Summary
Preparing your data for AI in 2025 requires embracing emerging tech trends—from agentic AI and AI governance platforms to data fabrics and hybrid computing—while applying unconventional thinking, such as targeting high-impact outliers rather than the average case.
Action points: review and align your data strategy with Gartner’s 2025 technology priorities, strengthen data governance by evaluating or implementing AI governance platforms, explore data fabric patterns for unified data orchestration, and adopt bold, high-leverage use cases rather than incremental fixes to drive real business impact.
Understanding how to prepare data for AI implementation in 2025 is like having the secret sauce in a Michelin chef’s recipe—essential for success.
After attending the Gartner IT Symposium, Adrian Heim (Head of Sales and Marketing at Calibo) and Cyril Soga (Head of Analyst Relationships at Calibo) discussed the latest trends in AI and data management in a fireside chat-style webinar.
They discussed the latest trends and insights that organizations need to embrace in 2025 and beyond. This blog delves into the strategic technology trends outlined by Gartner and provides a roadmap for making your data AI-ready.
Watch the full webinar here.
Malcolm Gladwell’s keynote speech during the symposium emphasized the need for radical asymmetric distribution in problem-solving. His talk highlighted how outlier-focused models can lead to more effective solutions, using COVID-19 as a prime example.
Initially, most countries focused on lockdowns based on a conventional bell curve approach, targeting the majority.
However, the key to controlling the virus was understanding that 10% of the population—those emitting significantly more aerosols—played a disproportionate role in spreading the virus. This analogy serves as a powerful reminder that innovative solutions often come from unexpected places, encouraging organizations to adopt unconventional approaches to complex problems.
Cyril outlined Gartner’s ten strategic technology trends for 2025, categorized into three primary areas: AI imperatives and risks, new computing frontiers, and human-machine synergy.
Looking ahead to 2025, several AI priorities have been identified for enterprises to focus on:
Platform engineering plays a critical role in preparing organizations for AI implementation. It serves as an enabler of efficiency, providing integrated tools and automated processes that simplify the application lifecycle.
Drawing an analogy to a shopping mall, platform engineering offers a ready-to-use environment that eliminates the need to build infrastructure from scratch, allowing developers to focus on innovation.
The concepts of data mesh and data fabric are advanced approaches to data management.
In conclusion, the future of data and AI is rapidly evolving, and businesses must stay ahead by integrating advanced technologies and approaches.
By aligning with the strategic trends and insights discussed at the Gartner IT Symposium, organizations can make their data AI-ready and leverage these innovations to drive growth and competitiveness in 2025 and beyond.
To get the full scoop, watch the full webinar here.
What does it mean to make data AI-ready?
It means ensuring your data is governed, accessible, and orchestrated across systems so it can support advanced use cases like generative AI, automation, and real-time analytics.
What key trends from Gartner should organizations act on now?
Agentic AI, AI governance platforms, data fabrics, and hybrid computing were highlighted as 2025 priorities that businesses should begin evaluating and adopting.
What practical steps can teams take today?
Align your data strategy with high-impact use cases, strengthen governance with policy-driven platforms, adopt data fabric patterns for orchestration, and focus on bold initiatives that deliver outsized business value.
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