Organisations that achieve positive AI outcomes invest up to four times more in data quality, governance, and workforce preparation than those with poor AI results, according to new research from Gartner.

The finding is based on a global survey of 353 data, analytics, and AI leaders.

Despite higher spending by top performers, the survey found broader confidence remains low. Only 39 per cent of technology leaders said they were confident their current AI investments would have a positive impact on financial performance.

"D&A leaders play a central role in achieving their organisation's AI value ambition," said Gartner analyst Rita Sallam. "Through 2030, the D&A leader's mandate is to deliver foundational areas, including new trusted data, context foundations and perceptive intelligence."

Gartner has outlined six shifts it says data and analytics (D&A) leaders must make to realise that mandate.

The first is moving to an "AI-first" operating model - using AI to transform business and operating models rather than making incremental improvements.

The second involves restructuring D&A teams around what Gartner calls "decision pods." These are smaller, cross-skilled groups augmented by AI agents and focused on business outcomes. Sallam said some organisations are experimenting with teams of as few as two people.

The third shift concerns data context. Gartner found organisations with the highest maturity of AI-ready D&A capabilities are achieving up to 65 per cent greater business outcomes.

"D&A success in 2030 is not about better models - it is about giving agents governed, contextual access to the right data," Sallam said. Context, including semantics and metadata, is now mission-critical, according to Gartner.

The fourth shift requires organisations to move beyond proof-of-concept projects and build integrated engineering practices across data, AI, software, and context engineering.

Trust and governance form the fifth shift. A separate Gartner survey of 360 IT leaders in the second quarter of 2025 found only 23 per cent were very confident in their organisation's ability to manage security and governance when deploying generative AI tools.

"Traditional control should be overhauled to prioritise trust-based governance models for AI agents," Sallam said. "Without trust in the data, outputs and decisions of AI models and agents, there is no value from AI."

The sixth shift is moving from measuring return on investment toward what Gartner calls a "value flywheel" - reinvesting efficiency gains back into growth and innovation.

Gartner analysts will be providing additional insights on AI and D&A trends at the Gartner Data & Analytics Summit 2026 in Sydney, June 16-17, 2026.