PolyAI named to Forbes AI 50 2023 list
⚠️ Unsupported Browser

Your browser is not supported.

The latest version of Safari, Chrome, Firefox, Internet Explorer or Microsoft Edge is required to use this website.

Click the button below to update and we look forward to seeing you soon.

Update now

Should you use an RFP when buying conversational AI?

Image of Tom Haynes
Tom Haynes
27 Apr 2023 - 5 minutes read

At PolyAI, we have encountered numerous companies that adopt the RFP process to find a specialist partner to help them create an effective customer-led voice assistant. But is going to RFP the best way to buy?

In this blog, we’ll look at why RFPs can be ineffective in finding the best conversational AI partner to solve your business problems.

Discovery is restricted

If you’re looking to deploy a conversational AI solution, there’s a high chance you want to streamline your contact center operations.

You know your business better than anyone, where processes could be more efficient and the outcomes you want to achieve.

However, conversational AI is complex. You’ll need to understand how these technologies integrate into your operations and why one technology can drive more value to your business than another.

Despite your best efforts, the structured format of an RFP document can limit your ability to communicate your specific requirements and business needs effectively.

Instead, understanding conversational AI’s place in your organization is achieved through thorough research and detailed conversations with potential vendors.

Conversational AI projects require a high degree of collaboration and customization. That’s why it is essential to use the sales process to work with vendors, ask questions, share ideas, and understand how the technology will drive better outcomes specific to your business needs.

Don’t just fill out forms – engage with your potential partners to ensure they can add value to your business.

They are time and resource intensive

Issuing and reviewing an RFP is a significant investment of time, money, and effort for your business. It can be challenging, with multiple departments and stakeholders required to issue the RFP.

Coordinating the process usually takes months. Competing priorities and differing opinions of what is required of the technology can cause roadblocks due to multiple rounds of feedback and revisions.

With a unified view across your business, technical and product requirements can become clear. Lack of alignment increases the time to value, and your team’s ability to gain valuable insights into customer behavior, identify skill gaps, and improve processes is delayed.

After the RFP (continuous development)

The RFP process requires organizations to outline the entirety of their conversational AI project upfront.

The drawback of this approach is that during the deployment process, conversational technologies, like voice assistants, will inevitably require ongoing changes.

When changes happen, an RFP is used as a reference point. If functionality or services fall out of the agreed scope, it can lead to delays.

Responding to these changes requires a flexible approach where you and your chosen vendor work in partnership to adapt.

It is essential to be aligned on what ongoing services your partner will deliver to avoid surprise costs after deployment, such as managing the significant amount of data generated as a result of deployment.


While an RFP can be a valuable tool, it may not be necessary or effective when looking for a conversational AI partner.

A more collaborative and open approach to this rapidly evolving and specialized technology can be more effective.

All is not lost if your organization requires you to carry out the RFP process. We’ve got you covered with five key areas you need to consider, including the questions you should be asking to get the most out of the process.

Request a Demo


Conversational AI for Business | April 2023

Five tips for writing an RFP for conversational AI for voice

Conversational AI for Business | February 2023

Five mistakes companies make when deploying conversational AI – and how to...