All Things AI: The Gartner Data & Analytics Summit 2024

All Things AI: The Gartner Data & Analytics Summit 2024

- by Philip Russom, Expert in Data Analytics & BI

I recently had the pleasure of attending my favorite conference of the year: The Gartner Data and Analytics Summit, which convened in Orlando, Florida on March 10-13, 2024. As usual, it was educational, fun, and social, plus I came away with many useful tips and actionable visions of where we’re going in our field of data and analytics (D&A). Please allow me to share what I learned, along with my general observations.

Artificial Intelligence (AI)

The 2023 summit strongly focused on data fabric, which in the Gartner view is the modern rallying point for unifying all data management technologies and best practices. However, many attendees scratched their heads and asked me something like this: “I can see why Gartner promotes the data fabric, but why does Gartner have so little to say about AI, at a time when the rest of the IT world is lit up by it?” Well, I’m not sure why that was the case in 2023. But I’d say that Gartner corrected that omission in spades by focusing the 2024 summit on all things AI.

And rightfully so, because AI – whether generative or not – has been one of the most debated and hyped topics of recent years in the D&A community, along with related topics in machine learning (ML) and large language models (LLMs). Hence, these high-profile topics were the subjects of most 2024 Gartner D&A Summit sessions, from the opening keynote (by Gartner analysts Debra Logan and Ehtisham Zaidi) to sessions on AI trends (Frances Karamouzis) and scaling AI (Arun Chandrasekaran).

Even the sessions that were not expressly about AI usually touched on how the rise of AI affects them (from the CDAO’s office and miscellaneous Ops methods to data ecosystems and metadata). Similarly, all sessions on data management tools and practices explained how these must contribute to traditional data goals (integration, quality, modeling, semantics, scale) while evolving to also support “AI-ready data.”

 Note that session speakers at the Gartner Data and Analytics Summit had a lot to say about so-called generative AI (or simply GenAI), which is the hottest topic in D&A today. However, sessions by Gartner analysts usually addressed all forms of AI, not just GenAI. (See Figure 1.)

FIGURE 1. Definitions of AI, from Joe Antelmi’s presentation What Everyone in D&A Needs to know About (Generative) AI: The Foundations (Source: Gartner Inc.)

The Gartner view, as I understand it, is that nascent GenAI will eventually complement and coexist with more established analytics practices, especially AI-driven predictive analytics, which already provides technical success and business value in many production systems. Likewise, non-AI analytics (reporting, dashboards, statistical analysis, self-service data prep, etc.) will also continue into the future, as long as they continue to deliver business value.

Chief Data & Analytics Officer (CDAO)

The CDAO is a management role that has recently evolved, as the responsibilities of the chief data officer (CDO) broadened to also encompass analytics. Gartner analysts saw this role coming, and a few years ago they created a Gartner advisory service specifically for it. The research and guidance of that service are represented in a CDAO track and several additional sessions in the main summit track:

  • So You Want to be (a great) CDAO, by Sally Parker, Sr Dir Analyst, Gartner
  • How CDAO Must Lead Data-Driven Change Management for Business Impact, by Sarah James, Sr Dir Analyst, Gartner
  • The CDAO Playbook for Generative AI, by Rita Sallam, Distinguished VP Analyst, Gartner

The focus was on how the CDAO must continue to evolve (and force the organization to evolve) to support more AI and other analytics. In fact, this is do or die for CDAOs, as stated in two Gartner Predicts statements made at the summit:

  • “By 2026, the CDAO’s ability to deliver data and AI literacy, culture change, and a skilled workforce will be a top-three determining factor in supporting business strategy.”
  • “By 2026, 75% of CDAOs who fail to make organization-wide influence and measurably impact their top priority will be assimilated into technology functions.”

With that in mind, here is a list of recommendations, as presented by Nate Novosel in his presentation CDAO Agenda 2024: Reinvent or Become Irrelevant:

  • Build your relationships, reputation and reach across the enterprise (and reconsider if your position allows you to do what you are being asked to do!)
  • Navigate complexity by showing business value — always. Showcase your successes as evidence for why your expanded responsibilities mandate more budget/resources.
  • Use AI as a direct line of sight to something that D&A Governance can hitch its wagon to. Start scaling your D&A operating model, potentially requiring an overhaul of current D&A capabilities.
  • For newer CDAOs, focus on delivering real solutions that align with key stakeholders’ agendas (and stop using culture as an excuse).

Data Ecosystems

Data Architectures (which Gartner analysts regularly call data ecosystems) involve a large-scale design that describes the many components of a data environment. This includes numerous datasets, data platforms, use cases, and interfaces, and tools (for data management and analytics), plus how these components integrate and interact in cloud, on-premises, and hybrid environments.

