AI platform providers are stepping up efforts to strengthen agentic AI governance, improve visibility and control over token usage, and offer enterprises greater flexibility in how AI solutions are deployed.
As the excitement around agentic AI continues to build, several AI platform providers have rebranded their solutions over the past year. While their platforms now put agentic AI front and center, they also encompass tools for developing predictive machine learning models and supporting generative AI applications.
Within this rapidly evolving landscape, Google and Amazon have emerged as clear leaders in cloud-based enterprise AI platforms, according to GlobalData, a leading intelligence and productivity platform.
GlobalData’s latest report, “Cloud-based Enterprise AI Platforms: Competitive Landscape Assessment,” reveals that sovereignty concerns are increasingly top of mind as enterprises seek greater control over critical operations. At the same time, demand is growing for stronger guardrails, including the ability to disable AI agents, alongside enhanced observability tools.
Google and Amazon stand out by offering a comprehensive suite of model development and management tools, access to leading large and specialized language models, and complementary data storage and management solutions that provide enterprises with a more seamless experience.
Rena Bhattacharyya, Chief Analyst and Practice Lead, Enterprise Technology and Services at GlobalData, said: “The platforms have expanded to include capabilities that help organizations incorporate, customize, and evaluate large language models (LLMs), as well as deploy AI agents. They are increasingly offering features that help organizations govern agentic AI and deploy responsible and ethical AI, such as the ability to create audit trails and track AI agents built on other platforms.”
GlobalData also notes that AI platform providers are responding to growing concerns over the rising costs of AI inference by introducing tools designed to give users greater control over token consumption. These tools allow organizations to set usage limits based on a range of criteria, including by person, department, or project.
Alfie Amir, Senior Principal Analyst, Enterprise Technology and Services at GlobalData, observes: “Frustrations over measuring ROI and meeting project expectations are spreading. Enterprises are moving from a strategy of ‘token maxxing’ to one of ‘value maxxing’ to focus more on the success of a project than on the amount of AI consumption.”
Bhattacharyya concludes: “Google’s internally developed suite of language models is broad and impressive. It was early to market with AI agent development tools, and it demonstrates thought leadership by developing the Agent2Agent (A2A) protocol with its peers. Amazon boasts a broad portfolio of solutions, from data management to AI agent development, as well as strong partnerships with IT services providers and a marketplace that provides access to partners’ solutions.”
