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NASHVILLE — The artificial intelligence vibes at the Sitecore Symposium are as real as sounds of country music cover bands emanating out of bars on Broadway Street here in the Volunteer State this week.
AI’s the foundation, after all, of the digital customer experience provider’s big software reveal at its 2,000-attendee customer conference at the Gaylord Opryland Resort and Convention Center: Sitecore Stream and its vision for an “Intelligent DXP.”
On the ground floor, however, web developers, web technologists, marketing technologists and good ole marketers have concerns over our bot friends. Some don't want to go all in — yet.
Governance. Security. Unknowns. Risky resource deployments. These practitioners also grapple with the age-old question for all hyped technology: how does this help my team, and, more importantly, my customers?
The experimental phase of AI is still here. For now. It's what they told us at Adobe Summit in Vegas in March. It's what they told us at Acquia Engage a year ago in Boston.
Sure, AI is the real deal, like a young Johnny Cash in the mid-50s about three hours west of here in Memphis, where the country singer broke through.
There is a significant rise in the use of AI across the DCX toolset, with 55% of organizations now using it to some degree, and more starting out on their journey, according to our CMSWire State of Digital Customer Experience report. More also believe the future impact of AI will be “transformative.”
Table of Contents
- Is There Real Value in AI Deployments Now?
- AI Adoption: Cautious Optimism Across Industries
- Governance and Security: Major Concerns for AI Rollout
- Balancing Excitement and Pragmatism With AI
- Industry AI Adoption: Waiting for the Right Moment
- The Cost of AI: A Barrier for Widespread Adoption
- Incremental Adoption and the Road Ahead
Is There Real Value in AI Deployments Now?
“It’s really right now just a lot of discussions amongst us, seeing what's out there,” said David DeLella, Sitecore customer and IT applications architect for Regal Rexnord. “It's growing every day, so it's really hard to keep up with right now. The thing is: when do we jump on the bandwagon? When are we ready to pull that trigger?”
DeLella shared that, from a developer's perspective, there's always a question of whether AI is truly delivering the expected returns, either from a coding or DevOps standpoint. He acknowledged that while there are promising AI demos with potential business applications, the development side hasn't yet fully embraced it.
His team is still in the early stages, exploring how AI could help speed up processes like onboarding, environment setup and code migration. However, they're hesitant to fully commit just yet, given the rapidly evolving landscape. The concern is whether investing now would be premature, as new AI models could render earlier efforts outdated. The key issue holding them back is determining when the value justifies the leap.
“When you look at it today, and then if we look at it again in six months, there's a lot more value six months from now,” DeLella added. “And if we had dove in at the beginning, did we feel like we would have wasted that six months trying to build on whatever was there at the time, only to have a new AI model come out? So it's kind of like, when do we jump in and it feels right for us? We’re still working to that point.”
Related Article: Can Sitecore Stream Orchestrate AI-Powered Marketing Success?
AI Adoption: Cautious Optimism Across Industries
In various sectors, businesses are cautiously experimenting with AI, recognizing its potential but remaining hesitant to fully embrace it.
Akia Young, a web technologist at the Merchant Risk Council, exemplifies this sentiment, explaining that her company is “still kind of new in the early stages of building out our AI policies.”
While they’ve implemented AI tools such as transcription platforms for multilingual conferences and ChatGPT for smaller tasks, Young’s organization remains in the exploration phase.
"We don't have a bunch of things going on with AI,” she said. “We might use it for, like, an SEO thing here and there," she said.
AI Data Security Is Paramount
Young explained that one of the key reasons her organization started building an AI policy this year was due to concerns about data security. With AI models learning from user data, they wanted to ensure that sensitive information — such as business practices and customer data — was secure and not used inappropriately.
Young emphasized the importance of protecting this data, especially in light of the increasing number of cyber attacks and breaches affecting many companies.
She finds reassurance in Sitecore’s AI announcements this week in Nashville because her company’s already a customer, and she feels better about using AI in one secure place vs. in disparate systems with a lack of governance.
“One of the biggest things that really perked my ears up at the Sitecore session this morning was about the fact that the data is secure,” Young said on Wednesday, Oct. 16. “So now, with us not having to put data here, put data here and put data there, with us putting it all in one umbrella in one bucket, I think that that cuts down on a lot of worry about where our information is.”
Related Article: Sitecore Incorporates OpenAI Generative AI Into Software Solutions
Governance and Security: Major Concerns for AI Rollout
That’s just it: one of the recurring themes among companies hesitant to fully adopt AI is the issue of governance and security.
Heather Hartkopp, digital platform manager and marketing technology specialist at Corbion, noted that governance was a major inhibitor for her organization’s initial AI rollout.
