The agentic AI era is here: Key takeaways from Google Cloud Next ’26

Google Cloud Next ’26 brought more than 32,000 leaders, developers, partners, and customers to Las Vegas with unmistakable Google energy: bold ideas, fast-moving innovation, and a clear focus on the next era of enterprise AI. This year, the conversation moved beyond experimentation and into execution, with Google Cloud placing the agentic AI for enterprise at the center of its vision.

For SoftwareOne, Next ’26 reinforce the critical role partners play in helping organizations translate innovation into practical, measurable outcomes with Google Cloud. The announcements at Next ’26 showed how quickly the agentic era is taking shape – and why that success will depend on more than technology alone. Organizations need trusted guidance across strategy, data readiness, governance, security, change management, and adoption. With our experience across cloud, AI, workplace, and managed services, SoftwareOne is well positioned to help customers move with confidence.

“Google Cloud Next ’26 made one thing clear: the agentic AI era is no longer a future concept – it is becoming the new operating model for businesses,“ said Gudmundur Adalsteinsson, Chief Partner & Sales Officer at SoftwareOne. “As Google AI becomes more open and connected across existing clouds, applications, and workflows, SoftwareOne is here to help customers turn that flexibility into real business impact with the strategy, governance, and adoption expertise needed to deliver it.”

Partners powering the agentic enterprise

Kevin Ichhpurani, President of Global Ecosystem at Google Cloud, used Next ’26 to underline a central point: the agentic era will be built with a strong, capable, and deeply connected partner ecosystem. As part of that commitment, Google Cloud announced a $750 million partner innovation fund to accelerate agentic AI development and deployment globally – supporting consulting firms, software partners, and channel partners as they build, scale, and bring new AI agent solutions to customers.

The announcement also highlighted new ways for customers to discover and deploy partner-built agents through Gemini Enterprise, including the new Agent Gallery, alongside expanded technical collaboration, training, workshops, incentives, and access to Google expertise.

This is where the trusted advisor role matters: helping customers identify the right use cases, build the right foundations, and scale AI in a way that is secure, governed, and tied measurable to business value.

AI agents move into the flow of work

A consistent theme ran through Google Cloud Next ’26: AI is becoming more integrated, more actionable, and more embedded in the way organizations work. In his keynote, Thomas Kurian, CEO of Google Cloud, positioned the agentic enterprise not as a future ambition, but as something already taking shape – with AI agents beginning to support people, teams, and businesses across everyday workflows, core processes, and customer experiences.

Google Cloud’s announcements brought together Gemini models, Workspace, data, security, infrastructure, and agent development into a more connected enterprise AI platform.

This is where Google Cloud’s full-stack advantage becomes important: Gemini Enterprise is built on Google Cloud’s integrated AI stack, designed to help organizations build, run, govern, and scale AI agents with performance, security, and efficiency in mind. For organizations, the value of AI will not come from isolated experiments, but from connecting the right use cases with the right data, tools, controls, and adoption approach – so agents can move into the daily flow of work and deliver measurable business impact.

Gemini Enterprise becomes the front door to AI

At the center of the announcements was the Gemini Enterprise Agent Platform, Google Cloud’s comprehensive platform to build, scale, govern, and optimize agents. The platform brings together capabilities from Vertex AI with new features such as Agent Studio, Agent-to-Agent Orchestration, Agent Registry, Agent Identity, Agent Gateway, Agent Observability, Agent Simulation, and Agent Evaluation – all designed to help organizations move from agent pilots to governed, production-ready deployments.

This marks an important shift for enterprises. Agentic AI will only deliver value when it can operate securely across data, applications, workflows, and people. For SoftwareOne customers, the opportunity is not simply to build more agents, but to build the right agents – connected to clear business outcomes, supported by governance, and designed to scale responsibly.

Workspace brings agents closer to everyday work

For many organizations, the most immediate impact of agentic AI will be felt in the tools employees already use every day. Google announced new Agentic Taskforce capabilities across Gemini Enterprise for Customer Experience and Google Workspace, including Workspace Intelligence, which provides a unified context layer across Workspace apps.

These announcements point to a more connected way of working. Features such as brand-aware content creation in Docs and Slides, improved Microsoft 365 interoperability, AI-supported migration, meeting summaries across Zoom, Teams, and in-person meetings, and governed agent access across Workspace all help reduce friction, and accelerate adoption, and make AI useful inside the real flow of work not outside it. The focus is no longer on individual productivity gains, but on connecting work across documents, meetings, data, and business processes.

AI infrastructure built for the economics of agents

Google also made major announcements across AI Infrastructure, including its eighth-generation TPUs: TPU 8t for training and TPU 8i for inference. TPU 8t is designed to deliver significantly more processing power for advanced AI training, while TPU 8i focuses on cost-effective, low-latency inference for production workloads.

This is a critical point for enterprise adoption. As organizations move from AI pilots to production-scale agents, cost, latency, performance, and reliability become board-level considerations. The economics of agentic AI will matter as much as the innovation itself. Customers will need to understand which workloads require advanced AI infrastructure, how to forecast consumption, and how to balance performance with financial governance.

Data and security become the foundation for agentic AI

Google’s Agentic Data Cloud announcement introduced an AI-native architecture designed to help organizations use data at the speed and scale required by agentic AI. Key capabilities included Knowledge Catalog, Data Agent Kit, and a cross-cloud, AI-native Lakehouse to help organizations ground agents in trusted business context across their data estate.

At the same time, Google announced Agentic Defense, combining Google Threat Intelligence and Security Operations with Wiz’s Cloud and AI Security Platform to help organizations prevent, detect, and respond to threats across multicloud, hybrid, and AI environments. New security agents support areas such as threat detection, detection engineering, and remediation.

For SoftwareOne, this is where the conversation becomes especially important. AI agents are only as valuable as the data they can trust and the controls that govern them. Organizations will need to think about security, identity, compliance, data quality, and operational accountability from the beginning – not after agents are already deployed. This is what will separate scalable AI transformation from fragmented experimentation.

Customer connections beyond the keynote

At Next ’26, the conversations did not stop when the keynotes ended. SoftwareOne also brought together customers and colleagues for a dedicated VIP customer experience in Las Vegas – creating space for deeper conversations, relationship-building, and reflection on what these announcements mean in practice. Moments like this are an important part of our partnership with Google Cloud: connecting innovation with real customer priorities and helping organizations turn event inspiration into the next steps of their AI journey.