Gartner Data & Analytics Summit 2026 London: Day 3 Highlights

We are bringing you news and highlights from the Gartner Data & Analytics Summit, taking place this week in London, U.K. Below is a collection of the key announcements and insights coming out of the conference. You can read the highlights from Day 2 here.

On Day 3 of the conference, we are exploring the data and analytics (D&A) mandate for 2030, discussing how to manage unstructured data for AI readiness, and discussing AI’s impact on headcount and business value. Be sure to check this page throughout the day for updates.

• Gartner Says Lack of Semantics Causes Inaccurate AI Agents and Wasted Spending

Presented by Rita Sallam, Distinguished VP Analyst, Chief of Research, Gartner

Data and analytics (D&A) leaders play a central role in their organization's AI success by providing the critical accelerants needed to realize value from AI. In this session, Rita Sallam, Distinguished VP Analyst, Chief of Research at Gartner, highlighted three shifts D&A leaders need to make to sustain AI value.

• “Chief data and analytics officers (CDAOs) and other D&A leaders play a critical role in AI success or risk failure.”

• “Through 2030, responding to this imperative will require shifts in how the D&A team organizes and works, builds and scales and creates value.”

• Shift #1: Create Value Compounding through Agentic Transformation

  • “Shift to becoming an AI‑first D&A organization. This starts with an explicit AI ambition — one that uses AI to transform, not simply optimize, business and operating models.”

• Shift #2: Treat Context as Critical Infrastructure

  • “Evolve your data foundation with context as critical infrastructure so AI agents operate with trusted situational awareness. D&A success is not about better models — it is about giving agents governed, contextual access to the right data.​”   

• Shift #3: Establish Trust as Catalyst of Value and Innovation​

  -  “Without trust in the data, outputs and decisions of AI models and agents, there is no value from AI.”

Journalists can receive additional information and/or request an interview with Rita Sallam by contacting Laurence Goasduff at laurence.goasduff@garner.com.

Presented by Jason Medd, Sr 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, Sr 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 Laurence Goasduff at laurence.goasduff@gartner.com.

Presented by Frances Karamouzis, Distinguished VP Analyst, Gartner

One hundred percent of executive leadership discussions involve AI strategy, value creation and headcount reductions for potential cost savings. In this session, Frances Karamouzis, Distinguished VP Analyst at Gartner, presented her views on AI’s impact on the workforce, business value and costs.

• High performing organizations are focusing on decoupling revenue from headcount. “AI is ushering in the era of business model arbitrage. We moved beyond labor arbitrage and resource inputs as the source of value creation. It's all about outcomes.”

• Headcount‑reduction‑led AI business cases have become irreconcilable. Less than 1% of layoffs is directly attributable to AI. “A focus on labor reduction for cost‑cutting or increasing productivity are not aligned with the realities of AI value creation. The focus should be on process redesign and business model shifts.”

• “Organizations are already in a talent‑debt situation. 2026 has begun with a mortgage on talent due to massive 2025 layoffs.” 

• “A paradigm shift from employee empowerment to process redesign and work integration is the key to successful value creation from AI initiatives.”

Journalists can receive additional information and/or request an interview with Frances Karamouzis by contacting Laurence Goasduff at laurence.goasduff@garner.com.