Gartner Data & Analytics Summit 2024 Orlando: Day 1 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 2 here and Day 3 here.

On Day 1 from the conference, we are highlighting the Gartner opening keynote presentation on generating value from AI readiness to collective intelligence, as well as sessions on the must-have skills for AI and D&A, and how GenAI is changing the way data is managed. Be sure to check this page throughout the day for updates.

• Gartner Predicts One-Third of Interactions with GenAI Services Will Use Action Models & Autonomous Agents for Task Completion by 2028

Presented by Debra Logan, Distinguished VP Analyst and Ehtisham Zaidi, VP Analyst, Gartner

Generative AI (GenAI) is an inflection point for data and analytics (D&A) and it is proliferating throughout organizations, which means the expectations for D&A leaders are higher than ever before. In this session, Gartner analysts Debra Logan and Ehtisham Zaidi discussed how rigorous execution of D&A fundamentals on business value can mature D&A leaders' core capabilities.

• “Modern digital technology has supercharged human collective intelligence to allow more information sharing, exchange of ideas and knowledge aggregation than ever before.” 

• “Organizations with mature D&A governance practices are 47% more likely to adopt innovations.” 

• “Allow and empower policies for AI - modify governance policies to make them more AI-friendly, and include AI considerations in the existing policies by aligning AI goals with the overall D&A governance strategy.” 

• “Rapid evolution of D&A and AI technologies (such as GenAI) offers leaders the opportunity to rethink and evolve their operating models.” 

• “More than 75% of organizations have evolved their D&A operating model to better support innovation in 2023. Sixty-six percent have had to reconsider their operating model due to disruptive technology.”

Presented by Jorgen Heizenberg, VP Analyst, Gartner

Being successful with data & analytics (D&A) is not so much about tools and technologies as it is about people. In this session, Gartner analyst Jorgen Heizenberg discussed the must-have roles for D&A teams, as well as how to build and develop the right skills and competencies.

• “All D&A roles are a combination of IT skills, like Python or SQL; data and analytics skills, like ETL or enterprise business intelligence; business or domain expertise, like marketing or supply chain; and soft skills, like communication or empathy.”

• “D&A roles should be defined by a 3-tier model.”

• “Global is about the entire enterprise. You will find leading roles there. Often in the central D&A team or center of excellence (CoE). A chief data officer falls under this tier.”

• “Regional is more decentralized or federated. For example, by function, process, geography or brand. Here you will find D&A roles that exist within these business areas.”

• “Finally, there are local roles. Within a specific department, project or community, people work with D&A, without being D&A people. For example, somebody in procurement that uses analytics to develop a quick overview of contractors.”

• “It’s key to rethink the definition of ‘qualified’ talent. Reduce or even eliminate arbitrary requirements around education, location or experience, to capture talent that might otherwise be screened out.”

Presented by Melody Chien, Sr Director Analyst, Gartner

Generative AI (GenAI) is revolutionizing data management, with innovation occurring at a rapid pace. In this session, Melody Chien, Sr Director Analyst at Gartner, discussed how GenAI is reshaping the landscape of data management.

• “Through 2026, GenAI will reduce manually intensive data management costs up to 20% each year while enabling four times as many new use cases.”

• “GenAI capabilities can simplify processes and speed up results, whether by augmenting the efforts of human workers, generating software code or optimizing chatbot performance.”

• “Identify potential use cases that are being slowed down by engineering bottlenecks and the lack of business involvement.”

• “Build data literacy and GenAI skills within your organization to safely use these emerging data management technologies.”

• “Partner with business stakeholders to evaluate and demonstrate the business value of GenAI by tracking improvement of data management to show tangible benefits.”