The narrative around AI is slowly but surely moving from hype to tangible outcomes, and from proofs-of-concept (POCs) to live implementations. In a chat with SAS’ chief marketing officer, Jennifer Chase, she was candid about the disconnect between enthusiasm for AI and its outcomes.
“What we are seeing is there’s a gap between all of the discussion and investment that’s happening in AI, and the ROI that customers are getting.”
The hard truth is that many organisations are still struggling to translate POCs into real and scalable business impact. But Jennifer observes that the most successful organisations share one critical trait, which is they anchor their AI strategy in trust and responsible AI practices.
“Thinking through your trustworthy AI is not an option anymore. It has to become the imperative.”
And for SAS, ‘trustworthy AI’ is not just a product label; it is an enterprise-wide discipline that spans technology, data, and people.
“So, the way we think about trustworthy AI is not only about the software solutions that you implement… it is how you look at your entire enterprise data strategy, how you train your employees.. We think about it from a holistic perspective.”
Marketing’s super power
According to Jennifer, even her marketing organisation is building up its AI competence, which includes creating to an extent, psychological safety for experimentation. “We recently did a (competition) to get new ideas for how we could be taking more risks within marketing, how we could be applying AI to help us achieve our objectives.
Although my title is Chief Marketing Officer, I think most days you could probably call me a chief collaboration officer.
Jennifer Chase
“We had over 80 submissions, and it was a really fun way to unlock the creativity of marketers to think about the work that they do, differently.”
In Jennifer’s view, marketing’s “secret superpower” in the age of AI, is an ability to collaborate across divisions.
“Although my title is Chief Marketing Officer, I think most days you could probably call me a chief collaboration officer, “ Jennifer explained, adding that she works with the sales and finance functions, as well as IT and human resource (HR).
“When it comes to AI, you have to be aligned with your CIO and your IT organisation, really ensuring that you’ve got the most modern capabilities, and your data strategy in place… You have to partner with your IT organisation to ensure this. And then we also work closely with our HR team to make sure that we’re putting proper (AI) training in place.”
Trust, governance, and data maturity
The chapter for simple productivity gains is closing.
In Jennifer’s view, a more consequential one is beginning.
“Our marketers in APAC are moving towards more department-wide capabilities,” she said, adding that they are asking questions like how to improve time-to-market and enhance customer experience. “And so those are the use cases that we tend to focus on now.”
One example of how SAS ticks this wishlist for marketers, is HAPPYGO, Taiwan’s largest loyalty card, that connects more than 11 million members with a broad ecosystem of brands.
By adopting SAS Customer Intelligence 360, Ding Ding (that powers the loyalty card) achieved a four to five times increase in productivity, a 20-percent lift in response rates, and more than one million customer touchpoints per day all just by personalising customers’ experience.
In this era, we used to think about garbage in, garbage out. Now, it’s garbage in, garbage SQUARED.
Jennifer Chase
From commute-time coffee offers to in-store birthday rewards, each interaction is driven by hundreds of data points in milliseconds.
Yet another example Jennifer shared is SBI General Insurance, which used to have fragmented customer data and offered customer journeys that were non-cohesive. Working with SAS, they now run much more customer-focused campaigns and see measurable gains in conversions, as well as improved customer retention.
Regulation and innovation
Enterprises also need to invest in data quality, integration, and accessibility before expecting AI to deliver meaningful outcomes. Jennifer opined, “In this era, we used to think about garbage in, garbage out. Now, it’s garbage in, garbage SQUARED.”
She noted that the APAC region is really comfortable with experimenting, and also that Europe leads the world when it comes to regulation which could make businesses in that region rethink some of their experimentation.
This highlights a tension between regulation and innovation – compliance may slow experimentation while ignoring governance will introduce long-term risk.
Being able to balance the two however, could lead to meaningful guardrails that enable bolder use cases.
