A clearer AI-analytics strategy, AI platform cohesion, more plug-and-play products, and a better vibe for coding need to be on show in Las Vegas to satisfy customers.
The mood among Amazon Web Services customers is shifting from curiosity to urgency as the company prepares to once again to “re:Invent” itself at its annual customer conference this week.
After a year in which Microsoft and Google tightened their narratives around unified data, AI platforms and workflow-ready agents, AWS can no longer rely on its scale, breadth, or incremental roadmap to maintain the confidence of CIOs.
Instead, say analysts, the hyperscaler must address four key concerns at re:Invent in Las Vegas this week if it wants to retain its position as the default enterprise cloud.
Closing the integration gaps between analytics, data, and AI
Although AWS is ahead in raw capability and breadth of services, say analysts, it is falling behind in its integration and unification of data, analytics, machine learning, and AI.
“It lags behind rivals on simplicity and integration,” said Phil Fersht, CEO of HFS Research. “Customers want fewer hops between analytics, machine learning, and generative AI. They want unified governance and a consistent metadata layer so agents can reason across systems,” he said.
Microsoft, at its Ignite customer event last month, beefed up its unified data and analytics platform, Fabric IQ, with new semantic intelligence capabilities. AWS, too, has been trying its hand at unifying its AI and analytics services with the launch of SageMaker Unified Studio last year but has yet to reach the level of simplicity that Microsoft’s IQ offerings promise.
When it comes to new AI analytics services from AWS, CIOs can expect more of the same, said David Linthicum, independent consultant and retired chief cloud strategy officer at Deloitte Consulting. “Realistically, they can expect AWS to keep integrating its existing services; the key test will be whether this shows up as less complexity and faster time-to-insight, not just new service names,”
Lack of cohesion in AI platform strategy
That complexity isn’t confined to analytics alone. The same lack of cohesion is now spilling over into AWS’s AI platform strategy, where the cloud giant risks ceding mindshare despite its compute advantage.
“SageMaker is still respected, but it no longer dominates the AI platform conversation. Open source frameworks like Ray, MLflow, and KubeRay are rapidly capturing developer mindshare because they offer flexibility and avoid lock in,” Fersht said.
This fragmentation is exactly what partners want AWS to fix by offering clearer, more opinionated MLOps paths, deeper integration between Bedrock and SageMaker, and ready-to-use patterns that help enterprises progress from building models to deploying real agents at scale.
More plug-and-play, less build-it-yourself
AWS’s tooling shortcomings don’t end there, said Fersht. The hyperscaler’s focus on providing the parts for agentic AI and leaving others to build with them make it harder for business users to consume its services.
“AWS is giving strong primitives, but competitors are shipping business-ready agents that sit closer to workflows and outcomes. Enterprises want both power and simplicity,” Fersht said.
Although there’s an assumption that enterprises are big enough to build things themselves, they want more plug-and-play than AWS imagines, Fersht said: “They do not want to engineer everything from scratch. They want reusable agent blueprints that map to sales, service, IT operations, and supply chain tasks.”
In fact, if AWS wants to compete with rivals to become the default agent platform for enterprises, it must hide complexity behind higher-level abstractions and simplify its agent stack, double down on workflow level agents, and give customers clear guidance on safe deployment, accountability, and ROI, he said.
Vibe coding disarray
Like other hyperscalers, AWS is aggressively experimenting in the vibe coding and agentic IDE space, where there’s no clear consensus on what developers actually want, according to Fersht.
“Everyone is experimenting because no one has cracked the next generation developer workflow. AWS is no different,” he said, adding that in some respects AWS has been more conservative than its rivals.
AWS is sure to be dealing some new innovations at AWS re:Invent in Las Vegas this week, but despite defining the cloud computing industry in 2006, it now finds itself, in many respects, playing catch-up.
