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Gartner urges data trust over AI hype for business success

June 30, 2025•Stephen Withers•Original Link•3 minutes
AI
DataTrust
AutonomousBusiness

Gartner analysts at the Sydney Data & Analytics Summit emphasized prioritizing data trust before AI adoption, highlighting the rise of autonomous business processes driven by AI agents.

At the Gartner Data & Analytics Summit in Sydney, analysts warned businesses against rushing into AI without ensuring data trust. Carlie Idoine, Gartner VP analyst, cautioned that "'Garbage in, garbage out' isn’t the worst thing in the world, but putting trust in that garbage is."

Key Takeaways:

1. Data Trust is Critical for AI Success

  • Gareth Herschel, another Gartner VP analyst, cited a 2024 survey revealing that data availability and quality are the top obstacles to AI implementation.
  • "If you cannot trust the data, you cannot trust the AI that uses it," Herschel emphasized.
  • Solution: Implement trust models that rate data reliability based on lineage and curation.

2. AI Agents vs. Generative AI

  • Erick Brethenoux, Gartner’s chief of AI research, clarified the distinction between AI agents (used for decades in tasks like predictive maintenance) and generative AI (like LLMs).
  • Agentic AI is largely a marketing term, but combining AI agents with LLMs can yield innovative results.
  • Challenge: Generative AI’s non-deterministic nature requires guardrails and simulations to ensure reliability.

3. Autonomous Business Processes

  • AI agents can execute multistep processes in parallel, saving time and costs. For example, loan applications can be processed faster by terminating failed checks early.
  • Autonomy levels: Low-risk decisions (e.g., travel arrangements) can be fully automated, while high-stakes scenarios may require human oversight.

4. ROI and Business Impact

  • Luke Ellery, Gartner VP analyst, noted that tools like Microsoft Copilot save only 14 minutes daily per employee, with a net cost of ~$1,150/year.
  • Upside: Employee satisfaction (NPS of 59 vs. 21 average) and perceived productivity gains.
  • Recommendation: Categorize AI use cases by value type and build a diversified project portfolio.

5. Future of Analytics: Perceptive Systems

  • Georgia O’Callaghan, Gartner director-analyst, predicted that by 2027, autonomous analytics platforms will manage 20% of business processes.
  • Trends:
    • Shift from reactive to proactive analytics.
    • Standalone tools replaced by integrated systems.
    • Dynamic, embedded insights over static dashboards.

Gartner’s 2027 Predictions:

  1. 50% of business decisions will be augmented or automated by AI agents.
  2. AI-literate executives will drive 20% higher financial performance.
  3. Task-specific AI models will outpace general-purpose LLMs in usage volume.

Final Warning for Leaders

  • Idoine warned that 75% of chief data and analytics officers risk being absorbed into tech functions if they fail to demonstrate organization-wide impact.
  • "AI is a juicy prize other leaders are eyeing," she said, urging professionals to "trust yourself, push the frontier."

For further reading, check out:

  • Gartner on agentic AI
  • 8 top predictive analytics tools for 2025
  • What is augmented intelligence?

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About the Author

Dr. Lisa Kim

Dr. Lisa Kim

AI Ethics Researcher

Leading expert in AI ethics and responsible AI development with 13 years of research experience. Former member of Microsoft AI Ethics Committee, now provides consulting for multiple international AI governance organizations. Regularly contributes AI ethics articles to top-tier journals like Nature and Science.

Expertise

AI Ethics
Algorithmic Fairness
AI Governance
Responsible AI
Experience
13 years
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95+
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