Dell Technologies has enhanced its cyber resilience portfolio in response to escalating cyber threats and the rapid adoption of AI, which is driving massive data growth.
Musa Masungwini, senior system engineer for data protection solutions at Dell Technologies sub-Saharan Africa, says companies face increasingly sophisticated attacks that disrupt operations, compromise data and damage trust.
“Today’s IT environments are more complex than ever before, spanning on-premises infrastructure, multicloud solutions and edge deployments. At the same time, cyber attacks are increasing in volume and sophistication,” says Masungwini.
According to Dell’s 2024 Global Data Protection Index, conducted by research firm Vanson Bourne, 88% of organisations expect GenAI to significantly increase data volumes – yet 65% back up less than half of their data.
“For business leaders, the stakes couldn’t be higher. Staying competitive in this volatile environment requires more than just innovation; it demands innovation that’s built on a foundation of cyber resilience,” says Masungwini.
Dell has integrated a generic application agent into its PowerProtect Data Manager, with custom script support, single sign-on integration and expanded CyberSense Analytics.
CyberSense Analytics now supports Microsoft Azure, which, according to Dell, offers 99.99% data integrity validation and expanded compatibility with Commvault backups.
The company has also shortened recovery time with improved orchestration tools, it states.
AI engineering
Dell asserts that AI holds real promise for businesses ready to put it to work, but there are challenges, including complex technology, disconnected teams and limited access to talent.
The company believes AI engineering is key to unlocking the benefits of AI.
Habib Mahakian, VP for southern and sub-Saharan Africa at Dell Technologies, says moving from ambitious ideas to something that actually delivers value requires more than just enthusiasm and access to new tools. “To unlock the full potential of their AI journeys, organisations need engineering, which turns concepts into solutions that drive real-world results.
"This is because each business brings its own data, workflows, people and goals to the AI initiative, which means solutions must be adapted, not just adopted. Delivering results takes sharp technical skills, plenty of co-ordination and an honest look at gaps in the current set-up.”
Even well-intentioned projects can end up in a holding pattern, never quite making it beyond the proof-of-concept stage. This challenge is echoed in recent Gartner research on the four emerging challenges to delivering value from AI safely and at scale.
“AI engineering puts the focus on execution. It’s about combining vision with hands-on problem-solving, using the right team and approach to bridge the gap from idea to working solution. At Dell, our experience has shown that cross-functional teams, what we call AI pods, work best,” Mahakian adds.
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