4 Things the B2B CMO Needs to Know About AI

Last week (Sept. 12), OpenAI introduced its new “o1” model series with enhanced reasoning capabilities.

But do the new reasoning capabilities of commercially available artificial intelligence (AI) systems give businesses today, particularly in the B2B space, a real reason to use them?

The answer — at least for CMOs and even CFOs — appears to be yes, despite the fact that the return on investment (ROI) of the still-novel technology remains challenging to measure.

As the B2B marketing landscape becomes increasingly digital, driven by shifting buyer preferences and heightened expectations for personalized experiences, B2B CMOs must navigate the evolving AI landscape with precision.

While AI offers substantial opportunities when deployed across four critical areas such as a personalization and predictive forecasting engine, or as a B2B customer analysis tool and automation tool, it can also introduce complexities.

Read more: The Crucial Role Payments Can Play in B2B Brand Building

Embracing AI as a Strategic Imperative for B2B CMOs

The integration of innovations like AI aims to bring greater efficiency to operations, even if it disrupts traditional practices.

To unlock AI’s potential, B2B CMOs must approach its implementation with a clear understanding of its capabilities and limitations. While AI can enhance marketing performance, it should complement — not replace — human creativity, intuition and relationship-building skills. By blending AI with their teams’ expertise, CMOs can create marketing strategies that are not only data-driven but also deeply human.

For example, AI excels at processing and interpreting large volumes of data, making it a critical tool for gaining deeper customer insights. In B2B marketing, understanding buyer behavior at a granular level — across various touchpoints and decision stages — can unlock competitive advantages. AI can help CMOs to analyze patterns in data that would otherwise go unnoticed, providing a clearer picture of what drives buyer actions.

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.

AI can help B2B CMOs uncover valuable insights into customer behavior, preferences and pain points by analyzing not just explicit data (e.g., purchase history, CRM data) but also implicit data, such as browsing patterns and engagement with marketing materials. AI can also analyze competitor data, providing CMOs with insights into market trends, gaps in service or emerging threats, helping businesses stay one step ahead.

The complexity of B2B purchase decisions — often involving multiple stakeholders over long sales cycles — makes personalization even more crucial. By using AI to automate and refine segmentation strategies, CMOs can ensure their marketing is aligned with individual decision-makers’ specific needs, improving conversion rates and shortening sales cycles.

Read more: Nine Things Payments Execs Need to Know for Their 2025 Business Plans

AI’s Role in Marketing Automation and Operational Efficiency

B2B CMOs are under constant pressure to do more with less, particularly in uncertain economic climates. AI-powered automation platforms can help by eliminating time-consuming manual processes, such as lead scoring, content distribution and reporting. This not only boosts productivity but also enhances consistency and accuracy in execution, driving operational efficiency while allowing human marketers to focus on high-value strategic activities.

AI can also optimize campaign performance in real time. With machine learning algorithms constantly analyzing data from live campaigns, AI can adjust bids, allocate budgets or refine messaging on the fly, maximizing the return on investment and ensuring that marketing efforts stay aligned with business objectives.

The integration of digital B2B payment systems with AI can also help provide a boost to both CMO and CFO responsibilities. In the June report “Getting Paid: Digital Payments for Improving Cash Flow and Customer Experience,” PYMNTS Intelligence revealed that 79% of firms want to receive digital payments, including wire, automated clearing house (ACH) and virtual cards, and 83% consider fully electronic payment processing to be important or very important.

Read more: The Power of Precision: Driving Revenue From B2B Customer Data

For example, by analyzing patterns in historical payments data, AI can forecast the likelihood of a prospect progressing through the sales funnel, enabling marketing teams to focus on high-potential leads. This enables CMOs to move from reactive to proactive strategies by forecasting future outcomes. This is particularly useful in account-based marketing (ABM), where understanding the likelihood of a prospect converting can optimize resource allocation and timing.

“AI has the potential to really move the needle for so much of the industry in terms of … 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.”

The enterprise AI marketplace is responding to the demand for business-centric solutions. Last week, Glean raised $260 million in a Series E funding round Tuesday (Sept. 10) to accelerate its artificial intelligence innovation, customer acquisition and global expansion of its Work AI platform for enterprises; while Gusto announced Wednesday (Sept. 11) that it will soon add an AI-powered assistant called Gus to the human resources (HR), payroll, benefits and compliance platform and products it offers for small business owners.

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