AI RFP software: Build or buy?


ai rfp software

A few decades ago, manual RFP response processes were the norm, with paper requests and proposals. Around the beginning of the century, RFPs turned digital, usually handled in spreadsheets, Word documents and PDFs.

As technology advances, so does the length and breadth of RFPs. There are two factors at play:

  1. B2B buyers are asking more questions than ever before, aiming to collect as much information as possible during the pre-purchase process to ensure they’re making the right decision.
  2. Artificial intelligence (AI) is transforming the response industry by enabling response professionals to generate more effective proposals faster. Both issuers and vendors now expect the speed and accuracy that comes from RFP automation.

While the market has only begun to talk about AI RFP software, it’s quickly becoming an operational necessity. Organizations that embrace innovative response technologies are already demonstrating competitive advantages over those that don’t. They are more efficient, more confident in the accuracy and quality of proposals, enjoy better employee experiences, and experience higher win rates over those who rely on manual processes.

Increasingly, the question is not whether to incorporate AI RFP software into response processes but whether to buy an existing platform or build one.

What we’ll cover

The new standard for Strategic Response Management

Manual processes and traditional RFP response tools are incredibly time-consuming and brimming with bottlenecks. Response professionals typically spend too much time chasing down SMEs and other stakeholders, relevant content is nearly impossible to find, and collaboration is challenging.

Manual and traditional processes are a lose-lose situation for nearly everyone:

  • Response employees become frustrated by not having the tools to help them paint the company in its best light.
  • SMEs are repeatedly pulled from their important obligations to answer questions they’ve answered numerous times.
  • Customers may receive disjointed, inaccurate or poorly written responses simply because responders lack the time and resources for excellence.
  • And critically, executive teams, investors and board members see poor ROI and very little data to help drive decisions.

Strategic Response Management (SRM) is among the world’s fastest-growing software categories because it addresses these response challenges. SRM technology centralizes company knowledge — like previous responses and Q&A pairs — and automates processes that enable sales and response teams to collaborate and respond quickly and accurately to even the most complex RFXs, security, due diligence and other questionnaires.

AI RFP software is becoming the new standard for SRM, with capabilities designed specifically to optimize the response process for RFPs, enhance the user experience and add intelligence to business decision-making.

To use baseball parlance, organizations that invest in SRM solutions begin the response process on third base, with up to 80 percent of the job finished automatically. In contrast, organizations that use manual or traditional RFP processes are still at bat.

How should an organization implement SRM? Should it buy an existing SaaS platform or build one for its exclusive use?

Build vs. buy: What to consider

Deciding whether to build or buy AI RFP software comes down to far more than just upfront costs. Carefully consider these factors.

Functionality

AI-led SRM platforms are robust and agile, with a slate of features that simplify any response process, from RFPs to any RFx or questionnaire. These include: multiple integrations, project management functionality, automated first drafts, collaboration tools, a highly searchable single source of truth for all company knowledge, advanced data analytics and more.

If your organization’s products or services are relatively straightforward and you have a highly collaborative workforce with an existing single source of truth, you might consider building. If you see many areas for improvement, you should consider purchasing a robust platform.

Long and short-term goals

Chances are your proposal teams are inundated with RFPs, so a short-term goal might be to simply stay above water. In that case, buying gives you the most immediate benefits. Going with an industry leader in AI RFP software also ensures that you’ll be ready for any emerging use case in the long term.

If you have highly specific use cases in the short term that you don’t anticipate evolving or expanding, building may be a good route.

Resource allocation

Presumably, one reason you’re considering adding AI RFP software to your existing tech stack is that your response teams are stretched to their limits, and you want to increase capacity without adding additional personnel. Additionally, developer roles are among the most difficult to fill and highest paid.

When building new software applications, both teams will have to be in the front seat: response professionals will have to consult on desired and required functionality, and developers will have to — well — develop the software.

Does your organization have the personpower to spare for the six to nine months it will take to build the software and months more to ramp up? If not, is outsourcing in your budget? Can you realistically reach your quarterly goals during that time with your existing response processes? Do you have the resources to maintain the software once it’s built?

As any developer knows, testing is frustrating and arduous, but also necessary. The more testing, the better. Pre-built software is tested not only internally but also by its entire user base. That’s generally not an option with custom-built platforms.

To be fair, every software, whether purchased or built, comes with a ramp-up period, but vendors should have resources to ease the transition.

Cost

Building a response platform from scratch will cost significantly more than purchasing one. However, by not paying for licensing models, the investment may pay off after a few years. Don’t forget, though, that you’ll continue to incur costs of updates, maintenance and training even after the platform is built.

