Solgari’s Ed Grant explains why customer engagement data is the foundation of successful AI strategies and how organizations are turning conversations into business outcomes.
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The next wave of enterprise AI will depend less on models and more on governed, connected data and operational context, according to Salesforce and Databricks.
The new AI Deployment Wars reveal that enterprise customers need more than technology: they need strategy, process modernization, secure integration, and change management.
Microsoft is accelerating its Frontier Firm vision with a new business unit that embeds 6,000 AI and industry experts directly with customers to build, optimize, and scale enterprise AI systems.
Palantir makes the argument that while some ERP standardization can be beneficial, an over-reliance on it can lead to squandered opportunity with emerging tech.
The companies that survive disruption are the ones focused on solving problems, not protecting products.
Akrites coordinates disclosure and remediation as discovery of open-source vulnerabilities in the AI Era is outrunning defense.
Microsoft is shifting Copilot Cowork to usage-based pricing while exploring lower-cost AI models, signaling a strategy focused on performance, economics, and customer choice.
Working with DynaTech Systems, Solmax standardized global business processes and created a single source of truth, helping eliminate data silos and improve financial and operational decision-making across multiple regions.
Enterprise AI growth increasingly depends on implementation expertise rather than model capabilities alone.
Dona Sarkar says AI has yet to find its defining mainstream use case, and the companies preparing now will be best positioned when that breakthrough moment arrives.
Google Cloud, OpenAI, and Anthropic are investing heavily in deployment capabilities, ecosystems, and forward-deployed engineers to help customers achieve measurable business outcomes and accelerate enterprise AI adoption beyond model selection.
The race to transform enterprises through AI is creating unprecedented demands for deployment expertise, customer success, and organizational change management.
IBM and Google Cloud have launched a new Google Cloud Practice designed to help organizations accelerate AI deployments by combining IBM Consulting expertise with Google Cloud’s Gemini Enterprise Agent Platform, cybersecurity capabilities, and advanced data technologies.
As AI spending surges, AWS argues that companies cannot ignore technical debt, which continues consuming substantial IT resources that could otherwise fuel innovation.
The Hyperscaler Backlog Sweepstakes defines the top AI factories, ranking Google Cloud, Oracle, Microsoft, and AWS in the top four.
Pinterest has signed a $4 billion infrastructure agreement with AWS through 2031, marking the largest technology commitment in its history. The partnership will support AI innovation, improve discovery experiences, and provide scalable infrastructure for hundreds of millions of users.
Google Cloud’s agreement with EQT could accelerate AI adoption faster than conventional sales strategies by reaching hundreds of companies through a single partnership.
At Workday DevCon in Las Vegas, Workday introduced major developer platform innovations, including Developer Agent and an agent-ready version of Workday Build, designed to accelerate AI-powered application development while maintaining enterprise-grade security and governance.
Christopher Lochhead explains why AI is commoditizing knowledge and execution, making creativity and differentiation the most valuable assets in business.