AI Assistant

AI assistants are becoming necessary tools for improving efficiency and customer interactions in today’s fast-paced business environment.

With numerous AI assistant products available, selecting the right one for your enterprise can be technical and difficult.

To help you make an informed decision, it’s crucial to ask potential providers the right questions.

Here are ten key questions to consider when evaluating AI assistant providers, ensuring you choose a solution that aligns with your business needs and goals.

These ten key points are shared by IBM Watsonx and are available at this URL. In this blog, we have explained that particular post in detail.

1). What’s Your Time to Value and Total Cost of Ownership?

Understanding the time to value means knowing how quickly you can expect to see benefits from the AI assistant after deployment.

The total cost of ownership includes all expenses, such as initial setup, ongoing maintenance, and additional charges for text-to-speech features.

Some platforms require significant developer effort, which can increase costs. To budget effectively, get a clear picture of all associated expenses.

2). Can You Provide Pre-Built, Flexible, and Custom Integrations?

Integrations are crucial for a smooth AI assistant experience. Ask how easily the AI assistant can be integrated into your existing systems, such as your website or IVR (Interactive Voice Response).

Flexibility in integrations allows you to combine the best tools available, making it easier to adapt the AI assistant to your specific needs.

3). Will We Be Able to Scale the AI Assistants Globally?

Knowing if the AI assistant can handle international and multilingual interactions is essential for businesses with a global presence.

Providers should have experience and references to demonstrate their capability to scale beyond a single region, ensuring consistent performance worldwide.

4). Can Your AI Assistants Meet Our Requirements for Governance?

Governance, risk, and compliance (GRC) are critical, especially for businesses handling sensitive data.

Ensure the AI models adhere to your industry’s GRC standards and that the provider offers IP indemnification, which protects your business from intellectual property disputes related to the AI technology.

5). How Accurate Is the Intent Understanding of Your AI Assistants?

Intent understanding refers to the AI’s ability to grasp what the user is trying to achieve.

High accuracy in this area means the AI can handle topic changes smoothly, suggest alternative options, recognise when human intervention is needed, and find relevant information in lengthy documents.

This ensures more efficient and effective user interactions.

6). Do You Provide One Centralized Solution for Easier Maintenance and Scaling?

A centralised solution means all functionalities, like search and voice, are integrated into a single platform.

This simplifies maintenance and scaling, reducing the need for multiple disjointed products and making it easier to manage and expand the AI assistant’s capabilities as your business grows.

7). How Hard Is It to Build Conversational AI Experiences for End Users?

Building conversational AI experiences easily is crucial, especially for business users needing more technical expertise.

As peer reviews indicate, look for platforms that offer user-friendly tools and minimal learning curves.

This ensures that creating and managing AI interactions is straightforward and efficient.

8). Is Your Conversational AI Platform Enterprise-Ready?

Enterprise needs differ significantly from personal use. Ensure the provider understands enterprise requirements, including robust authoring tools, lifecycle management, and maintenance.

This ensures the platform can support the complex demands of a large organisation.

9). Do You Have a Clear Roadmap for Future Productivity?

A clear roadmap shows the provider’s commitment to future development and innovation.

Ask if they are targeting use cases and product improvements that align with your business goals and offer a significant return on investment.

This will help you plan long-term and ensure the AI assistant will evolve to meet your needs.

10). How Efficient Are the AI Assistants?

Efficiency covers costs in data usage, GPU requirements, and CO2 emissions. Large, general-purpose models can be expensive and resource-intensive.

Custom, fit-for-purpose models tailored to your data can often deliver the same results more cost-effectively and sustainably.

Understanding these factors helps you choose a solution that balances performance with cost and environmental impact.

By asking these questions, you can better assess which AI assistant provider will meet your enterprise’s needs and deliver the best value for your investment. It will help you ultimately end with the best incorporation of generative AI into your business.

This blog’s insights and recommendations are based on information provided by IBM WatsonX, as shared on their LinkedIn page.

We at NexaQuanta, along with the expertise of IBM WatsonX, can help you better understand how GenAI could help you effectively respond to regulatory changes.

Use this link to join NexaQuanta’s webinar and explore how generative AI can empower your business to navigate regulatory changes effectively.

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