Is your data strategy ready for gen AI? LOB leaders may disagree

Rapid advancements in artificial intelligence (AI), particularly generative AI are putting more pressure on analytics and IT leaders to get their houses in order when it comes to data strategy and data management.

Line-of-business leaders are feeling the need to move on generative AI now and are asking their technical counterparts to step on the gas: 77% of business leaders fear they are already missing out on the benefits of gen AI and that percentage climbs to 88% among marketing leaders, according to the Salesforce State of Data and Analytics report released on Thursday.

Salesforce’s findings gibe with IDC’s Worldwide C-Suite Survey 2023-2024, released in September. More than half of C-suite executives in IDC’s survey feel that gen AI is top-of-mind for new investment and 87% say they are at least exploring potential use cases.

IT leaders are also enthused about the technology. Foundry’s recently released AI Priorities Study 2023 found that 56% of IT decision-makers are eager to learn more about gen AI. They’re looking to apply the technology via chatbots and virtual assistants (56%), content generation (55%), industry-specific applications (48%), data augmentation (46%), and personalized recommendations (39%). Foundry is the publisher of

According to Salesforce’s survey, early adopters are already seeing results from gen AI efforts, including faster customer service resolution times and increased sales. But the enthusiasm must be tempered by the need to put data management and data governance in place. The Salesforce report found that 87% of technical leaders say that advances in AI make data management a higher priority and 92% say that trustworthy data is needed more than ever before. IT leaders say that the requirements for successful gen AI use include accurate, complete, and unified data (55%); enhanced security measures to avert new threats to the business (54%); and ethical use guidelines (30%).

“The concept of data management and having trusted data continues to be critical,” says Ryan Aytay, president and CEO of Salesforce subsidiary Tableau Software. “The majority of people we speak to say AI is moving their data management priorities ahead — it’s accelerating it. We also hear this scary stat that most people don’t feel like they’re getting enough value from their data today.”

Disconnect on data maturity

Analytics and IT leaders overall are confident in the data maturity of their organizations, according to Salesforce’s report. Considering factors such as data capabilities, processes, sponsorship, investment, and vision, 37% of those leaders say their organization’s data maturity is best-in-class, while another 57% say their data maturity is on par with the industry standard. Only 6% feel their data maturity is below industry standard or nonexistent.

Technical leaders were also the most confident in the accuracy of their data. Salesforce found 57% of data and analytics departments and 53% of IT departments were completely confident in data accuracy. Line-of-business departments that depend on that data were much more skeptical, with marketing (45%), sales (42%), and service (40%) leaders expressing less confidence in the accuracy of their organization’s data.

“Ultimately, is the data fresh? That’s more important,” Aytay says. “It’s less about right or wrong. A sales leader needs data in real-time. If the data is 24 to 48 hours old, it’s technically wrong because it’s not fresh.”

Still, 94% of technical leaders say they should be getting more value from their data and 78% say their organizations struggle to drive business priorities with data. Their top data priorities are improving data quality, strengthening security and compliance, building AI capabilities, improving company-wide data literacy, and modernizing tools and technologies. But while the goals may be straightforward, organizations are struggling to achieve them: People don’t need to be sold on the potential of AI, but they do need to be sold on short-term and long-term strategies for AI.

Stakeholder discontent

Essential to that success is a unified data strategy, which 59% of IT leaders say they don’t have — a top concern when it comes to implementing gen AI. Furthermore, 60% say gen AI won’t integrate into their current tech stack.

“If you go out and ask a chief data officer, a head of IT, ‘Is your data strategy aligned?’, well of course they might think it is,” Aytay says. “But is it really aligned to what the other stakeholders in the business need every single day? If I’m a sales leader, I need to know my pipeline. I need to know my forecast. I need to know how many reps I’ve hired. I need to know what my upcoming events are. But if that’s not tied to the IT team and they’re not thinking the way that I think, it’s very hard to actually have an aligned strategy.”

Salesforce found that 41% of line-of-business leaders feel their organization’s data strategy has little or no alignment with business objectives, while 37% of analytics and IT leaders feel the same way. The study suggests that a lack of shared KPIs may be a root cause of this issue. More than 60% of technical leaders admit they’re in the dark about business teams’ data utilization or speed to insight, and 68% don’t track the value of data monetization, making it difficult to effectively quantify the ROI of data initiatives at all.

Aytay notes the sales team might want to automate their outbound communications with customers, but using off-the-shelf gen AI could risk leaking proprietary company data into public large language models (LLMs).

“If they’re working with their IT and data office, they might do it in a more trusted way where you’re masking data and making sure it’s not getting disrupted and there aren’t any compliance issues,” Aytay says.

Indeed, both business and technical leaders rank security threats as the top challenge to achieving their data goals. As opportunities to integrate new data sources and leverage new technologies proliferate, so do vulnerabilities. As organizational data increases in volume and complexity, the threat surface also expands.

Foundry’s survey found that 45% of IT leaders feel that security and privacy are factors affecting the integration of generative AI with existing systems. IDC’s survey also found that more than 45% of respondents felt that security concerns are the biggest challenge associated with implementing gen AI initiatives.

The increased data volume and complexity also exacerbates the difficulty of data harmonization, making it difficult to extract value from data sources. More than two-thirds of technical leaders expect data volumes to increase 22% on average over the next year.

Salesforce says building data governance and data culture is key to effectively leveraging data. Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used, including the set of rules or policies by which information is collected, managed, stored, measured, and communicated.

Until organizations get a handle on these fundamental facets of their data strategies, the drive for capitalizing on the promise of generative AI may bring with it a greater likelihood of risks being realized and deeper rifts in perception on IT preparedness to make good on data-driven decision-making and data-related advancements.

Data Governance, Data Management, Generative AI