Gartner Data & Analytics Summit 2026 Orlando: Day 2 Highlights

We are bringing you news and highlights from the Gartner Data & Analytics Summit, taking place this week in Orlando, Florida. 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 the necessity of unstructured data management for GenAI-ready data, the future of AI, and activating AI agents in analytics and BI platforms. Be sure to check this page throughout the day for updates.

• Gartner Identifies Three Pillars for Deriving Value from AI
• Gartner Announces Top Predictions for Data and Analytics in 2026

Presented by Nina Showell, Principal Analyst, Gartner

Almost every GenAI use case requires organizations to extract, qualify and govern significant volumes of unstructured data. In this session, Nina Showell, Principal 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 deliver GenAI-ready data.

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

• “From 2025 through 2029, the share of AI spending on AI data readiness will increase 7x, 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 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 the Gartner expert by contacting Meghan Moran at meghan.moran@gartner.com.

Presented by Erick Brethenoux, Distinguished VP Analyst, Chief of Research, Gartner

AI is moving faster than ever, with AI techniques that should bring adaptability to an uncertain world in constant flux. However, despite its extraordinary power and early promises, recent advances in AI have not been leveraged to its full potential. In this session, Erick Brethenoux, Distinguished VP Analyst, Chief of Research at Gartner, discussed what AI should do for us to deliver the value that we are expecting.

• “The fact that we only have a limited understanding about intelligence is also illustrated by the fact that many people, including renowned scientists and experts, have very different opinions about the reality of true artificial intelligence.”
• Future of AI Trend 1: AI on Steroids: “Scalable AI that benefits from massive compute power.”
• Future AI Trend 2: Composite & Neurosymbolic AI: “AI composed of multiple data-driven and knowledge-driven techniques.” 
• “As AI evolves, use it to enable ever more sophisticated business solutions, way beyond productivity improvement.”
• “Do not rely only on a single AI approach and keep an open mind for alternative and emerging AI approaches, beyond predictive, generative and agentic AI.”

Journalists can receive additional information, including all seven future AI trends, and/or request an interview with the Gartner expert by contacting Meghan Moran at meghan.moran@gartner.com.

Presented by Edgar Macari, Director Analyst, Gartner

Analytics and business intelligence (ABI) platforms are increasingly integrating AI agents to transform how data is analyzed and insights are delivered. In this session, Edgar Macari, Director Analyst at Gartner, discussed how data and analytics leaders need to proactively understand these shifts to maximize AI's business impact and ensure organizational readiness.

• “Agentic analytics becomes an overkill when it comes to: strict compliance and audit needs, low ROI use cases, as well as immature data and integration readiness.” 
• “D&A leaders can avoid the “black box” by prioritizing explainability for compliance, build trust with transparent insights, and ensure traceability with semantic layers.”
• “Avoid agent washing by adopting an evidence-based evaluation involving real-world scenarios, implementing task-driven acceptance, and engaging in detailed roadmap discussions.”
• Agentic AI is transformative, but success depends on disciplined evaluation and phased adoption:
  • Refine the enterprise AI strategy.
  • Identify where agentic analytics becomes an overkill.
  • Prioritize explicit transparency capabilities.
  • Prevent agent washing by adopting an evidence-based evaluation approach.

Journalists can receive additional information and/or request an interview with the Gartner expert by contacting Meghan Moran at meghan.moran@gartner.com.