AI in Enterprise - Why Care So Much About Inferencing?
Artificial intelligence has rapidly evolved from a futuristic concept to a present-day necessity, fundamentally reshaping businesses and governments across the spectrum. In financial services, AI drives real-time fraud prevention and custom-tailored financial guidance. In telecommunications, it optimizes network efficiency and personalizes service offerings. In retail, it's transforming inventory control and customer interactions – from forecasting demand to curating individual shopping experiences. In healthcare, AI enhances diagnostic capabilities and personalizes treatment plans.
Despite a significant 83% of companies claiming that using AI in their business strategies is a top priority, overall widespread adoption has remained relatively modest and flat since late 2024. According to Exploding Topics' April 2025 Statistics, current company usage of AI shows that only 33% have only started implementing limited AI use cases while 14% have tested proofs of concept with limited success, and only 7% are looking into it.
This suggests that while the intent and exploration are high, full-scale AI integration is still in its early stages for many. Even those with more mature implementations show that 21% have promising proofs of concept they are looking to scale, and only 25% report processes fully enabled by AI with widespread adoption. That low adoption has everything to do with the high cost and complexity of AI Inferencing.
WHAT'S HOLDING BUSINESS BACK?
The ability to deploy and operationalize trained artificial intelligence models is paramount to realizing their transformative potential across these industries. This crucial stage, known as AI inferencing, requires significant infrastructure and investment, making the AI inferencing market a key indicator of AI adoption and maturity. According to a Grand View Research report from early 2025:
- Global AI Inferencing Market: Projected to reach approximately USD 106.15 billion in 2025, highlighting the substantial investment in deploying and running AI models for real-world business applications.
- Global AI Training Dataset Market: Estimated to be around USD 3.2 billion in 2025, representing the investment in the foundational data necessary to develop and train AI models that are subsequently used for inferencing.
- Global Enterprise AI Market: Forecast to reach USD 28.54 billion in 2025, indicating the overall spending by businesses on AI software, platforms, and solutions that ultimately rely on AI inferencing hardware deliver value. Just as training a model to recognize different types of money is an upfront investment, the real return comes when that trained model can instantly identify a "greenback" as a US dollar bill in a live transaction.
What exactly is AI Inference, ANYWAY?
Imagine training an AI model to recognize different kinds of cars. You would feed it thousands of images of various makes and models – sedans, trucks, SUVs, sports cars, Fords, Toyotas, etc. – so it learns their distinct features.
AI inferencing is when a child, using an app connected to this trained AI, points their phone camera at a car driving down the street and the app instantly identifies it, saying "That's a silver Toyota Prius!" or "Look a red Ford F-150 truck!"
The child is using the trained AI model to infer the type of car from the image. This seemingly simple inference task, however, can require anywhere from 10x to 100x more computing and networking power compared to a single training operation, especially when dealing with complex models and real-time processing demands across a large user base.
the cpu bottleneck
Additionally, we have developed an AI-CPU that surpasses the performance constraints of traditional CPUs, which fall behind the rapid advancements of GPUs. They are akin to race cars hindered by the rugged paths traversed by early Ford Model-Ts. Our focus is on augmenting the capabilities of GPUs rather than competing with them.
We enhance GPUs instead of competing against them. Supported by our extensive network of open-source software collaborators, we elevate the performance of all AI technologies phases in building and installing AI:
- Training is the creation of new AI models through supercomputer-like data centers. They are typically capital, R&D, or product development expenses, with a distinct start and finish.
- Inference is the deployment of those trained AI models into cloud computing or on-premise data centers or Inference servers. For most businesses, they are a daily operating expense with a direct impact on your cost of sales and therefore, revenue and profit margins.
To put it simply, AI Training is about investing money, while AI Inferencing is about making money.
To capture the business ROI from your R&D or product development efforts, it's important to understand that AI Training and Inference each have their distinct business process and technical requirements. In fact, in the world of silicon and hardware, they are distinct markets.
"AI is two markets, training, and inference.
Inference is going to be 100 times bigger than training."
Chamath Palihapitiya, Investor & CEO of Social Capital
ACCELERATING AI ADOPTION WITH neureality
As NeuReality advances innovation while reducing cost barriers in AI inferencing, we enable financial services, life sciences, telecommunications, retail, education, and government institutions to deploy AI models and applications more efficiently, swiftly, and with less overhead—significantly surpassing the capabilities of current CPU-centric GPU solutions. Today's CPU-centric AI inference solutions are expensive, complex, and energy-intensive.
To achieve more cost-effective and energy-efficient AI inference, the NR1® chip consolidates the general-purpose CPU and NIC bottlenecks into a single unit but packs six times more processing power. The NR1 is compatible with all GPUs or AI accelerators, enhancing their utilization from less than 50% with traditional CPUs to nearly 100% with NR1. This optimization ensures that each expensive GPU is fully utilized as more are incorporated into an inference server to manage expanding and intricate AI workloads.
From a business perspective, this translates to achieving linear scalability without performance delays or drop-offs as AI workloads expand—whether processing medical images through computer vision or managing agentic AI in telecommunication call centers. The higher the price/performance ratio (AI token per dollar and watt), the more cost-effective your AI decisions and predictions become.
The conventional host CPU architecture, upon which all AI accelerators and GPUs rely today, faces challenges due to the vast scale and complexity of AI models and workloads. Technologies like generative AI, agentic AI, RAG, and Mixture of Experts (MOE) underscore the need for a more open and efficient AI architecture specifically designed for the AI era.
Additionally, we built the first true AI-CPU designed for inference orchestration. Our NR1® Chip surpasses the performance constraints of traditional CPUs, which fall behind the rapid advancements of GPUs, akin to race cars hindered by the rugged paths traversed by early Model-Ts.
We don't compete with GPUS - we enhance them. Supported by our extensive network of open-source software collaborators, we make AI shine.
Embracing the Future of AI Inference
With AI inference’s capability for producing real-time insights beyond human capabilities, NeuReality is implementing high-performance solutions that meet the real, unique needs of the enterprise, adhere to green AI standards by delivering higher AI tokens for lower-cost power., and achieve AI inference scale without breaking the bank.
NeuReality's enterprise-ready NR1® AI Inference Appliance comes pre-loaded with software, APIs, computer vision, generative AI, conversational AI, and more. Watch the demo from our CEO Moshe Tanach.
The first of its kind, this ready-to-go NR1® Appliance is up and running in under 30-60 minutes - either on-premise or through your cloud service provider. Rapid deployment allows your team to focus on immediate AI innovation, customer feedback, and amazing AI experiences with NP1.
This not only boosts the financial health of your company but can also give your customers the most efficient AI with redefined price/performance
Contact us today for a preview, demo or guided walkthrough of how our NR1 Appliance can help your business innovate with AI!
