If you’re responsible for procuring software for your team or organization, you’re probably familiar with the term “enterprise-grade technology.” Many B2B SaaS vendors likely tout their enterprise-grade solutions, enterprise-grade applications, or other enterprise-grade benefits. We know, that’s already a lot of “enterprise-grade” mentions and we’re just in the first paragraph. But what does enterprise-grade really mean? Why is it so important for generative AI technology in particular? And what differentiates enterprise-grade technology from other free applications available? In this article, we’re going beyond the buzzword to explain why investing in an organization-wide AI solution is critical for success.

Why Even Consider Enterprise-Grade AI? 

Large organizations often require specific software that integrates into their existing infrastructure, scales to support their entire workforce, and meets their high bar for security to protect their data, people, and brand. 

Enterprise-grade technology has never been more important than it is today, with the rise of artificial intelligence (AI) technologies in the workplace. Enterprise organizations are increasingly adopting generative AI solutions to enhance communication, optimize workflows, and increase productivity. According to the 2024 Work Trend Index Annual Report, the “use of generative AI has nearly doubled in the last six months, with 75% of global knowledge workers using it.” But the reality is that many of your employees are likely using AI technology that hasn’t been properly vetted and produced by your IT team. And that’s a problem. There is a crucial distinction between relying on unsecured, public AI tools and investing in enterprise-grade generative AI. 

For enterprises dealing with sensitive data, intellectual property, and other private information, choosing a secure, reliable, scalable, and robust AI solution is essential. Additionally, enterprise-grade AI should be the foundation of any organization’s strategy to drive company-wide efficiency and effectiveness. If the goal of AI is to make every employee more productive, then enterprise-grade AI compounds those gains across the enterprise. 

Enterprise-Grade AI Differentiator #1: Protection of Intellectual Property and Data Privacy

According to the 2024 State of Business Communication report, some of the primary concerns that business leaders have about generative AI are protecting their company’s security, privacy, and intellectual property. Utilizing unsecured, publicly available tools, like the free version of OpenAI’s ChatGPT, whose generative AI models aren’t tailored to enterprise-level security standards, can lead to breaches of sensitive enterprise data and other compliance risks. Investing in enterprise-grade AI is one way to alleviate these concerns. 

Enterprise AI vendors have robust security protocols and ensure that companies that use their large language models (LLMs) retain full ownership of their training data and generated content. This is critical for companies in industries that handle proprietary and sensitive information, such as healthcare, legal and financial services, or governmental agencies. It’s also equally important for any company that handles customer data, as maintaining trust is vital for all businesses. 

At Grammarly, one of our core principles of responsible AI is preserving the privacy and security of all customers. This means that we go above and beyond to ensure compliance with enterprise-grade regulations and security requirements, safeguard intellectual property, and fine-tune our models on datasets that are safe, fair, unbiased, and secure. Many other enterprise AI companies, including Microsoft Azure, also have robust responsible AI initiatives that ensure data privacy and security are maintained at the highest level. While evaluating enterprise AI vendors, be sure to ask about the details of their responsible AI programs and how they handle your data and intellectual property. 

Enterprise-Grade AI Differentiator #2: Access to High-Performance, Tailored AI Models

When it comes to enterprise-level operations, high-performance generative AI models are essential. Enterprise-grade AI impacts the full organization, not just one single person or one single use case, so it must be able to handle many, tailored use cases and large amounts of data and requests. Enterprise AI offers higher levels of operational efficiency for businesses by providing customizability and scalability capabilities that aren’t available in open AI use tools. 

• Customizability: From conversational AI chatbots to document and meeting summarization, tailored solutions are key to optimizing workflows. Enterprise-grade AI allows for fine-tuning on proprietary data, ensuring highly relevant and accurate outputs that are tailored to specific business use cases. This leads to superior performance, greater accuracy, and more reliable outputs, as opposed to relying on generic AI systems that lack customizability.
• Scalability: Enterprise AI platforms are designed to handle the processing of vast amounts of data and can scale seamlessly as your business grows. These systems also support high-volume use, enabling consistent performance for your entire workforce. Scalable AI models can efficiently manage high volumes of simultaneous tasks, so you never have to worry about system slowdowns.

