How Equipping Your Business Development Team With AI Enhances Your Pipeline

By now, if you operate a tech-savvy organization, you have likely already seen what artificial intelligence can do as a tool to manage the complexities of a supply chain. From flagging potential bottlenecks before they occur to optimizing route logistics to evaluating supplier risk, AI is proving its value on the supply side of the business.

But let’s not overlook the impact AI can have on a key supply-chain driver within your organization: the new business and sales pipeline.

Ultimately, you want a robust, bustling supply chain, because that suggests your business development team is doing its job on the front end by filling your pipeline with new deals, contracts, orders, project work, etc. It’s here in the business development area of an organization where AI in its various forms—task-driven agents, generative AI-powered assistants, machine learning, and natural language processing, to name a few—can make a real difference, both quantitatively and qualitatively, helping companies land more of the kinds of new business they desire, while also helping them identify and address risks that directly affect the supply chain.

Just as with managing a supply chain, intelligent capabilities can help an organization perform key business development and sales pipeline-related activities and workflows more efficiently, with more precision and less guesswork. That, in turn, provides a real competitive advantage in vying for new business—an edge that can translate into new revenue and greater profit margin, without increasing employee headcount.

Survey Says: More Companies Today Are Utilizing and Benefiting From AI

According to the results of our 2025 AEC Inspire Report, an annual benchmarking report covering the architecture, engineering and construction industries, technology-mature companies (including those using AI in their operations) “win more bids, deliver more projects on time, accelerate cash flow, and more frequently report positive indicators of organizational growth and profitability” compared to their less tech-focused peers. The edge for tech-mature firms is especially stark in proposal win rate, where they outperform less tech-focused firms by 19%.

More than half—55%—of the 300 companies surveyed report using AI in some capacity. Another 28% are intrigued by AI but not using it, while 16% have yet to employ AI at all. We expect the universe of non-AI-users to shrink quickly as more companies recognize the competitive value it can provide—and the risk they take in not exploring it.

Among the companies we surveyed, the most common use cases for AI come in the areas of business development and IT. Rather than viewing AI as a tool to replace people, they see it primarily as a workforce enhancer. Two-thirds of respondents expect AI to help employees work faster, and just over half believe it will enhance employees’ performance.

One important AI-related red flag emerged from our findings: among the companies that use AI, two-thirds lack clear policies or procedures for its governance, leaving them exposed to risks related to data stewardship, accuracy, security, and ethical considerations. This is an area where AI-enabled companies clearly need to take steps to protect themselves from the risks associated with AI use.

Meanwhile, findings from a recent IDC study commissioned by Microsoft suggest that well-placed AI investments can provide a strong return on investment. For every $1 a company invests in generative AI, the ROI is 3.7x, and organizations are realizing value within 13 months. More than 40% of respondents said productivity-related AI use cases provide the greatest ROI.

What kinds of AI capabilities on the business development and sales pipeline side of the business are apt to provide a strong ROI? Let’s look at a handful that are proving their value.

AI Tools Can Serve as an Organization’s Eyes and Ears in the Marketplace

Ever had that sinking feeling your organization is missing out on solid new business opportunities, like when your first time hearing about a particular opportunity is when one of your competitors announces they won the contract? A lack of strong, comprehensive market intelligence capabilities that scour the landscape for new business opportunities (RFPs, open bid solicitations, etc.) can create troublesome blind spots for an organization, putting them at a decided competitive disadvantage.

A new generation of AI-driven market intelligence tools can eliminate those blind spots and keep companies informed of new business opportunities—and not just any opportunities, but ones that track to an organization’s specific, predetermined parameters.

These market intelligence AI tools can serve as an organization’s eyes and ears in the marketplace, taking into consideration parameters like the type of work and customer desired, geographic region, contract length and more, then providing a steady stream of attractive opportunities that land in the company’s sweet spot, with enough lead time to act upon them. These could be opportunities that the company might otherwise have overlooked, and that their competitors could well miss.

Versatile technology that it is, AI can help set those search parameters, then assist in evaluating opportunities once they’ve been identified. With the ability to gather and digest huge amounts of data from internal and external sources, AI-powered analytics can put a fine point on who a company’s ideal customers are from a profitability standpoint, for example, as well as the types of contracts that have been most profitable and the customers that have yielded the most repeat business. That’s valuable insight that can inform the search parameters a company provides to its AI market intelligence tools.

Once opportunities are in hand, the emphasis shifts to being target-smart. Intelligent analytics can create a decision (or compliance) matrix that helps organizational leaders evaluate and prioritize specific pursuits by zeroing in on the most winnable, profitable, and desirable opportunities.

AI can identify the specific requirements within a solicitation, then map back to your organization’s ability to meet each of those requirements. So ultimately, instead of relying on gut instinct alone, decision-makers now have data to inform their go/no-go calls. And as a result, instead of wasting time and resources pursuing work that isn’t in your wheelhouse, you’re filling the pipeline with more of the kinds of business you covet.

Close More Deals with AI-Powered Proposals

With a clear picture of which opportunities to pursue, next comes the labor-intensive work of formalizing those pursuits with the creation of a bid, offer, or proposal. This is an area where proposal AI tools can take on much of the heavy lifting, freeing your people to focus on the parts of a bid or proposal where a human touch is particularly important.

AI capabilities are really coming into their own in terms of their ability to handle tasks like gathering, verifying, standardizing, organizing, and smoothing data and content for a bid or proposal. It can review and interpret the requirements of an RFP, some of which can be highly complex and esoteric, and even explain in plain language what certain requirements mean. Instead of your business development teams spending long hours sifting through large volumes of data and documentation to identify relevant information for a bid or proposal, verifying data accuracy, or trying to make sense of complex contractual compliance language, they can hand those tasks over to AI.

Not only can AI cull, organize, and verify appropriate information from various internal and external sources (repurposed info from past proposals, for example, or third-party market research), it also can turn all that information into a coherent whole by employing natural language processing to generate content. It can then flow that content into automated proposal templates to create a first draft that’s 60 to 70% complete. That means business development teams won’t have to start from scratch with each new bid or proposal.

The result can be game-changing for a business in terms of the quality of proposals and bids it produces and its overall proposal-generation capacity. Capabilities like these can cut average RFP time-to-draft by 70% and slice potentially six-figure proposal-generation costs in half, while increasing a firm’s overall proposal capacity 15 to 20%—without increasing head count or compromising win rate.

More Business Development Use Cases for AI

The potential business development use cases for AI that connect back to the supply chain are numerous and growing. For example:

• By applying intelligent analytics to their pipeline and current contract, order, or project backlog, firms can identify any at-risk business in the pipeline. This, in turn, will inform decisions about sourcing, production, inventory, and the like on the supply chain side.
• During the process of evaluating vendor procurement options for a proposal or bid, AI can help identify vendors that offer more favorable terms and/or present a lower supplier risk, which can bolster the appeal of that proposal or bid.

These are yet more reasons why an organization should consider looking for opportunities to integrate AI beyond supply chain management.

About the Author

Matt Moddelmog

Matt Moddelmog is senior vice president of product management at Unanet, a software company that provides enterprise resource planning, and customer relationship management solutions for organizations in the government contracting, architecture, engineering, construction and professional services industries.

Connect with me on LinkedIn, Facebook, X and Instagram.