WekaIO released results from "The
State of AI and Analytics Infrastructure 2021" study, which queried
technology professionals about their current AI and analytics
strategies.
The
study surveyed over 500 participants across IT, data, and engineering
functions about their IT architectures, frameworks, databases, spending,
challenges, and more. Participants included individuals from North
America, Europe, Asia Pacific, and the Middle East, with respondents
from various industries such as healthcare, research, financial services, and government.
Among the key findings were:
- 86%
of respondents have at least one AI initiative. Most companies tend to
have 2-3 initiatives, while a few even had as many as 5 initiatives.
- Use
cases vary significantly by vertical, but the most cited initiatives
were recommender engines, scientific visualization, and image
recognition.
- The
approaches to AI vary, but research and government tend to build their
own models that are customized to their needs, while commercial
enterprises tend to use ready-to-consume models to gain a time-to-market
advantage.
- In general, 50% of the data used is self-generated, but other sources contribute.
- While no respondents stated that they plan to be cloud-only,
most expect a significant and increasing portion of their workloads to
be in the cloud. Privacy concerns and the complexity of extending
workloads to the cloud are the main headwinds toward additional cloud
adoption.
- Over half of the respondents are already using GPUs, and adoption of GPUs is especially high in the Automotive segment.
- The
most significant headwind to the adoption of AI initiatives is the lack
of data scientists, followed closely by a lack of budget and
infrastructure to perform the AI.
"In
a rapidly changing world where AI and analytics continue to make
headway into how organizations source, manage and store massive amounts
of data, we sought to take a snapshot of real-world uses to help develop
strategies that can make a difference," said Ken Grohe, president and
CRO at WekaIO. "The survey revealed that the biggest headwind to
successful AI initiatives are too few data scientists and insufficient
technology infrastructure, such as cloud adoption. Many of our customers
use Weka to burst to the cloud for cost-effective, on-demand capacity
or compute resources. The Weka File System (WekaFS) can
extend to the cloud seamlessly, which enables data mobility while
eliminating data silos. So, whether your data is on-premises or in the
cloud, your applications have access to all your data in a single,
unified namespace. We hope the survey will be used by enterprises to see
if their AI infrastructure approach is delivering the simplicity, speed, and scale they need."
Based
on the study's results, experts at Weka suggest implementing AI
initiatives sooner rather than later. To do so, companies should
construct a plan for managing their data well ahead of their actual need
to use it. Enterprises should also keep their AI investments well
documented in order to measure their ROI or to compare whether they are
spending too little or too much on their AI initiatives.
One way to address AI and analytics infrastructure needs is by deploying Weka's Limitless Data Platform, which is built on the shareable, scalable, and distributed file storage system WekaFS.
Designed to help future-ready clients' data centers and enable digital
transformation, the breakthrough WekaFS solution was architected to
leverage the performance benefits of flash, high-speed networking, and
compute acceleration technologies (like GPUs) whether the data resides
on-premises, in the public cloud, or as a hybrid model. WekaFS stands
out as a leading solution because it gives clients the leverage to get
more value out of their compute resources, providing a full
enterprise-grade solution with advanced security and full cloud
integration.
Those
interested in reading the full results of the study, including topics
such as cloud initiatives, use of CPUs and GPUs, and impact of Covid-19
can register to download a copy at https://www.weka.io/report.