ROI

Predicting ROI requires extensive research. Here are just a few of the costs and outcomes to consider:

  • What features do you need?
  • How much will it cost to build a platform?
  • How much will it cost to purchase a platform?
  • How much will an approved security system cost?
  • Do the SaaS models you’re considering meet your security requirements or is that an extra cost?
  • How many employee hours are currently spent on the tasks you hope to automate, and at what cost?
  • What is the implementation time?
  • Are you losing opportunities during the building and ramp-up time because of a sluggish response process?
  • How much time will be spent supporting and maintaining the software?
  • How much more revenue will you hope to generate?

One ROI factor that’s nearly impossible to predict is user adoption, which is all about training and employee experience. It should be noted that, in most cases, the total cost of ownership of custom-built software is much higher and it takes longer to achieve a net positive ROI.

The ROI of AI RFP software like Responsive is simpler to quantify than with custom-built software. Metrics such as user numbers, time spent on the platform, time searching for content, and other data are easily accessible. Your chosen vendor should be able to quantify ROI for you before you sign.

Scalability

As markets change, businesses and technologies must adapt. Additionally, company knowledge and other data increase exponentially and an SRM platform should be equipped to find and manage increased data.

“There were 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every two days.”

~ Eric Schmidt, Executive Chairman at Google

Build or buy with growth in mind. Response platforms should start with a strong architecture but allow for adding additional resources as needed. Keep these questions in mind:

  • How many users will the system support without affecting speed and functionality?
  • How easy is it to expand storage?
  • How easy will it be to add functionality?
  • How flexible is AI technology? Can it handle natural language prompts?
  • Is the code clean enough that it will be seamless for future developers?

Custom-built software requires that you consistently develop and adapt, which is expensive and time-consuming. Even tech powerhouses such as Microsoft, Google and Meta — all Responsive customers — chose to buy AI RFP software rather than build it.

Buy vs. build at-a-glance summary

Consideration Buy Build
Functionality Off-the-shelf software generally features a better range of functions but not necessarily built to your individual specifications. You can build around specific needs but it could require complicated design. It can be challenging to incorporate AI.
Long & short-term goals Built for a wide range of use cases. It can be difficult to anticipate future use cases but easier to customize for the short term.
Resource allocation Requires few upfront resources to onboard a new AI RFP software. The best vendors will provide support. Many cross-functional resources are required.
Cost Buying may seem costly in the short term but is far less expensive in the long term. Building will be more expensive in the short term. Plus, you’re likely to incur ongoing costs for support and maintenance.
ROI You should be able to speak to similar customers about their ROI. An established AI RFP software is likely to deliver ROI faster. ROI is difficult to predict until implementation and usually takes longer to achieve.
Scalability Varies between platforms. The best SRM platforms are powered by AI that supports scale. Depends on the software’s inherent flexibility. Company content grows almost exponentially and software should be able to expand and help manage redundant, obsolete and trivial content.

Who are the ideal candidates for building?

Organizations with unique business models and a limited number of response use cases may benefit from building a bespoke RFP software solution. However, they should have the resources to build with future-proofing in mind and to test, oversee user adoption, and maintain and update as needed.

Some organizations with strict security concerns might also gravitate toward building, but more on that in a moment.

Who are the ideal candidates for buying?

Organizations with an immediate or near-immediate need, those that have a limited upfront budget, and those with limited resources to design and implement software that is scalable and flexible enough for the long-term should look into buying.

Organizations with vast content libraries, a wide array of applications and other complex requirements should thoroughly assess vendors before making a final call. The best AI RFP software solutions providers will seamlessly integrate into your existing tech stack via a suite of integrations, allowing you to scale without friction.

And, of course, organizations that don’t want to expend resources to update and maintain software regularly should buy without hesitation.

What core capabilities should AI RFP software include?

Fluctuating economies and the changing security landscape are making buyers more discerning than ever, as demonstrated by questionnaires that are becoming increasingly complex and technical.

Yet, a lot is at stake. It’s estimated that $11 trillion of revenue is currently won each year through RFPs, and that number is expected to grow. Anyone reading this blog post knows the costs of lost opportunities from low-capacity manual and traditional response processes. Companies that adopt AI RFP software, on the other hand, enjoy a 16 percent higher win rate and 34 percent more revenue, according to a recent report.

The AI RFP software market is growing, but functionalities, agility, use cases, experience levels, customer support and security compliance vary — tremendously.

The elephant in the SRM room: AI

The biggest game-changer for Strategic Response Management (SRM) has been AI: both Generative AI (GenAI) and machine learning. GenAI produces first drafts using pre-approved content. Machine learning automates repetitive tasks, aids in project management and adds workflow intelligence, saving up to 80 percent over manual response times.

