AWS’s Agentic AI Push: Too Late, Too Little, and a Sign of Larger Problems

Amazon Web Services (AWS) recently announced the formation of a dedicated group focused on “agentic AI,” framing it as the next big innovation for the cloud leader. The concept of agentic AI—autonomous systems capable of taking actions to achieve tasks without constant human input—has clear potential. AWS CEO Matt Garman went as far as to predict agentic AI as a multi-billion-dollar business opportunity for the company.

On paper, this sounds like a bold move, but in practice, it feels like a hollow one. Aside from the announcement itself and vague promises of innovation, there’s little evidence AWS has anything tangible to offer in this space right now. A few customer demos, like Alexa autonomously booking rides or navigating websites, lack sophistication and appear aimed more at consumers than enterprises. Unsurprisingly, many in the market see this as just another example of AWS trying to ride established trends rather than blazing its own trail forward.

Why AWS Is Too Late—and Too Generic

Over the years, AWS has built its reputation as a leader in cloud by breaking new ground, pioneering services like EC2 and S3 that transformed how enterprises manage infrastructure. But this latest move into agentic AI represents a sharp departure from that proactive innovation. Instead, it feels reactive—a rushed response to the industry’s shifting focus toward more advanced AI systems.

For enterprises, the announcement falls flat for several reasons:

• The Technology Gap: AWS offers no concrete enterprise-ready capabilities to back up its agentic AI claims, and no clear timeline for when those might be available. Meanwhile, enterprise customers are looking for immediate solutions to real business problems, not promises about future potential.
• Consumer-Centric Demos: The examples AWS showcased lack the enterprise-grade functionality or complexity needed to solve meaningful challenges for businesses. Autonomous shopping assistants or vehicle booking might impress a few curious onlookers but fail to address the operational needs of global enterprises or mission-critical workloads.
• Too Slow to Act: By the time AWS officially formed an agentic AI group, the concept had already gained significant traction elsewhere. Enterprises view AWS’s announcement as late to the party, making it harder for the cloud giant to regain momentum with skeptical buyers who increasingly expect bold, market-defining leadership.

For a company that once defined the future of digital transformation, AWS’s reliance on announcements without delivering enterprise-focused results signals a troubling shift. Enterprises seek visionaries who can guide them into uncharted territory—not a “fast follower” trying to catch up on trends already well underway.

Enterprise Skepticism Is Mounting

Beyond the specific challenges of agentic AI, AWS’s broader slowdown in innovation has left enterprises questioning its role as a growth partner. The public cloud was once seen as the ultimate destination for enterprise IT, but cracks in that story are starting to emerge. Enterprises are tired of vague promises and incremental improvements. They want transformative capabilities that solve complex problems today, not flashy but hollow narratives about tomorrow.

AWS’s pattern of “innovation-by-press-release” encapsulates why many enterprises are starting to explore other technology strategies altogether. These organizations realize that dependence on public cloud providers introduces limitations: unpredictable costs, reliance on massive, shared infrastructure, and the risk of stagnating technology.

As a result, enterprises are increasingly looking outside the traditional public cloud model. They are diversifying their technology strategies, balancing private cloud infrastructure with on-premises systems, co-location, or edge solutions. This allows them to create customized, more predictable environments tailored to workload-specific needs—all while reducing their reliance on slow-moving cloud providers like AWS.

The Takeaway for AWS

The formation of a new agentic AI group at AWS should have been an opportunity to assert the company’s leadership in enterprise innovation. Instead, it underscored a growing perception that AWS is no longer the visionary it once was. The announcement feels like a response to an industry trend rather than the spearheading of a new one—and enterprises are starting to notice.

Moving forward, AWS will need to rethink its approach if it wants to retain enterprise confidence. That means regaining its role as a leader, not a follower, and delivering concrete solutions far faster and with greater enterprise relevance. If AWS cannot address the growing frustration among its customers, more enterprises will continue to look for alternatives outside the confines of the public cloud model. For AWS, the stakes have never been higher, and the company’s future as a trusted innovation partner depends on how it chooses to respond.

Some AI tools used to edit this article.