Quantum computing presents both opportunities and risks, particularly for enterprises regarding cybersecurity. As algorithms used today may be vulnerable to quantum attacks, organizations must prioritize Post-Quantum Cryptography (PQC) to protect critical data. Immediate action is necessary to assess vulnerabilities, update encryption strategies, and prepare for upcoming threats.
IBM drives enterprise change through innovation in both AI and quantum
At IBM’s Think conference in Boston, key themes included an AI-first enterprise, hybrid cloud, and quantum technology. Engaging discussions with leadership highlighted the need for tailored tech strategies. Notable announcements featured AI tools like IBM Bob and advancements in quantum computing. Governance remains a critical focus for CIOs considering AI deployment.
AWS moves further into enterprise applications with Quick, Connect Talent, Connect Decisions and Connect Health
Last week, AWS held their “What’s next with AWS” event in San Francisco. The event brought together a group of analysts, media and customers to view their new launches firsthand. In addition, the event keynote was livestreamed for those who…
The AI Hypercomputer: Why Google is No Longer “Just Another Cloud”. Key takeaways from Google Cloud Next 2026
It is 2026 and enterprise customers are looking at how to effectively leverage both AI and cloud to advance their company’s position and provide greater value to customers. This week is Google’s annual Google Cloud Next conference in Las Vegas…
The Trojan Horse in Your Inbox: Why Personal AI Agents are a CIO’s Newest Nightmare
Agentic AI personal agents are gaining traction for enhancing productivity, but they present significant risks for CIOs due to potential data breaches and malicious activities. While they can streamline workflows by accessing user data, the lack of governance and oversight raises concerns. Organizations must educate users on the associated risks and implement security measures to safeguard sensitive information.
Is SaaS dead? The reports of SaaS’ death are greatly exaggerated.
The discussion centers on whether AI can replace Software-as-a-Service (SaaS) applications. While many assert AI will fully replace SaaS, it's more accurate to say AI may augment or improve certain SaaS functionalities. The complexity of building enterprise applications using AI, alongside governance and operational challenges, suggests that a complete replacement is improbable.
Artificial intelligence is revolutionizing customer engagement strategies for contact centers and service management
The discourse surrounding AI in contact centers suggests a nuanced approach rather than outright replacement of human agents. While AI can enhance efficiency and improve customer experience, it poses challenges, especially with ingrained systems. Successful integration requires understanding business needs and leveraging AI to augment, not entirely replace, human roles, focusing on value enhancement.
Beyond the Hype: 9 Cybersecurity Realities CIOs Must Face at RSAC 2026
Enterprises must rethink cybersecurity strategies in 2026, driven by advancements in AI and quantum technologies. The upcoming RSAC conference will highlight key areas to watch, including AI applications, network security, simplification of solutions, post-quantum cryptography, and evolving identity management. These aspects reflect the complexity and urgency of current cybersecurity challenges.
Cisco AI Summit Expands and Elevates the Enterprise AI Conversation
Cisco's AI Summit in San Francisco featured prominent industry leaders discussing AI's potential and challenges. Key themes included the importance of trust, infrastructure constraints, and the need for effective data management. Cisco executives emphasized AI's transformative role in enterprise, urging a rethinking of technology utilization to harness opportunities and address current gaps.
Why AI is failing in the enterprise and two ways to correct it
Enterprises face challenges proving positive ROI from AI, with only 5-25% success reported. To overcome these hurdles, two pathways emerge: embedding AI seamlessly into existing processes and providing user training. Effective adoption requires understanding user workflows and ensuring AI's integration enhances, rather than disrupts, established practices.