Business leaders care about generative AI for their business because it offers a range of benefits that can help them achieve their goals and stay competitive in their industry, however, the sheer number of tools available on the market can be overwhelming.

With the prevalence of employees using ChatGPT, CEOs and COOs are looking for solutions to bring generative AI in house. In this article, we will explore some of the key factors businesses should consider when selecting a generative AI tool to bring in-house.

Choosing the wrong tool can not only be a waste of time and money, but it can also lead to subpar results and even damage a business's reputation.

Why Get an In-House Generative AI?

While there are many third-party generative AI tools available on the market, some companies may choose to bring the technology in-house.

• Use case discovery. Make the internal generative AI available generally and let employees discover effective usage.
• Control. Take greater control over the development and implementation of the tool and tailor it to specific needs.
• Customization. Adjust the tool's parameters and settings to generate output that meets specific requirements.
• Security. Implement security protocols and controls and mitigate the risk of leaking sensitive information when employees use public AI sites with internal information.
• Cost. An in-house tool can be less expensive than licensing fees or subscription costs.
• Data privacy. Maintain control over the data generated by the tool, supporting compliance with relevant data protection regulations.
• Competitive advantage. Develop unique capabilities and generate output that is tailored to their specific needs.

What Features Can Boost Functionality?

Here are some key features to consider:

• Tailored workflow. Specialized workflows should meet the business's specific requirements.
• Natural language processing. Written content output should be high-quality and accurate.
• Real-time generation. Tools that can generate output in real-time such as an assistant can be particularly useful for applications such as augmenting the customer service experience.
• Integration. Some tools integrate with the business's existing systems and infrastructure, such as content management systems or customer relationship management tools.
• Image and video generation. Look for features such as the ability to generate images or videos that meet the business's specific requirements.
• Machine learning. Tools that use machine learning algorithms can improve output over time.

What Helps Make AI Easy to Use?

A user-friendly tool with a clear interface and intuitive controls will encourage employees to quickly start using it effectively.

Interface. A clear and intuitive interface design that is easy to navigate with a simple, organized layout will help users quickly understand how to generate output.

Documentation and tutorials. Look for adequate documentation and tutorials such as manuals, videos, and online resources.

What Implementation Factors Are Key?

Some factors can make it easier to integrate generative AI tools into a business:

• Implementation timeframes. Look for a realistic estimated timeline.
• Compatibility. Look for a tool that can be seamlessly integrated into the business's workflow and processes.
• Integration. Check for APIs or other integration options that can help streamline the process of integrating with systems and infrastructure such as content management systems and customer relationship management tools.
• Vendor support. Consider the level of support provided by the tool's vendor, such as technical support or customer service.

What Are Some Cost Considerations?

The tool should be cost-effective and provide a good return on investment. Business leaders should consider the upfront costs of the tool, as well as ongoing costs such as maintenance and upgrades.

Consider whether the tool offers a free trial or demo period to help businesses evaluate its effectiveness before committing to a purchase.

Understand the ongoing costs and evaluate whether it requires regular upgrades or maintenance.

Look for pricing plans or options that can accommodate the business's changing needs.

What Are Some Fundamental Security Considerations?

• Data privacy. Evaluate data privacy and whether the tool complies with relevant data protection regulations, such as GDPR or CCPA.
• Encryption. The tool should use encryption to protect data in transit and at rest.
• Access controls. Businesses should be able to limit access to sensitive data or functionality to authorized users.
• Vulnerability management. Check for a program in place to identify and address potential security vulnerabilities.
• Compliance. Evaluate whether the tool complies with relevant security standards.
• Third-party security. Consider the security practices of any third-party vendors or partners that the tool relies on, such as cloud providers or data processors.
• Incident response. Evaluate how the tool responds to security breaches.

We’re Here to Help

To learn how an in-house generative AI tool can unlock your organization’s business potential, contact your Moss Adams professional.

Additional Resources

• Generative AI Services
• Technology Consulting Services