Regardless of whether you buy or build, a siloed tech stack can limit AI optimization. Many organizations struggle with:

  • A lack of integration and system communication
  • Inconsistent and isolated data
  • Inefficient resource utilization
  • Slower innovation and adaptability
  • Inconsistent security protocols

AI-powered SRM can bypass silos with an organization-wide single source of truth and feature native integrations that work with, instead of against, existing applications.

What to look for in an AI-enabled SRM platform

Here are just a few of the fundamental functions of an AI-enabled response management platform:

  • Response content drafting — AI can generate a first draft using pre-approved content from similar Q&A pairs, so content creators just have to edit and approve.
  • Content repository—An AI-powered response management platform should offer robust content management capabilities, including search functionality, customized tagging and review systems, version control and more. Ideally, it should serve as a single source of truth for the entire organization. Products like Responsive LookUp democratize knowledge and make content accessible from practically anywhere.
  • Collaboration tools —An RFP response can include a dozen or more stakeholders. AI powers tools built into RFP software such as real-time editing, smart recommendations, go/no-go decision-making, project management, automated task assignment and more. The best tools will even surface the right collaborators for a project, automatically.
  • Analytics—Make intelligence-driven decisions with AI-driven analytics and insights. Optimize your SRM with a slate of data, including win rates, response times, resource utilization and more.

The challenges of building your own RFP software

There are clearly some advantages to homegrown RFP response platforms. They are more customizable, you’ll have more control over updates, and they could be more cost-effective over time (if your needs are limited).

However, there are also disadvantages, along with some obstacles that might be tough to overcome. Initial costs, resources, and implementation time can be prohibitive, especially for organizations looking for speedy outcomes.

Building native AI applications requires training data — the more, the better. Companies that choose to build AI RFP software on their own will have limited datasets, not to mention that 84 percent of organizations have limited experience with AI. In fact, a recent Gartner study found that only 16 percent of organizations have more than five years of experience using AI. Tech employees are somewhat more likely to use AI at work than in other industries, but only 14 percent of tech employees regularly use it for work.

Most AI applications use large language models (LLMs) to augment native capabilities. Without proper guardrails in place, there can be security and privacy risks to the publicly-trained tools.

And, it can take several years to reach a net positive ROI and AI-powered software requires ongoing training, maintenance and other resources.

The advantages of purpose-built RFP software

When organizations purchase purpose-built software, they purchase more than a series of algorithms.

They receive:

  • Expertise — RFP platforms are designed and built by response professionals with ongoing input from hundreds of thousands of users.
  • Peace of mind — RFP software providers have all the resources they need to ensure a high-quality product. Plus, you won’t have to worry about managing ongoing maintenance.
  • Track record — Well-established RFP software solutions have thousands of customers and multiple case studies to serve as proof points.
  • Scale — The best AI RFP software platforms are tested to function under variable conditions. AI SRM solutions like Responsive support any response type and enable global collaboration between unlimited users.
  • Round-the-clock monitoring — Software providers have systems in place to identify and respond to issues as they arise.
  • ROI — AI RFP software providers deliver unmatched value so you win more in less time.

Responsive AI is built for Strategic Response Management

AI is proving to be the most useful tool in a response professional’s toolbox. However, it’s extremely complex and, when not responsibly designed, utilized and managed, it can be risky.

Responsive, the leader in SRM, is AI-powered and has been since our start in 2015. AI is part of our DNA.

Responsive AI transforms SRM into efficient, streamlined processes that drive better business outcomes. The key elements include:

  • Advanced capabilities — Responsive offers AI-powered smart content recommendations, SME recommendations, AI-generated first drafts, editing and fine-tuning, tone and style customization, translations, proactive project management, and the ability to handle high volumes of complex information requests at record speed.
  • An integrated experience — Responsive seamlessly integrates with many of the tools you use every day.
  • Risk and compliance management — Responsive always puts users and customers first. Our AI is developed and deployed with fairness, accountability, transparency and respect for privacy. We adhere to ISO 23053:2022 and all other relevant standards.
  • Ongoing support — We’re always here if you have questions about the Responsive platform or if you’d like some expert help with your response process.

Explore best-in-class AI RFP software in action

If you’re still debating whether to build or buy, we invite you to see how an AI-native SRM platform works, and how it can infuse your response process with expertise and efficiency.

See why over 2,000 companies, including more than 20 percent of the Fortune 100, rely on Responsive to help them achieve their business goals. Schedule a demo here.


Wendy Gittleson

Wendy has more than 10 years experience as a B2B and B2C copywriter. She developed a passion for writing about tech from living in the San Francisco Bay Area and working for a technology school. From there, she transitioned to writing about everything from SaaS to hardware and cloud migration. She is excited to be part of the wonderful team at Responsive and looks forward to playing her part in building the future. Connect with Wendy on LinkedIn.

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