“Governance — everybody's fear,” she said. “We can't understand or truly know where our data security is at with this,” she explained. “We didn’t have enough information. ...AI for us was kind of scary last year. Everybody was like, we're not even going to talk about it, don't bring it to the table.”
This year, Hartkopp said regulators who enforce GDPR laws started sharing education about other companies that were endorsing or embracing AI. She felt more comfortable gaining those references.
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“That's one of the biggest reasons for coming here,” Hartkopp said of the Symposium. “It’s really getting more exposure and understanding what AI could bring to us, how we could absorb that and create an ROI that the executives would get excited about.”
Balancing Excitement and Pragmatism With AI
With the growing excitement about AI comes a healthy dose of pragmatism. Hartkopp acknowledged that, while her company is still taking small steps with AI, they are already seeing potential applications in customer service and sales.
“Customer service would benefit huge,” she said, adding that AI could improve the efficiency of global operations and reduce the need for human intervention in certain areas. However, she emphasized that internal operations and efficiency are the current focus, rather than marketing or customer-facing outcomes.
“We don’t have a 24-7 customer operation,” she said. “But we ship globally, so we have to be available at any time. AI could leverage that for us."
With AI, she wants to do some internal lift so that marketers can leverage that conversation initiation.
“Whereas now, it's a lot of trade shows," Hartkopp said. "Come to the trade show and talk to us, versus browse around and get a high level of information, and as we watch you look and ask things, we’ll get you to the right channel and the right communication. So I think that's a second step, honestly, just because we need some internal lift within our own resources.”
Industry AI Adoption: Waiting for the Right Moment
John Field, senior director and analyst at Gartner, described a future where AI is no longer seen as a novel technology but a standard part of business operations.
“I long for the day, and I see this with a lot of vendors, where we stop talking about AI as a thing, and it's just embedded,” he said.
The industry also has some work to do gaining value for customers — vs. gaining value for marketers — when it comes to AI.
“The thing I find interesting about marketers' focus on AI is it's about them using it,” Field said. “It's about how they're going to get efficiencies. I think it's genuinely going to help to solve the personalization issue. ... But what they're not thinking of is how can they do it for their customers. It’s making their jobs easier, but how are you trying to make your customers' jobs easier by using AI. It’s really very selfish.”
Related Article: Why 93% Ignore AI in Marketing
The Cost of AI: A Barrier for Widespread Adoption
Another challenge companies face when considering AI adoption is the cost, both in terms of infrastructure and ongoing usage. If you look at the cost to train AI models (Sam Altman has estimated more than $100 million for ChatGPT-4) just imagine how that gets passed onto those using it eventually. Then again, ChatGPT costs $20 per month, and APIs are APIs.
Matthew McQueeny, head of relationships at Konabos, touched on the financial barrier AI poses for many organizations. While AI could offer significant efficiencies, the cost of implementing it might be more than anticipated, potentially beyond what's already covered in existing licenses. He pointed out that AI’s benefits, such as providing insights and automating processes, come with the high cost of server capacity and system resources, making it prohibitive for many companies.
He likened AI's energy and resource demands to cryptocurrency mining, where the real profits are made by those selling the infrastructure, such as chip makers like Nvidia, and hosting servers.
AI: What's the Total Cost of Ownership?
McQueeny emphasized that calculating the true return on investment of AI will require looking at the total cost of ownership (TCO) and whether AI can ultimately allow companies to do significantly more with their current workforce. However, it remains unclear if costs will decrease or if AI can be seamlessly integrated into existing systems at a more manageable price.
“Does it mean we can do 10 times as much with our existing employees and get the equivalent of having that many more employees if they can smartly curate it?” McQueeny said. “Or is the price going to come down? Is it going to be able to be embedded into a system like Sitecore? Because, Sitecore can work hand in hand with Microsoft, so they can truly do that. I think it makes a lot of sense. It's a natural way. It feels to me innovative, and well thought-out to do it, not just like a plugin. But I think the ROI is tough in the enterprise with generative AI.”
Incremental Adoption and the Road Ahead
Overall, companies across industries are taking a measured approach to AI adoption. Governance, security, cost and operational efficiency remain top priorities as organizations experiment with AI applications. Practitioners in the digital customer experience world here in Nashville represent the cautious optimism shared by many professionals — they recognize AI’s potential but are still waiting for the right time to fully commit. As Gartner's Field pointed out, the key to AI’s success lies in its ability to seamlessly integrate into existing systems, becoming a foundational tool rather than an experimental add-on.
It's about “leveraging it the right way, and not allowing it to wag the company," McQueeny said. "So it's control, it's cost, it's security. These kinds of systems that Sitecore is announcing, you'll hear in a lot of these enterprise solutions as well, they're controlling it. It's in your instance. Like Sitecore even said, we're not taking your data to do an underlying model with your info. So I do think that that starts to help, maybe not be the killer app, but be the pragmatic entry into it.”
