InfoVerge Highlights Key Steps for Scaling AI Successfully
Before scaling AI initiatives, organisations must establish clear data policies, strong data governance, and solid security protocols. This was the core message from InfoVerge’s technical experts during their Digital Frontier webinar series, emphasizing the crucial role of quality data as the foundation for AI deployment.
Data Quality and Governance: The Starting Point
Ntiyiso Mayile, Chief Data Officer at InfoVerge Solutions, pointed out the complexity of the AI landscape. He stressed that AI doesn’t operate in a vacuum and requires solid, fundamental data inputs to function effectively.
Skhumbuzi Mjoji, CTO at InfoVerge Solutions, added that without high-quality and well-governed data, even the most advanced AI systems can’t produce reliable or scalable results. AI models depend on structured, semi-structured, and unstructured data to learn and improve, making a strong data foundation essential.
Common Challenges in Scaling AI
Many organisations struggle to move AI from pilot phases to production due to:
- Lack of a proper data foundation
- Insufficient data governance
- Fragmented technologies and data silos
- Poor data management practices
Mayile warned that without effective data management and governance, AI projects risk bias, security issues, and unreliable outcomes, potentially turning AI into a liability rather than an asset.
Building a Data Culture and Clear Objectives
Developing a data culture is critical. Everyone in the organisation must understand the importance of the data they handle. It’s not just the IT department’s responsibility.
Mayile urged organisations to treat data as a valuable asset, not just a by-product of business processes. Clear objectives are essential before adopting AI. Without defined use cases, AI adoption may fail to deliver meaningful results.
“You need a lot of quality data and compute power. Many organisations also lack clear goals for AI use,” explained Mayile. “Building the right infrastructure to support AI workflows is key, rather than trying to retrofit existing systems.”
Balancing Innovation with Governance
Organisations must find a balance between fostering AI innovation and maintaining governance. A flexible governance framework should adapt based on AI’s potential impact and encourage collaboration and transparency across teams.
InfoVerge’s Five Pillars for AI-Ready Data Foundations
InfoVerge recommends focusing on these five pillars to build a scalable and trustworthy AI foundation:
- Develop an AI-first data strategy that prioritises integration and accessibility
- Create a unified, reliable data repository for consistent data access
- Accelerate AI initiatives to generate faster insights
- Manage, govern, and secure data throughout the AI lifecycle
- Streamline data operations to reduce costs and support scalable AI deployment
Upcoming InfoVerge Webinars
InfoVerge’s Digital Frontier series continues with two upcoming webinars:
- From Data to Intelligence – Activating Smarter Operations: 23 July
- Scaling AI Success – Governance, Ethics, and Future-Proofing: 17 September
These sessions will explore practical tools and strategies to scale AI initiatives responsibly and effectively.
For those looking to deepen their AI knowledge and skills, exploring structured training programs can be valuable. Visit Complete AI Training’s latest AI courses for options tailored to management and technical professionals.
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