Using unsecured AI tools may save initial costs, but they can fall short in terms of large-scale enterprise needs. Unsecured AI systems may also expose businesses to performance bottlenecks, limited use cases, or the inability to scale AI models to meet growing needs. In contrast, enterprise-grade AI platforms enable companies to fine-tune foundation models on specific datasets, ensuring the system’s outputs are aligned with the company’s goals. These platforms also provide in-depth support for metrics tracking, enabling businesses to measure the success and impact of AI implementation on operational efficiency.

Enterprise-Grade AI Differentiator #3: Integration Capabilities Across Your Enterprise Tech Stack

Another key differentiator between one-off AI solutions and enterprise-grade technology is their integration capabilities. One-off solutions require employees to break their existing workflows to use AI functionality for even the most simple tasks. Enterprise-grade generative AI, however, is equipped to enhance, not compete with, the capabilities of your existing technology. 

Generative AI applications that can be easily integrated into existing enterprise systems and data ecosystems help to streamline tasks, enhance decision-making, improve communication, and automate routine, time-consuming processes. When your enterprise AI works with the rest of your tech stack, it improves the ROI across that entire tech stack because your team is more efficient using every tool and more productive across established workflows.

You want to look for an enterprise-grade generative AI tool that not only meets your customizability requirements and can scale with your business but also easily integrates with your existing tech stack. With Grammarly, you get strategic AI communication assistance across over 500,000 apps and websites—more than any other AI writing partner—so you see the benefits span across every tool you’ve invested in.

Enterprise-Grade AI Differentiator #4: Control Over AI Models, Use, and Updates

The final significant differentiator that you get from investing in enterprise-grade AI is the ability to maintain control over the lifecycle of the AI systems in place. Unsecured AI tools often leave businesses vulnerable to risks related to unpredictable updates, lack of support, or changes to the platform. Enterprise-grade AI, on the other hand, gives enterprises more control. This can include control over how data is handled and stored, how and where employees can use the AI applications, and how the AI models are upgraded and maintained.

Moreover, enterprise-grade solutions often come with responsible AI guidelines and practices that are critical in ensuring sustainable AI operations. These tools ensure proper validation and fine-tuning, which align the AI with ethical standards, including reducing biases in training data and ensuring the long-term sustainability of AI-driven operations.

By maintaining control over the AI lifecycle, enterprises can ensure that their AI solutions remain adaptable and secure as their business evolves, something that is hard to guarantee with unsecured AI systems.

Grammarly offers customizable admin roles to control deployment and settings across an organization, allowing for bespoke permissions to satisfy the needs of individual teams, for example, by configuring specific domain or application blocklists based on a person’s job function. With bring your own key (BYOK), we’re giving enterprises control over their data encryption keys—offering additional assurance and oversight into how their data is stored—by enabling them to encrypt application-level data at rest.  

Achieving Enterprise-Wide Success With AI

Investing in enterprise-grade generative AI is not just about gaining access to the latest AI technology—it’s about ensuring that your organization can operate securely, efficiently, and effectively in the long term. Unsecured AI tools may offer quick fixes, but they come with risks related to data security, performance limitations, and lack of control. By choosing enterprise AI platforms, businesses can benefit from tailored solutions that are scalable, secure, and aligned with industry-specific needs.

With Grammarly, you get AI that stays in your control. Grammarly’s enterprise offering provides upgraded security features and flexible management options that allow you to rest easy knowing you have the most robust enterprise security and control features of any AI communication assistance company.

One company, Databricks, saw a 1,994% ROI and $1.4M in savings from rolling out Grammarly across its entire enterprise, including the marketing, sales, support, IT, finance, and engineering departments. All groups saw productivity and writing-quality improvements from Grammarly’s AI, in addition to revised training services, accelerated employee onboarding, and the upskilling of employees.