A recent global market survey by analytics firm SAS and Coleman Park found that while 9% of organizations plan to invest in generative AI by 2025, a staggering 90% of CMOs admit they do not fully understand the technology or its potential impact on business processes. This knowledge gap highlights a significant concern amid the ongoing AI hype.
However, some companies are charting a different course with AI.
The Nature Conservancy, an environmental nonprofit, and SAS are demonstrating practical, revenue-generating applications of gen AI. These include branding, lead scoring, and tailoring customer journeys—strategies highlighted during discussions at ADWEEK’s Brandweek event in Phoenix, Ariz.
“There’s a general AI washing that’s happening right now,” said Jennifer Chase, evp, chief marketing officer, SAS. “There’s so much hype around it, and we owe it to our businesses and, frankly, society to deepen our knowledge around generative AI.”
The Nature Conservancy is looking to scale its environmental efforts, eyeing ambitious goals like preserving land twice the size of India and conserving 10% of the world’s oceans, and gen AI is helping it get there, according to the organization.
The technology has helped the nonprofit optimize its marketing fundraising decisions, such as which of its lapsed owners it should reach out to while crafting digestible messaging from scientific papers.
Though many environmental nonprofits face declining fundraising, the organization is bucking the trend with its new strategies—growing its revenue by 8% annually, according to its director, strategic analytics, John Blackwell. In contrast, peers in the sector have experienced an 8% drop in donations year over year.
“The organizations that were similar to us in fundraising about five years ago, in many cases, we’re raising about twice as much as they are today,” said Blackwell.
The Nature Conservancy has also begun using synthetic data to supplement its limited pool of high-dollar donors, allowing it to build predictive models that identify potential major donors from smaller contributions.
“None of this actually works unless you have a really strong data foundation,” Blackwell said.
More accurate customer predictions
SAS, meanwhile, is pushing its AI boundaries, using predictive modeling and gen AI to automate customer journeys at scale, according to Chase. From lead scoring to creating next-best offers, AI has driven SAS’s customer engagement strategy, helping the firm maintain a competitive edge.
