Enterprise AI transformation has a new home: the boardroom. Across financial services, CEOs are now demanding results, not more roadmaps. As Google Cloud Next 2026 packed Las Vegas with announcements — from the Gemini Enterprise Agent Platform to eighth-generation Tensor Processing Units — a clear theme emerged among systems integration partners: The era of tinkering is ...

AI policy fragmentation is emerging as a critical risk for Washington, and without a federal standard, a patchwork of conflicting state-level rules threatens to undermine American competitiveness. That gap is precisely what Appian Corp. is moving to address at the highest levels of government. The process automation company serves federal, state and local agencies — from the ...

Google LLC and Anthropic PBC are two of the most powerful forces shaping enterprise AI. As agentic deployments demand platforms that are both capable and safe to build on, the Google-Anthropic partnership is fast becoming the model others are measured against. Google and Anthropic have spent three years building one of the most consequential partnerships ...

As AI rapidly rewrites enterprise economics, cloud cost optimization has become essential for preventing budgets from collapsing under AI workloads, enabling organizations to slash expenses and redirect engineering talent from reactive firefighting to higher-value innovation. Nordstrom Inc. learned that lesson firsthand after migrating its data warehouse to Google Cloud LLC’s BigQuery, a move that exposed ...

As enterprises navigate the complexities of scaling AI initiatives, the agentic AI blueprint for success lies in combining deep process intelligence with powerful cloud platforms, enabling organizations such as Genpact Ltd. to transform finance and operations workflows through reimagined processes and effective partner ecosystems. That convergence defines the moment the industry finds itself in as ...

Consumer packaged goods companies face mounting pressure to grow profitably while operating on razor-thin margins — and agentic AI is emerging as the tool that can close the gap between fragmented data and real-time marketing outcomes. The sector has long relied on weeks-long campaign measurement cycles, disconnected consumer data and costly physical test markets to ...

The agentic AI boom has an inconvenient truth: Without a solid data foundation, the revolution stops before it starts. Conversations surrounding an emergent agent control plane signal that agentic AI is maturing — but the enterprises best positioned to capitalize are those that did the unglamorous data work years before the hype arrived. That divide between prepared ...

As enterprises pivot from AI experimentation to production deployment, AI storage infrastructure is emerging as the critical bottleneck determining whether massive chip investments deliver real returns. The central challenge for running large-scale AI workloads has shifted from building models to keeping the accelerators that run them fully fed. GPU and tensor processing unit utilization rates ...

Enterprise AI ambitions are stalling not because models are hard to build, but because the data foundations underneath them were never designed to support intelligent workloads at scale — and a unified data lakehouse architecture might be the solution. The problem is especially acute for legacy organizations carrying decades of accumulated data infrastructure built in ...

AI investment is surging to manic heights, but C-suites have yet to see it translate into measurable business outcomes — a gap that is now one of the defining strategic challenges of the current technology cycle. As Google Cloud Next 2026 showcases a full-stack push toward agentic infrastructure, a quieter and more urgent conversation is ...