AI Prompt Engineering Helps B2B Firms Find Needle in Data Haystack

B2B businesses are increasingly looking to artificial intelligence (AI) solutions in support of process excellence.

Across marketing, customer success, compliance, payments and beyond, AI innovations are reshaping traditional workflows.

Amid Google’s new upgrades on Tuesday (Sept. 24) to attract more businesses to its Gemini platform, enterprise organizations and smaller businesses are finding ways to create more precise, context-driven inputs for AI tools that will drive business growth.

Against that backdrop, the rise of AI prompt engineering for B2B operations is becoming crucial to unlocking the capabilities of AI in automating tasks, deriving insights and transforming how B2B companies interact with their data.

AI prompt engineering refers to the practice of crafting specific, context-driven inputs — or “prompts” — to elicit desired outputs from AI models. Unlike traditional programming, where exact instructions are needed to achieve results, prompt engineering focuses on how to frame questions or commands in ways that guide AI systems toward more meaningful and actionable outputs.

This is particularly important for large language models (LLMs), like OpenAI’s GPT, which have vast capabilities but need structured, precise guidance to deliver optimal outcomes. As AI systems from firms like Microsoft, Salesforce, Workday, Oracle and ServiceNow reportedly look to transition their AI copilots to AI agents, being capable of getting to the desired outcome is crucial for B2B success and driving competitive differentiation.

Read more: AI in Commerce: 5 Essential Use Cases for B2B Operations

AI Prompt Engineering: Revolutionizing B2B Interactions With Data

By learning how to communicate effectively with AI, businesses can enhance their data analysis and optimize workflows, turning AI from a complex, often opaque system into a practical business enabler.

In B2B environments, data is the lifeblood of decision-making, whether it’s forecasting demand, managing supply chains or crafting customer engagement strategies. AI prompt engineering enhances how companies interact with their data by allowing them to extract deeper insights more efficiently.

“AI has the potential to really move the needle for so much of the industry in terms of their ability to better understand what’s going on within their payments environments and the ability to be more proactive with their buyers or suppliers,” Nick Izquierdo, executive vice president of payments at Billtrust, told PYMNTS.  “And alongside that, the productivity AI brings is really driving more success satisfaction out of both sides of the equation.”

B2B firms often struggle with data overload, facing terabytes of structured and unstructured data from various sources. Without precise query mechanisms, even the most advanced AI models can produce outputs that are too broad or vague. By mastering the art of crafting prompts, businesses can ask the right questions and guide AI to provide answers that are laser-focused on the specific business problem, significantly reducing time spent on data sorting and irrelevant outputs.

“The moment you slice the world through the lens of historical transactional behavior, you can then leverage a predictive GenAI framework and say something about the likelihood of those future transactions,” Pecan CEO and Co-Founder Zohar Bronfman told PYMNTS. “It’s evolutionary in terms of how businesses can operate.”

For instance, a B2B logistics company can use prompt engineering to query its AI system about inventory bottlenecks during specific time periods, focusing on high-priority geographies. By framing the prompt to focus on time, location and SKU level, the company can get actionable insights quickly, helping them adjust operations in real-time.

Read more: AI for KYB Onboarding Helps B2B Partnerships Scale Securely

Driving Efficiency Through AI-Powered Automation

Efficiency is the backbone of B2B operations, where long, complex processes often stretch across multiple stakeholders, systems and even geographies. AI prompt engineering plays a pivotal role in streamlining these workflows by automating decision-making processes and enhancing the speed at which information is processed and acted upon.

“What I’m most excited about is the future of payments, how quickly it’s moving,” Eric Frankovic, general manager of corporate payments at WEX, told PYMNTS. “Understanding your supplier relationships, what’s best for you as a company, and what best supports your size and growth goals is crucial.”

For instance, procurement teams can automate vendor risk assessments by creating prompts that direct AI to analyze supplier performance data, compare it against historical benchmarks and assess geopolitical risks. This cuts down the manual effort required to process vast amounts of information, delivering actionable results in real-time.

Separately, in B2B marketing, businesses can design prompts that instruct the AI to not just analyze customer interaction data but to do so in the context of industry trends, competitive positioning and the company’s unique value proposition. This makes the insights richer and more aligned with the company’s broader business goals.

As the findings detailed in “CMOs Leaning on GenAI For Market Research, Even As ROI Dips,” the fifth edition of PYMNTS Intelligence’s 2024 CAIO Project, more than nine in 10 CMOs said they used GenAI for actions in the category of market research and insights.

Ultimately, prompt engineering offers businesses something invaluable: speed. In competitive B2B markets, the ability to move quickly is critical. Whether it’s responding to shifts in customer demand, adjusting supply chain strategies or rolling out new products, speed can make or break success. Prompt engineering ensures that businesses can get to outcomes faster, bypassing the trial-and-error phase that often accompanies new technology adoption.

And as PYMNTS covered last month, AI is no longer just the domain of large corporations with deep pockets and extensive tech teams. Small businesses are getting in on the action as well. Recent PYMNTS Intelligence data in the June report “SMBs Race to Critical Mass on AI Usage” found that 96% of small- to medium-sized businesses (SMBs) that have tried AI tools see it as an effective method to streamline tasks.

That said, the ways that Main Street SMBs can unlock growth through strategic applications of AI looks a little different from the approaches being taken by their larger enterprise counterparts.