Dive Brief:
- Businesses are grappling with the consequences of poor data frameworks, according to a SoftServe report published last week. The company commissioned Wakefield Research to survey 750 business leaders.
- Around two-thirds of decision-makers said they believe no one within their organization understands the data collected or how to access it. Nearly 3 in 5 business leaders say key decisions are made based on inaccurate or inconsistent data.
- Nearly 75% of leaders blame poor prioritization and resource allocation for the disconnect, citing investments in generative AI at the expense of data and analytics initiatives.
Dive Insight:
No matter the industry, AI success relies heavily on the approach to data.
USAA turned its attention to deploying AI-based solutions last year after it spent three years cleaning up its massive data estate, Chief Data and Analytics Officer Ramnik Bajaj told CIO Dive. American Honda also underlined data’s role as an enabler of generative AI and core to the broader IT strategy last year during a CIO Dive virtual event.
Moving forward on initiatives without the right foundation can lead to wasted resources. Organizations admit to being stuck in the pilot phase as ROI lags and tools prove unreliable.
Data challenges often derail AI projects, according to a Lenovo report published earlier this month.
Businesses continue to push forward and ramp up AI-related efforts despite the rocky tech terrain. Around 9 in 10 leaders have expressed concern about generative AI pilots proceeding without addressing problems uncovered by previous initiatives, according to an Informatica report. Nearly 3 in 5 respondents said they face pressure to move projects along faster.
Strengthening data governance and processes is especially critical as businesses look to add AI agents to their tech stacks this year. CIOs know their business can’t reach AI ambitions without a solid data foundation, leading many technology leaders to prioritize data know-how in upskilling initiatives.
