Is your data AI-ready?
That was a consistent theme at this year’s Gartner Data & Analytics Summit in Orlando, Florida. There were many Gartner keynotes and analyst-led sessions that had titles like:
- “Scale Data and Analytics on Your AI Journeys”
- “What Everyone in D&A Needs to Know About (Generative) AI: The Foundations”
- “AI Governance: Design an Effective AI Governance Operating Model”
The advice offered during the event was relevant, valuable, and actionable. If attendees learn from the shared experiences offered by Gartner and many of the customer speakers and practitioners, they’ll be better equipped to drive greater value from their organization’s data strategies.
But as I shared in a previous post, “Data Integrity for AI: What’s Old is New Again,” much of this advice surrounding AI will be hauntingly familiar to those of you who have journeyed in the data management and analytics space through the last three decades. Familiar recommendations included:
- Tie your data strategy and priorities to clear and measurable business value. As Gartner analyst Saul Judah stated in his presentation, “How to Create a Data and Analytics Strategy for Real Business Results”:
“The goal is to create a business strategy that is infused with data, analytics and AI — not a data strategy or an analytics strategy.“
- Prioritize data quality. It was repeated consistently throughout the event – you need to ensure your AI, analytics, and operational initiatives are working with trusted, fit-for-purpose data.
To further drill home this point, in their opening keynote to kick off the conference, Gartner analysts Carlie Idoine and Gareth Herschel shared:
“Data availability or data quality is the #1 obstacle to implementing AI.” (Source: 2024 Gartner AI Mandates for the Enterprise Survey)
- Build and scale your data governance program. This is not new news – organizations must define foundational data-centric processes, policies, roles, and responsibilities with data governance (and now AI governance).
Gartner Director Analyst, Sue Waite summed it up best in her presentation, “5 Things That Keep Heads of Governance Up at Night.” She shared that many of her clients continue to ask:
“Why don’t they see how important governance is?”
So, do these sound familiar? Even with the addition of AI-readiness as a trending priority, the recommendations on how to move forward have not dramatically changed. The Gartner analyst sessions that I attended also acknowledged this reality.
Sue’s question above mirrored one my key takeaways from the event: “Why is no one listening?” Or maybe better stated: “If they’re listening, why aren’t they succeeding?”
Sue also shared an illuminating stat from Gartner’s 2024 CDAO Agenda Survey,
“89% of respondents said effective D&A governance is essential for enabling business and technology innovation. Yet only 48% of respondents have a consistent set of governance policies and practices that apply to all data, analytics and AI assets.“
This tells us that the disconnect isn’t due to a lack of awareness – it’s a matter of execution. Many organizations are still working through the foundational data challenges that have existed.
Services
These services provides a comprehensive range of consultative services tailored to your specific requirements, focused on delivering measurable outcomes and achieving your objectives.
Attendees continue to focus on data management fundamentals
My Precisely colleagues and I were fortunate to have collectively held hundreds of conversations with the data and analytic professionals at the event. Many were aware of – or at least had a perspective to share – on their organization’s journey to crafting their AI strategy.
While some attended the event to solve a specific “AI-readiness” challenge, many others are still working on more longstanding priorities around digital-transformation-themed operational and analytic improvements. To name a few:
- Data modernization
- Data governance
- Cloud analytics
- Customer retention and experience
- Compliance
These aren’t always framed as “AI-readiness,” but I would argue that all these familiar initiatives are in fact helping to get their organization’s data AI-ready. Focusing on these fundamentals will accelerate their journey to deriving value from transformative AI adoption.
Members of our team will also be attending Gartner’s UK Summit in May, and I’m eager to hear the key takeaways from those conversations. It’ll be interesting to see whether the same challenges emerge – particularly around themes like data governance, quality, and AI readiness – or if new priorities begin to take center stage.
Where is your organization on the journey to AI-readiness? What’s holding you back from success? If you’re feeling stuck, I’d recommend reaching out to our Strategic Services team – they’ll help you tailor a data strategy that’s best suited to your unique needs and objectives. Then, you’ll be equipped for true AI-driven success.
