Tony and I talk about the concept of MarTech 4.0, explaining why enterprise organizations must move beyond siloed channel strategies toward unified data, content, decisioning, and orchestration.

If you're a MarTech leader, you've probably experienced some version of the same frustration. Your team owns critical systems, manages increasingly complex customer data, helps shape digital experiences, and is now being asked to play a leading role in AI initiatives. Yet despite all that responsibility, you can still find yourself treated as an implementation resource. The business arrives with a request, your team evaluates the options, builds the solution, and moves on to the next request. Meanwhile, strategic decisions too often happen elsewhere.

MarTech has evolved from an idea, to a stack, to a career path for enterprise leaders who can successfully bridge the domains of marketing, technology, and data. After supporting MarTech leaders for nearly two decades, RSG has distilled key strategic lessons to apply for the coming AI era.

The MarTech landscape is shifting rapidly, amid requirements for omnichannel engagement and greater understanding about the enterprise foundations required for successful AI in Marketing.

What does MarTech selection look like in an era characterized by almost overwhelming AI messaging? How much does AI really matter to finding the best-fit platform and vendor? What do you need to do differently, and what remains tried-and-true?