5 Essential Use Cases for B2B Operations

May 24, 2024

34 4 minutes read

Untitled design6 — AI artificial intelligence b2b operations.png

It’s getting harder and harder to spell innovation without AI (artificial intelligence).

And with the news Wednesday (May 22) that Zilliant is integrating generative AI across its pricing lifecycle management solutions, leveraging AI across B2B operations to enhance efficiency, accuracy and strategic decision-making is at the top of the agenda for many businesses.

That’s because, from payment orchestration and transaction security to credit underwriting and invoice financing, supply chain management, demand forecasting, and even B2B communications and marketing, AI — when responsibly and strategically deployed — is reshaping the operational landscape.

As AI continues to evolve, its integration into B2B payments and operations is not just beneficial but increasingly becoming essential.

Companies that embrace AI-driven solutions can potentially find themselves at an advantage relative to peers that continue relying on legacy systems, unlocking enhanced capabilities that drive growth and differentiation.

Still, implementing AI into B2B workflows is not as easy as 1, 2, 3. Successful integration depends on robust compliance and governance frameworks to ensure data security and objective outputs, as well as employee upskilling.

AI: The Silent Partner Revolutionizing B2B Operations

In a competitive landscape, AI is increasingly shaping up to be the silent partner that can transform challenges into opportunities and set new standards for excellence in B2B operations.

“There are three themes [around B2B payment innovation] we’re seeing: payment velocity, tooling and the role of artificial intelligence (AI),” Nick Izquierdo, executive vice president of payments at Billtrust, told PYMNTS.

“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,” he said. “And alongside that, the productivity AI brings is really driving more success satisfaction out of both sides of the equation.”

The payment process in B2B transactions is often fraught with complexity, involving multiple payment methods, currencies and regulatory requirements. AI-driven payment orchestration platforms can help streamline this process, ensuring seamless and efficient transactions. These platforms utilize machine learning algorithms to optimize routing paths, reduce transaction costs and mitigate the risk of payment failures.

As PYMNTS reported in April, recent advancements in deep learning and computer vision have made invoice processing more automatable. That’s according to Krishna Janakiraman, head of engineering at Ottimate, who spoke to PYMNTS in an interview posted April 5 about how AI can enrich AP processes.

Separately, AI significantly bolsters transaction security. Advanced algorithms analyze transaction patterns in real-time, identifying anomalies and potential fraud with remarkable accuracy. This proactive approach not only enhances security but also fosters trust among business partners, a crucial element in B2B relationships.

In fact, PYMNTS Intelligence found that over half (52%) of financial institutions plan to lean on AI solutions to combat fraud. And just last month (April), Mastercard debuted “Scam Protect,” a product suite combating the use of AI to scam consumers; while earlier this month, Visa launched its own AI-powered solution designed to help issuers combat enumeration attacks.

In the realm of credit underwriting and invoice financing, AI also offers transformative potential. Traditional underwriting processes, often reliant on static data and manual reviews, are time-consuming and prone to errors.

AI, however, leverages alternative and dynamic data from multiple sources, including financial statements, transaction histories and other activity, to assess creditworthiness with greater precision and make faster decisions in real-time, enabling improved access to financing for businesses.

Similarly, in invoice financing, AI can predict payment behaviors and assess the likelihood of invoice repayment, allowing financial institutions to offer more competitive rates and terms.

Streamlining B2B Operations by Removing Historical Frictions

Perhaps the most profound impact of AI in B2B operations is in strategic decision-making. AI systems, equipped with advanced analytics, provide executives with actionable insights drawn from vast datasets. These insights can uncover hidden patterns, forecast future trends and offer recommendations, empowering leaders to make informed decisions swiftly.

“The ChatGPT light bulb went off in everybody’s head, and it brought artificial intelligence and state-of-the-art deep learning into the public discourse,” Andy Hock, senior vice president of product and strategy at Cerebras, told PYMNTS.

“And from an enterprise standpoint, a light bulb went off in the heads of many Fortune 1000 CIOs and CTOs, too,” Hock added. “These generative models do things like simulate time series data. They can classify the languages and documents for applications, say, in finance and legal. They can also be used in broad domains to do things like help researchers develop new pharmaceutical therapies or better understand electronic health records and predict health outcomes from particular treatments.”

AI also enhances supply chain visibility, tracking shipments in real-time and predicting potential disruptions. This proactive approach allows businesses to mitigate risks, ensure timely deliveries and maintain customer satisfaction.

And of course, in marketing and outreach, AI enables hyper-targeted campaigns by analyzing vast amounts of data to identify trends and preferences. This level of personalization not only improves engagement rates but also helps drive better ROI for marketing efforts.

For all PYMNTS B2B coverage, subscribe to the daily B2B Newsletter.