Conference Updates

Orlando, Fla., March 22, 2023

Gartner Data & Analytics Summit 2023 Orlando: Day 3 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 and Day 2 here.

On Day 3 from the conference, we are highlighting D&A predictions, how to address AI risks and how to articulate the value of a D&A initiative. Be sure to check this page throughout the day for updates.

Key Announcements

Top Data and Analytics Predictions, 2023

Presented by Rita Sallam, Distinguished VP Analyst, Gartner

Gartner has identified top predictions for data and analytics that provide a forward-looking perspective on how markets, skills and organizations will evolve. In this session, Rita Sallam, Distinguished VP Analyst at Gartner, shared how to leverage these predictions to build a data and analytics strategy to return to growth, drive innovation and create value from uncertainty.

Key Takeaways

  • By 2026, 5% of workers will routinely use AI against their employer’s wishes to complete tasks. “The future of all work will be transformed by AI.” 

  • By 2026, 20% of top data science teams will have rebranded as cognitive science or science consultancies, increasing diversity in staff skills by 800%. “Data science will change given its pervasiveness, and it will encompass more disciplines.”

  • By 2026, 50% of business intelligence tools will activate their user’s metadata, offering insights and data stories with recommended contextualized journeys and actions. “D&A teams must move from dashboards to stories, using metadata to personalize the user experience.” 

  • By 2027, 80% of enterprise marketers will establish a dedicated content authenticity function to combat misinformation and fake material. “AI technology is progressing much faster than people or organizations are able to absorb its implications and capabilities. Responsible AI must be a priority.”

  • By 2026, more than a quarter of Fortune 500 CDAOs will have become responsible for at least one data and analytics-based product that becomes a top earner. “CDAOs can make a positive impact on the performance of the organization and strengthen their own position by joining the Chief Digital Officer in driving digital product revenue growth.”

  • By 2026, environmental sustainability will be a key criterion in over 60% of data management initiatives, supported by financial governance practices. “Within the scope of a cloud ecosystem, environmental sustainability initiatives have a direct link to cost management outcomes.”

What You Need to Do About New AI Risks

Presented by Sumit Agarwal, Sr Director Analyst, Gartner

AI solutions are the top emerging technology to be deployed, or close to deployment, across enterprises. In this session Sumit Agarwal, Sr Director Analyst at Gartner, discussed where, when and how AI can be compromised and what data and analytics leaders need to do about new AI risks.

Key Takeaways

  • “Regulatory compliance is the primary reason why privacy, security and/or risk are barriers to AI implementation.” 

  • “Breaches and hacks against AI are plentiful and are rendered in many variations. Organizations must take compromises by insiders as well as outsiders seriously.”

  • “Collective organizational management of AI privacy, security and risk results in improved AI business outcomes.”

  • “When it comes to tackling new AI risks, data and analytics leaders need to get organized and set up their priorities for AI trust, risk and security management (AI TRiSM).” 

  • The top 5 priorities for AI TRiSM are:

    1. AI Inventory: Capture the extent of exposure by inventorying AI used in the organization and ensure the right level of explainability. 

    2. AI Risk Awareness: Drive staff awareness across the organization by leading a formal AI risk education campaign.

    3. Privacy and Data Protection: Eliminate exposures of internal and shared AI data by adopting data protection and privacy programs.

    4. Robust ModelOps: Support model reliability, trustworthiness and security by incorporating risk management in model operations.  

    5. AI Security and Resilience: Adopt specific AI security measures against adversarial attacks to ensure resistance and resilience. 

  • By 2026, organizations that operationalize AI transparency, trust and security will see their AI models achieve a 50% result improvement in terms of adoption, business goals and user acceptance. 

  • “Organizational peers with vested interest in AI must work together to manage AI privacy, security and risk.”

Articulating the Value of a D&A Initiative in Four Easy Steps

Presented by Nate Novosel, VP, Advisory, Gartner

Data and analytics (D&A) leaders are responsible for creating enterprise value to generate opportunities, and play a crucial role in business strategy. However, D&A leaders struggle to produce clear, measurable business value. In this session Nate Novosel, VP, Advisory at Gartner explained how D&A leaders can get more business value from their data. 

Key Takeaways

  • There are four steps to articulating D&A value:        

       1. Tying data pain points and opportunities to business goals

       2. Identifying the potential value of a data improvement

       3. Measuring the value of a D&A investment

       4. Visualizing and articulating the value to business leaders 

  • “Making the case for data investments should focus on showing the improvements to the decisions that will drive strategic goals.” 

  • “Creating a data-driven culture is not just the execution of a grand information architecture transformation; it is a set of minor, gradual changes to how staff make decisions.” 

  • D&A teams should measure four altitudes of improvements to how their organization uses data to get value: Outcome, decisions, D&A initiatives and data measures.

  • “D&A initiatives should aim to improve the inputs and results of better analysis and decision-making, including improving data, data management and data literacy.”

About Gartner

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