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.
Palantir challenges traditional ERP and standardization, suggesting an alternate approach in the current economy and age of AI.
Jalapeño represents OpenAI’s first major move into custom AI hardware, combining the company’s AI architecture expertise with Broadcom’s semiconductor manufacturing capabilities to deliver faster, more energy-efficient inference for large language models.
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.
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.
The AI market is entering a new chapter where execution and business outcomes matter more than proving technological capabilities.
As AI token demand surges, CEOs must take ownership of allocation strategy to ensure scarce AI resources drive business outcomes, not internal politics.
Addition to the company’s governance control plan eliminates a wide range of manual steps required to transition an agent from local usage to enterprise availability.
OpenAI’s new token management tool highlights a deeper challenge: CEOs, not AI administrators, must decide how scarce AI resources are allocated across the business.
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.
Microsoft modernized employee device procurement with a centralized platform before adding agentic AI, cutting costs by $20M and simplifying the user experience.
Sachin Gandhi outlines how enterprises are scaling AI through a growing ecosystem of first-party, partner, and custom agents across core business functions.
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.
A cautionary look at AI adoption, highlighting how poorly chosen use cases and immature implementations can create more operational disruption than business value.
KPMG and Microsoft are expanding their partnership to help enterprises deploy agentic AI at scale through standardized governance, deployment, and management frameworks.
As AI spending surges, AWS argues that companies cannot ignore technical debt, which continues consuming substantial IT resources that could otherwise fuel innovation.