Going beyond GenAI for RFPs, proposals, & bids

Bid and proposal teams sit at the epicenter of response management — they are the stewards of company knowledge and play a vital role in revenue generation. But bid and proposal teams can’t operate in a silo. 

That’s where SRM comes in. Strategic Response Management democratizes knowledge across an organization and streamlines the cross-functional collaboration necessary to share company information with prospects and ultimately secure partnerships.

Key trends from the 2024 State of Strategic Response Management Report

What are bid and proposal teams experiencing “on the ground?” What are industry leaders’ perspectives? 

Let’s take a look at some of the key trends in Strategic Response Management:

• 48% of company revenue, on average, is tied to RFPs, bids, tenders, and proposals
• 70% of respondents say revenue generated through bids, inquiries, and assessments has increased in the past year
• 90% say that bid and proposal teams are a direct and significant contributor to revenue
• 89% say that their organization is experimenting with AI, but leading organizations are going beyond GenAI for more than just writing

While the business impact of strategic response teams is evident, data from the report revealed that strategic response professionals are strained. There are many challenges facing proposal teams, including under-resourcing, tight deadlines, and an overwhelming volume of siloed and scattered information.

AI unlocks key efficiencies that can unburden strategic response teams. GenAI dramatically contributes to their efficiency when it comes to content production, but doesn’t solve for inefficiencies in other parts of the response process, like content and workflow management. 

Broadening the use of AI for maximum impact

We know that companies at the forefront of AI adoption are seeing increased revenue. Yet, The 2024 State of Strategic Response Management Report found that fewer than one-third of companies have formally deployed any AI technology in their bid, proposal, and capture processes. 

Nearly all respondents (96%) noted that strategic response processes require several key competencies, including:

• Aligning stakeholders
• Collaboration and organizational alignment
• A consistent voice and style
• Accuracy and compliance
• A single source of truth
• The ability to personalize responses
• The ability to track historical data
• Using key reports that measure the impact of responses
• Access to self-service automation

Robust SRM platforms go far beyond GenAI to address the end-to-end response process, going beyond text generation. This enables response teams to rapidly and efficiently assess every opportunity that comes in the door and create accurate and on-brand responses to any questionnaire that aligns with business goals.

GenAI in SRM

GenAI, made famous by chatbots such as ChatGPT and DALL-E, generates text, image, and other media types from human prompts. GenAI uses artificial intelligence to understand and respond to natural language. Some chatbots use GenAI technology. GenAI is trained on large language sets. Consumer-grade GenAI, such as ChatGPT, gets most of its training from the internet and customer data. 

GenAI is currently the top way organizations use AI technology and is just one of an arsenal of AI tools used in SRM processes. Using input from an organization’s content library, GenAI assists through the entire writing process, from generating to editing and refining. 

GenAI controversies

GenAI is not without its controversies and risks, which is particularly true with consumer-grade chatbots. According to the Responsive and APMP research, nearly three-fourths of organizations are concerned about potential privacy and IP risks, “hallucinations” (or fictional results), and risks from using content that’s not approved, compliant, or up-to-date.

Privacy 

Consumer-grade GenAI is trained on public-facing content like the internet and human interactions with the tool. 

Because public models are exposed to such large datasets, the possibilities for creative inspiration, problem-solving, and more are nearly limitless. However, consumer-grade models’ most significant strength is also its biggest weakness. 

Any human interaction, whether the data entered is sensitive or not, may be used in its training. If your company manufactures widgets, for example, your proprietary blueprints could end up on someone’s personal computer or, worse, a competitor’s. It’s no wonder that nearly three-fourths of companies have privacy concerns regarding consumer-grade chatbots. 

Depending on desired use cases, business-grade GenAI might initially be trained on public-facing content, but user interactions are not used for public training. All proprietary information is contained well within an organization’s virtual walls.

Hallucinations

Hallucinations are wrong answers that, at first glance, may seem correct. Neither consumer nor business GenAI is immune from hallucinations, which is just one of the reasons humans must remain in the loop. 

That’s not to say that consumer-grade and business-grade GenAI carry the same risks of hallucinations. 

Business-grade GenAI can still produce hallucinations, but they’re less common. Still, it could, for example, base its results on information from two years ago that matches all your criteria. So, all results need to be double-checked by humans.

Unapproved/out-of-date/non-compliant content

Using unapproved, out-of-date, or non-compliant content exposes organizations to legal and compliance risks, especially when the content is no longer accurate. 

Like hallucinations, business-grade GenAI is less likely to uncover risky results than consumer-grade. More advanced AI can identify quality content; however, the best way to ensure approved, up-to-date, and compliant content is to keep it out of your content library, which means having a well-established and maintained content governance system. 

For that, you’d have to go beyond GenAI.

Going beyond GenAI for proposals and bids

While GenAI enhances the SRM process with writing and translation, the sophisticated AI engine behind an SRM platform like Responsive automates the response process and amplifies potential use cases. 

Go beyond GenAI for:

• Content governance — 63% of successful organizations surveyed in the 2024 State of Strategic Response Management Report believe AI will impact SRM through its ability to automate or simplify content management by flagging and helping update ROT (redundant, outdated, or trivial) content
• Fast, quality responses — 56% of organizations anticipate that AI will impact SRM by being able to quickly and easily draft and optimize responses with smart recommendations and intelligent automation
• Risk mitigation — 55% believe that checking responses for accuracy and compliance will impact the future
• More personalized responses — 52% believe that AI’s ability to create responses that are specifically tailored based on customer context and relevant company advantages will impact the future of SRM
• Workflow management — 49% believe that automated workflow management will impact SRM in the future. It already sets up project timelines, tasks, and review cycles with minimal user input

The best AI-led SRM platforms already have each of the above capabilities. 

Will AI replace humans? 

When the conversation around AI first heated up last year, many bid and proposal professionals feared that the technology would supplant them. The Responsive and APMP study reveals that AI — while transformational — is not a threat to anyone’s employment.

40% of leaders and 30% of practitioners believe AI will help strategic response teams operate with fewer employees. Headcount reduction seems to not be a major part of the equation, perhaps because many feel that AI will help fill in the gaps left by a global talent shortage with no end in sight. 

47% of leaders and 80% of practitioners anticipate a better use of staff time. Of course, this includes taking a more strategic approach to each opportunity and generating higher-quality responses for higher win rates, revenue, and growth.

It’s clear from the sentiment surfaced in the research that most bid and proposal professionals no longer have fears surrounding job security. Instead, they’re excited that AI development will create an environment in which they can better thrive, delivering even more impact to the business.

AI strategies that yield results in Strategic Response Management

It’s worth noting once again that organizations experiencing revenue growth are 3X more likely to use an AI-powered SRM platform, according to the research.

As an example, Netsmart, a medical technology company, successfully implemented AI strategies with dramatic results. They now spend one-tenth the time they used to generate responses and submit 67% more proposals.

How did they do it? Andrew Mersman, Senior Director of Solution Consulting at Netsmart, described their strategy: