Getting Your Data AI-Ready

Rapid data creation and escalating needs for storage and processing may lead to significant strain on legacy infrastructure across an organisation. And as IT leaders look to implement AI and maximise its business value, solving these infrastructure challenges becomes crucial.

How can IT and security leaders ensure that their data is ready for AI? CIOs and CISOs in our Sydney communities gathered recently to discuss how to navigate the explosive growth of data, identify the solutions needed for an AI-ready infrastructure and establish the foundations to enable the business in an AI-focused world.

Dan Eline, Vice President, Platform Solutions at Digital Realty moderated the discussion. Sydney Governing Body Members Santosh Adsul, Head of IT, ANZ at TK Elevator; Artak Amirbekyan, Head of Data, AI and ML at Transurban; Khurram Malik, Chief Information Technology Officer at Ingenia Communities Group; Morgan Donnelly, Head of Cyber Risk, Westpac Group at Westpac; and Danny Walsh, Business & Technology Services (BTS) Director, at George Weston Foods led their peers in small group discussions.

Across our communities, data and analytics and delivering value with AI are important focus areas for CIOs in our annual Leadership Perspective Survey. Data governance and generative and traditional AI are also top priorities for CISOs. Here are the key takeaways from their discussion on the intersection of data and readiness for AI.
 

Key Takeaways from the Discussion

• Navigating the explosive growth of data.

Managing the explosive growth of data may require new thinking and strategies for CIOs and CISOs. One executive explained the concept of data gravity, saying, “Data has mass, and as it grows, it’s increasingly difficult to move it or replicate it in a practical sense.” Executives agreed that they are focusing on where their data resides and how to effectively bring applications and services to the data.

Another executive noted that as IT and security practitioners, the default mode is “to take a systems type of view. What if we consider data as a logistics problem? What data do we have and where does it need to be?” Executives likened this concept to having a “data quarter master” to organize and manage the delivery of data assets. 

CIOs and CISOs also shared that they are shifting towards data-first thinking, as well as prioritizing data governance, quality, and proper permissioning. One noted that “there is quite a lot of clean up activity going on in organizations” as they focus on the quality of data and permissioning.
 

• Identifying common challenges and solutions for an AI-ready infrastructure.

Executives identified those data governance and quality issues as a common challenge for them currently. As the amount of data is growing so quickly, they are finding they need to control its use and classification. One executive said that they “need to build quality control in, so that we don’t create a ‘garbage in, garbage out’ problem.”

Another CIO shared that the quality of an organization’s historical data can pose a challenge. They noted: “If you’re going back 20 years, the quality of data you collected then is different from what you’re collecting now. And if your model goes back 20 years, then you have a mixed quality of data.”

Overall, executives agreed on the need to implement quality control measures to ensure high-quality data and address the challenges posed by historical data and unstructured data growth. They also discussed compliance with privacy regulations, focusing on data storage locations and methods.
 

• Establishing foundations to enable the business in an AI-focused world.

When it comes to establishing the right infrastructure for AI, CIOs and CISOs agreed that they should start with the business process and align AI projects to business goals. As one said, “We want to take a business lens, not data or technology lens, and determine what matters about this to the business.”

CIOs and CISOs are also managing the transition to cloud solutions, with many organizations adopting hybrid approaches. Some have moved on from the infrastructure journey to data governance.

Executives are also addressing the challenges of legacy applications with one leader comparing these applications to an old car, “running steadily, until someone wants to change it, which introduces new challenges.” 

They also aim to establish policies and governance frameworks for AI deployment, similar to software development lifecycle processes, to ensure responsible and effective AI use. They discussed increasing awareness and education internally to differentiate between AI and basic automation, so they can adjust security concerns accordingly.

To join a conversation on data governance and AI readiness, community members can sign in to the app to find and register for upcoming events. If you are new to Gartner C-level Communities, apply to join your regional CIO or CISO community to connect with IT and security peers on critical priorities.
 

Special thanks to Digital Realty.