Gartner Data & Analytics Summit 2026 Sydney: Day 2 Highlights

We are bringing you news and highlights from the Gartner Data & Analytics Summit 2026, taking place this week in Sydney, Australia. Below is a collection of the key announcements and insights coming out of the conference. You can read the highlights from Day 1 here.

On Day 2 from the conference, we are highlighting sessions on government AI adoption; unstructured data management; and how organizations can get ready for data & analytics in 2030.

• Gartner Identifies the Top Trends for Data and Analytics

Presented by Dean Lacheca, VP Analyst, Gartner

As governments accelerate efforts to responsibly adopt AI in pursuit of operational efficiency and enhanced public service delivery, recurring challenges and systemic barriers persist. In this session, Dean Lacheca, VP Analyst at Gartner, outlined the key strategic pillars and best practices for successful AI adoption in the public sector.

• “AI adoption expectations within government don’t reflect reality, with more than 50% of AI projects not making it into production.” 

• “Limited value from AI is not a technical problem, but a lack of strategic clarity and decisive leadership. Organizations need every AI project to clearly define its value and focus on converting AI opportunity into measurable business impact.”

• “To find new value, AI needs to be ready technically. This means having an AI strategy set the pace, anticipate hidden costs and select vendors based on required capabilities.”

• “To capture and sustain value, organizations and workforces need to be ready. This requires transforming talent through hiring restraints, talent and value remixing, and developing critical skills like context engineering.”

• “Government organizations must build the flexibility to rapidly adopt new AI capabilities while maintaining a stable workforce, governance and risk posture.”

• “With momentum building behind AI agents and multiagent solutions, Australian governments cannot afford to ignore these emerging implementations of AI.”

Presented by Jason Medd, Senior Director Analyst, Gartner

Almost every GenAI use case requires organizations to extract, qualify and govern significant volumes of unstructured data. In this session, Jason Medd, Senior Director Analyst at Gartner, discussed how data management leaders should deliver workflows that orchestrate entity extraction, vector data embeddings and semantic data enrichment with structured data pipelines to enable GenAI-ready data. 

• “By 2027, the IT spending focused on multistructured data management will account for 40% of the total spent on data management technologies and services.”

• “From 2025 through 2029, the share of AI spending on AI data readiness will increase seven times, driven by the essential need for AI-ready data.”

• “Through 2028, heads of AI, data science and data management will attempt to build their own unstructured metadata solutions, incurring costs more than 300% higher than they would if they used existing document and records solutions, skills and practices.”

• “Data management leaders who are unable to feed multimodel data-hungry AI models will fall behind on executing their AI strategies.”

• “Continuously assess whether the data strategy is aligned with the AI strategy. Look for opportunities to merge the data management practices for structured & unstructured data.”

Journalists can receive additional information and/or request an interview with Jason Medd by contacting Emma Keen at emma.keen@gartner.com.