Data ecosystems and various cloud architectures for D&A were discussed by Gartner analysts in several sessions at the Gartner D&A Summit:

  • Data Ecosystems: Simplify the Delivery of Complex Data Management Infrastructure, by Adam Ronthal, VP Analyst
  • Ask the Expert: What Should CDAOs Know About Modern Data Architectures? by Robert Thanaraj, Dir Analyst
  • Ask the Expert: Everything You Wanted to Know About Cloud Data Management but Were Afraid to Ask, by Rick Greenwald, Sr Dir Analyst
  • Do You Know Where Your Data Is? How to Implement Multi-Cloud Data Governance, by Nina Showell, Principal Analyst
  • Data Lakes, Data Warehouses and Lakehouses: How to Choose, by Roxane Edjlali, Sr Dir Analyst

“Data Ecosystems are diving head-long into the Trough of Disillusionment on a Gartner Hype Cycle,” said Adam Ronthal, at the Gartner D&A Summit. (See Figure 2.) In other words, data ecosystems have survived their hype, and they are now on their way into mature practices and common use – if they survive the trough. The impact on user organizations is that a well-designed and curated cloud data architecture is now a critical success factor for fully modern and/or high-value D&A programs.

FIGURE 2. Data Ecosystems mapped on the Hype Cycle for D&A programs and practices. (Source: Gartner, Inc.)

For further reading on data architecture topics, see my 2023 paper Cloud Data Architecture Principles.

Data Fabric

The data fabric has become the leading-edge paradigm for data management development, deployment, and automation. Garter defines the data fabric as an architecture and set of best practices for unifying and governing multiple data management and data semantics disciplines, including data integration, quality, active metadata, master data, pipelines, catalogs, observability, data engineering, and more. The diverse tools and practices of a data fabric must interoperate deeply, in both development and production. Without data fabric, organizations struggle with data availability and access, data standards, governance, data engineer productivity, and time to use for analytics and other data products.

As stated by Gartner’s Thomas Oestreich, in his presentation 5 Things That Keep Data Management Leaders Up at Night: “Data fabric design is the future-proof architecture. Data ecosystems will lead to your future infrastructure.”

As I mentioned earlier, I feel that Data Fabric as a topic got short shrift in the 2024 summit, although it was the main theme in the 2023 summit. Even so, there were ample sessions by Gartner analysts on data fabric and related topics:

  • Data Mesh v/s Data Fabric? Evaluate the Benefits and Cautions Before Making Your Decisive 2024 Investment, by Ehtisham Zaidi and Robert Thanaraj
  • Roundtable: Data Mesh/Fabric Post Debate Followup, Mark Beyer
  • Ask The Expert: Everything You Wanted to Know About the Data Fabric But Were Afraid to Ask, Ehtisham Zaidi

Other Nails Hammered at the Gartner D&A Summit 2024

Metadata – Active and Otherwise. The important role of metadata was hammered into attendees’ psyches. In fact, in a LinkedIn post before the summit, Gartner analyst and Distinguished VP Mark Beyer said of the summit: “It’s almost a Metadata Summit!” – due to the numerous sessions by Gartner analysts that explore modern approaches to metadata. Furthermore, almost all summit sessions – regardless of the main topic – mentioned metadata as a critical success factor.

  • Money, Love, Power… and Metadata: 4 Things That Matter, by Adam Ronthal
  • Active Metadata — Magic, Myth, Miracle or Machine? by Mark Beyer
  • Ask the Expert: How Have You Started Getting Your Data AI Ready? Mark Beyer

DataOps and Data Engineering. I thought one of the better sessions of the summit was FinOps, DataOps, PlatformOps: Ops Excellence in Data Management, as presented by Robert Thanaraj. It laid out the principles of operational excellence for DataOps (observability, accountability, flexibility, and augmentation), and defined Gartner’s interpretation of PlatformOps (combine teams, technology and processes to enable continuous collaboration between platform providers and tenants).

Selecting Vendor Products. This is an area of guidance that has distinguished Gartner’s advice to clients for decades. Tips in this area were shared in several summit sessions, plus in sessions that discussed recent Gartner Magic Quadrants (by Melody Chien and Nina Showell):

  • How to (Not) Buy Software Like Everyone Else, Rick Greenwald, Sr Dir Analyst, Gartner
  • Roundtable: Which Database to Choose for Your Use Case, by Rick Greenwald

Data Observability and New Directions for Governance. One of the most enlightening presentations (in terms of demystifying new technologies and practices) was The State of Data Observability Technology — Detection, Recommendation and Prevention, by Melody Chien.


I feel that the best summary of Gartner’s high-priority recommendations – as made during the Gartner Data and Analytics Summit 2024 – was presented by Rita Sallam in her talk “Top Data and Analytics Predictions, 2024.” Let’s close this article with her actionable recommendations:

  1. CDAOs must become indispensable.
  2. Potential loss of intellectual property and copyright infringement will be a major risk.
  3. People will prove key to getting value from AI.
  4. Governance will be rebranded as strategic business.
  5. Enterprises must balance AI ambition with risk tolerance.
  6. Natural language will become the new composer.
  7. GenAI will emerge as both the problem and the solution for cost escalation.
  8. Natural language will free data access and use.
  9. Expect new user experiences beyond dashboards.
  10. Governance will continue to be key to AI value.