Salesforce Report Highlights Importance of Data in the AI Revolution
Data has long been vital to the success of business initiatives. However, with the meteoric rise of artificial intelligence (AI) data has become even more important. Salesforce, a leading cloud-based CRM platform, in collaboration with Tableau, released its inaugural State of Data and Analytic report.
One of the roadblocks in realizing the full potential of AI is to manage and leverage data for business needs. According to Salesforce Chief Data Officer Wendy Batchelder, “The AI revolution is actually a data revolution, and a company’s AI strategy is only as strong as its data strategy, with trust at its core.”
The Salesforce report was compiled by surveying over 11,000 information technology, analytics, and line-of-business leaders across 18 countries to discover how businesses are navigating the rapidly evolving AI landscape.
A Strong Data Foundation Fuels AI
Advances in AI are moving fast, and data management teams are feeling the pressure to supply algorithms and high-quality data. Almost 9 in 10 (87 percent) of IT and analytics leaders believe that the rise of AI makes data management a higher priority.
Over nine in 10 (91 percent) business leaders say generative AI would benefit their organization, however, they are concerned about their organization’s ability to capture generative AI value. Early adopters of generative AI are already seeing positive results such as improvement in customer satisfaction. It’s not surprising that the early success of some organizations has resulted in over three-quarters of business leaders (77 percent) fearing their company is missing out on generative AI’s benefits.
According to the report, a major roadblock to deriving maximum value for generative AI is the lack of a united data strategy that integrates generative AI into the existing tech stack. Eighty-six percent of respondents believed the AI outputs are only as good as the data inputs. There are also some ethical concerns about the use of AI and uncertainty about generative AI bias that can potentially lead to inaccurate results.
The report highlights the importance of data maturity as a sign of AI preparedness. Organizations that have higher data maturity have a more positive assessment of their organization’s data quality, technology infrastructure, and AI strategy.
Data’s Full Potential Remains Elusive
While business leaders realize that data is the key to getting AI benefits, there is significant misalignment between data strategy and business goals. According to the report, many line-of-business leaders (41 percent) believe that their data strategy has either partial or no alignment with business objectives. Similarly, 37 percent of analytics and IT leaders also see room for improvement.
The core reasons for this disconnect include the lack of shared KPIs across teams, dealing with overwhelming volumes of data, and security threats. Technical and line-of-business leaders are concerned that integrating new data sources could increase security vulnerabilities.
The lack of data visibility could be a reason why business leaders are concerned about security threats. Nearly half (45 percent) of analytics and IT leaders say that they have partial or no visibility on how data is used within their organization.
The teams closest to data, including the analytics and IT teams, have the highest confidence (57 percent) in data quality. This shows an opportunity to instill data confidence across other teams including marketing, sales, and service teams.
Building confidence in data accuracy is more than just a technical fix – it requires a shift in mindset. There needs to be a collective change in behaviors and beliefs about the importance of data. The good news is that analytics and IT leaders are taking action. Nearly eight in ten analytics and IT leaders plan to increase the budget for data training and development.
The findings of the report show that data governance can play a key role in buying data trustworthiness with 85 percent of analytics and IT leaders using data governance to quantify and improve data quality.
“Managing data is the most important action a business can take to successfully implement generative AI,” said Batchelder. “To effectively manage data, leaders must use data governance strategically and invest in a strong culture now more than ever.”
The report indicates that analytics and IT leaders lean on cloud solutions to mitigate data gravity, which refers to the concept that data has mass as the mass grows larger it pulls additional resources making it more challenging and expensive to manage that data.
Analytics and IT leaders are relying on better infrastructure (44 percent), using multiple cloud providers (41 percent), and employing decentralized or distributed data storage solutions (40 percent) to mitigate the threats of data gravity.
Looking ahead, companies need to overcome several hurdles to unlock the full potential of AI. The Salesforce report indicates that business leaders are aware of the key challenges and understand what tools can help them succeed in leveraging the power of AI technology.