers, products and team interactions. By calling multiple systems and data lake services, you can easily coordinate these data sources so that employees can query them from a single dashboard. With all data mapped into a shared data model, teams can easily manage data, eliminating duplicate records or conflicting rules

By integrating data and functionality, your sales, marketing, and service teams can make informed decisions based on a single view of your customers, rather than dealing with large amounts of siled information. Marketers can leverage a comprehensive customer view to uncover untapped needs to create magical connections with 500 million fans around the world, bringing the excitement of the track to fans in creative new ways. Service representatives can provide better support with a single view into a customer's recent call history, including technical issues and product purchases. Unified data coupled with workflow automation can help your service reps gain insights to offer relevant discounts at the right time to help retain dissatisfied customers

For businesses that close the data gap by investing in improving employee data fluency and exploring generative AI analytics tools, the rewards are substantial. By building a foundation of trust in your data, tools, and processes, and using natural language processing for queries, you can provide a 360-degree view of your customers, and you can empower everyone in your organization to make data-driven business decisions.

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