Marketo users might notice something curious about the header image on the original version of this piece. It is not Adobe’s CEO. It is Steve Lucas — then CEO of Marketo — photographed in San Francisco in 2017. Stay with that for a moment.
Artificial intelligence is forcing investors to rethink the economics of enterprise software. Adobe’s announcement that CEO Shantanu Narayen will step down after nearly two decades highlights how leadership transitions often coincide with major technology shifts. The timing is not coincidental.
A contrast that tells the story
Adobe continues to report strong financial results. Its subscription platforms remain highly profitable and widely adopted across industries. Yet the company’s share price has struggled over the past year. That contrast says a lot about the current moment in enterprise software.
Operational performance remains strong, but markets are beginning to ask a different question. Not whether Adobe’s current products are good. But whether the economic logic underlying large enterprise software platforms — deep integration, high switching costs, multi-year licence contracts — will hold in a world where AI tools offer increasingly capable alternatives at dramatically lower prices.
This same question is being asked about Salesforce, HubSpot, Atlassian, and every other platform that built its business model on the stickiness of enterprise workflows. The AI era is forcing a re-examination of where software value actually comes from.
“Enterprise platforms continue to play a critical role not because of the features they announce, but because of the infrastructure they provide: governed data environments, integrated systems, and secure operational workflows.”
Why enterprise platforms still matter in the AI era
Much of the current AI excitement focuses on individual tools. Generative applications, specialised copilots, vertical AI products. The narrative is disruptive: agile new tools replacing legacy platforms. But enterprise environments operate under very different constraints than the individual productivity context where many of these tools gain their initial traction.
Large organisations require controlled access to sensitive customer data, compliance with regulatory frameworks across multiple jurisdictions, integration across sales, marketing, finance, and customer service systems, and auditability of decisions that influence revenue and customer relationships. These requirements do not disappear in an AI era. They become more demanding.
Many AI tools gaining traction today are adopted bottom-up. Individual employees experiment with generative tools, build automations, and explore new workflows. That experimentation is genuinely valuable. But it creates governance debt. Ungoverned AI tool adoption in enterprise environments generates fragmented data flows, inconsistent customer experiences, and compliance exposure that typically surfaces twelve to eighteen months after the experimentation phase.
Three questions that will shape what comes next
What leadership profile will the board prioritise? A product innovator, a platform strategist, or a leader focused on capital markets communication would each signal a different direction for Adobe. The choice will reveal whether the board believes Adobe’s primary challenge is product differentiation, AI integration, or investor narrative.
How will Adobe translate AI capability into sustainable economic value? Investors will closely watch how AI features influence adoption, pricing, and recurring revenue growth. Adding AI features to existing products does not automatically translate to pricing power. The question is whether Adobe can demonstrate that its AI layer creates enough measurable value to justify the platform premium in a world of capable alternatives.
How will Adobe position its platforms in a market where AI tools are available outside traditional enterprise software ecosystems? The competitive threat is not from a single rival. It is from the cumulative effect of specialised AI tools that address individual workflow needs without requiring the full platform commitment.
What this means for Marketo Engage customers
For enterprise customers, the answer may ultimately be less dramatic than current narratives suggest. Large organisations still need governed data environments, integrated systems, and secure operational infrastructure. If anything, the AI era may increase the value of platforms capable of orchestrating these capabilities at scale — because the governance and integration burden grows, not shrinks, when AI tools are introduced into the workflow.
The most interesting question the Adobe leadership transition raises is not about Adobe specifically. It is about where enterprise software value accumulates in an AI era. The companies that maintain durable positions will be those whose platforms sit at the governed, deeply integrated layer that AI tools require to operate reliably in production. That is exactly the layer that most enterprise marketing stacks have underinvested in.
Which brings us back to Steve Lucas and that 2017 photograph. Marketo was acquired by Adobe in 2018 for $4.75 billion, primarily because of the depth of its enterprise workflow integration and the governance infrastructure it had built around B2B marketing automation. The value was in the foundation. It still is.
The Gravity Scan maps your marketing stack across 28 assessment areas — identifying where foundation maturity is sufficient, where it is not, and what to address before the next AI investment decision.