The report, "Cloud-based Enterprise AI Platforms: Competitive Landscape Assessment," finds that AI platform providers across the market are racing to add agent governance capabilities, improve token usage visibility, and extend deployment options for organisations with data sovereignty concerns. Several vendors have rebranded their platforms over the past year to lead with agentic AI.
"The platforms have expanded to include capabilities that help organizations incorporate, customize, and evaluate large language models, as well as deploy AI agents," said Rena Bhattacharyya, Chief Analyst and Practice Lead, Enterprise Technology and Services at GlobalData. "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 identifies a shift in how enterprises are thinking about AI consumption. Alfie Amir, Senior Principal Analyst at GlobalData's Enterprise Technology and Services practice, described the change as a move "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." Frustrations over measuring return on investment and meeting project expectations are spreading, he noted.
Bhattacharyya concluded: "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."
The GlobalData report covers sovereignty, killswitch controls for agents, observability tooling, and LLM customisation as the primary capabilities enterprise buyers are now evaluating.
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