Martin Kihn is the SVP Strategy for Marketing Cloud at Salesforce and author of the book “Agentforce”
Never before have so many people become as infatuated as quickly and as enthusiastically with an emerging technology as they have with AI.
According to one estimate, 66% of people now use AI regularly1. It has become an indispensable utility in their everyday lives. People use it to shop. To plan their travel holidays. To consult on health concerns. To manage their finances. To help with repairs. To interpret technical jargon. To manage and respond to e-mails. To plan dinner. To organize their day. Even to serve as a confident and friend.
All of this adds up to an historic inflection point in the market. AI is influencing how people discover, compare, and buy products and services. It has already upended search marketing. It has disrupted the way brands are discovered. It has turned the marketing funnel upside down. It has drained away web site traffic. It has neutered the power of brands to influence consumer choice. It has made prices fully transparent. Most of all, it has raised the expectations of customers to new heights.
Suddenly the old marketing playbooks have become relics of a bygone era when brands were more or less in control of their destiny. Marketers are now faced with reinventing the way brands go to market. But it is not yet clear that very many brands – especially me-too brands most at risk – grasp the full extent of the threat. Instead marketers are caught up in merely using AI to compress campaign timelines and workflows. Understandably so: they spend more than half their time today on tedious and repetitive production work. CMOs who can automate routine execution tasks and trim headcount are always seen as heroes by their bosses.
Marketers can now push out more campaigns in less time with fewer resources across more channels with more precise aim. But they are falling short in harnessing the full power of AI to reimagine the customer experience. Which is why so many AI pilot projects fail to scale. AI is just plugged into current ways of doing things. Marketers just want to keep doing what they’ve always done – only faster – when what they really need to do is rethink processes from scratch. Instead of seeing AI as a way to free their time for more strategic visioning, they think of it as scab labour. So there is an enthusiasm gap that is holding back progress.
The other major stumbling block is a longstanding one that marketers can’t solve on their own. They are often stuck working with legacy systems and a mishmash of loosely connected marketing tools that are simply underpowered to cope with the demands of generative AI. Hyperpersonalization is an alluring concept – until it runs headlong into the sobering reality of stove piped systems and dirty data. What marketers really need – what they’ve always needed – is a unified customer data infrastructure and knowledge base – machine readable by AI – that they can trust.
Which is exactly what SalesForce has brought to market: an all-in-one enterprise solution called Agentforce that connects all of the requisite components in an integrated, AI-ready architecture. By implementing Agentforce marketers can jump start the deployment of agentic AI, sidestepping the perilous path of going it alone. There is always a lot of heavy lifting involved in taking a do-it-yourself custom-built approach, and often it does not end well, mainly because of messy, conflicting data and disconnected systems. Too many moving parts, too many chances for things to go sideways. Whereas with an interoperable, purpose built, tightly connected solution, especially one from a known vendor like Salesforce, the on-ramp is less steep.
Since its inception almost 30 years ago, when it pioneered the concept of cloud-based SFA software as a service, Salesforce has continued to push the boundaries of what’s possible. Its longtime market dominance in CRM gives it instant credibility and peace of mind with enterprise-size businesses looking to build a central operating system for agentic AI automation.
In his role as strategy lead for Salesforce’s Marketing Cloud, Martin Kihn is charged with explaining the advantages of using their platform. His gift is that he is able to translate technical jargon into plain language that marketers can easily understand. His two prior books pulled back the curtain on customer data infrastructure, building an aspirational picture for marketers of what their technology foundation should look like, from front to back end. In his newest book Agentforce, Martin Kihn lays out an evolutionary path for marketers to follow if they hope to harness the full power of agentic AI.
I started by asking Martin if he thought his real job was as Salesforce’s “Chief Explainer”.
Martin Kihn (MK): You know, it’s hard to figure out what our talents are in life and I think they emerge later. And because I look back on my career and I think, well, what was I good at all those years? And I think that’s exactly what it is. It’s taking something technical. And my approach to it is if I can get to a point where I understand it, which takes work, then I can explain it. And I think Richard Feynman2 said that. He’s like, if you can, if you can explain something to an eighth grader, then you really know it.
Stephen Shaw (SS): Right.
MK: And they understand it and they get it. So I try to explain how our products work and I try to do it in a way, and I feel almost anything can be understood, even AI, if it’s explained correctly, even very technical concepts can be understood. So that, that is my role.
SS: Which is the success, I think, of this latest work of yours. It does that exceedingly well. And of course we’re inundated these days with articles and white papers and consultancy reports and everything else on AI but piercing the technical fabric of it is another challenge. As I alluded to earlier, you had, you’ve written two other books3, “Customer Data Platforms” and in a similar vein – excellent at explaining a complex subject – and “Customer 360”, both of those are co-authored. This one you chose to write on your own. I’m just wondering what the thinking was behind that or why the change?