Digital Transformation Gap Between Strategy and Execution

New tools aren’t the answer, how we use them is.   In this interview with Dice, I share why IT teams need to shift from chasing the next tool to taking ownership of their full stack. The real impact comes from simplifying, integrating, and making smarter decisions about what drives business outcomes.   The teams that stand out are the ones who: Understand how everything connects, including cloud, data, security, and operations Reduce unnecessary complexity Turn technical insight into clear business decisions   Take a look here: https://lnkd.in/dKpFaVEU   #DigitalTransformation #ITLeadership

Here's the latest in Gemini Enterprise, your end-to-end system for the agentic era: All of Google Cloud's AI tools are now under one roof to help you securely build, scale, and govern agents across your organization. Read more from #GoogleCloudNext.

Here's the latest in Gemini Enterprise, your end-to-end system for the agentic era: All of Google Cloud's AI tools are now under one roof to help you securely build, scale, and govern agents across your organization. Read more from #GoogleCloudNext.

Here's the latest in Gemini Enterprise, your end-to-end system for the agentic era: All of Google Cloud's AI tools are now under one roof to help you securely build, scale, and govern agents across your organization. Read more from #GoogleCloudNext.

Unmanaged SaaS and shadow AI = hidden risks. ⚠️ Download the solution brief, "SaaS Access Governance," to see how better governance closes the gaps. 1Password

Microsoft has been recognized as a leader in API management, showcasing how Azure API Management effectively governs, secures, and observes APIs at a global scale. I found it interesting that this recognition highlights the increasing importance of API governance in digital transformation. What are your thoughts on the role of API management in shaping the future of technology?

The world is bimodal again. We have seen this before: on-prem vs. cloud, desktop vs. mobile, and other shifts where organizations moved from one fundamental operating model to another. No one moved 4,000 servers to AWS overnight. Enterprises ran both models in parallel until the new one proved itself. That is similar to what is happening with AI. Some organizations use AI to amplify existing processes, others are building agentic systems to develop and operate software in an AI-first way. Both modes will coexist, and both will depend on observability, but they will require fundamentally different kinds of it. I discuss the details of this transformation in my latest blog - https://lnkd.in/d2tM8nrk

just had a thought, agent surfaces are feedback-loop shaped. Slack is great when the loop is tiny: ask, confirm, done. Desktop/CLI wins when the work needs context, diffs, logs, tests, and correction. Cloud agents are best when parallelism matters more than immediacy. The right surface is the shortest loop that can still hold the work. https://lnkd.in/euG_eH9h

Attended the Asia Pacific Best of Next ‘26 by Google Cloud today. It was an insightful experience exploring how AI, cloud infrastructure, and agentic systems are shaping the future of technology and enterprise applications. Some of my key learnings and highlights from the event: • The overall focus of the event was on the “Agentic Cloud” and how organizations are moving beyond basic AI adoption toward large-scale AI-driven transformation. • The keynote sessions by leaders including gave a strong perspective on how AI agents will become an important layer across enterprise workflows, infrastructure, and decision-making systems. • One of the most interesting sessions for me was around the Gemini Enterprise Agent Platform and how developers can build, scale, and govern sophisticated AI agents for real-world use cases. • Learned how the “Agentic Data Cloud” is evolving from traditional storage systems into intelligent systems of action capable of powering proactive and trusted AI agents at scale. • The sessions around AI infrastructure gave insights into how the industry is preparing for the agentic era with purpose-built hardware, scalable cloud systems, and flexible infrastructure models. • The developer-focused sessions were especially engaging because they focused on solving real engineering problems while building autonomous agentic applications. • Explored updates around Google Cloud databases and how multimodal AI applications can leverage unified real-time architectures for actionable insights. • The discussions around AI security were very relevant, especially understanding how organizations need to rethink security in a world of AI-driven systems, agents, and autonomous workflows. • It was also interesting to see practical applications of AI through customer stories and demos from organizations working on retail intelligence, AIoT systems, customer experience, and enterprise automation. • Another valuable takeaway was understanding how low-code and AI-powered tools are enabling even lean teams and smaller organizations to build intelligent systems faster. • The event also highlighted how tools like Gemini Enterprise, Google Workspace integrations, and generative AI models are improving productivity, collaboration, and business operations at scale. • I particularly enjoyed the combination of technical deep dives, architecture discussions, product launches, demos, and real-world implementation stories shared throughout the sessions. Overall, the event gave me a much clearer understanding of where AI engineering, cloud computing, infrastructure, and enterprise systems are heading in the coming years. Looking forward to exploring more in AI agents, scalable systems, cloud technologies, and real-world AI applications.

May 04, 2026: AI Disruption forces a reevaluation of IT service delivery models, challenging traditional SaaS licensing. Read the full breakdown: https://lnkd.in/dbXhq2Fd #agenticsystems #enterpriseai #itmanagement #saasmodels