Our Ed Ortega sat down with Cisco's, SVP of AI Software and Platform, DJ Sampath for a frank, insightful and rich conversation about what's really getting in the way of enterprise AI adoption and success.
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The most uncomfortable finding in Section’s January 2026 AI Proficiency Report is about perception; Leaders overwhelmingly believe their AI deployments are succeeding. The rest of the organisation, particularly individual contributors, do not share that view.
Enterprise users don’t want more features—they want less interruption. Tools fail when they break context and steal attention. The best systems stay invisible, carry context forward, and let users remain in flow while the work moves naturally around them.
“Platform” is one of the most overused words in product — and one of the most misunderstood. A true platform isn’t just shared infrastructure; it’s reusable capability built to help teams move faster. Get it right, and you unlock scale. Get it wrong, and complexity quietly slows everything down.
Stop treating AI enablement as a distant vision or software rollout. Progress stalls because organizations avoid hard choices today. Treat AI as an operating model change. Pick one real workflow, build with small teams, learn fast in 90 days, and let execution—not hype—shape strategy.
Boards don’t need more AI hype—they need sharper governance. This piece cuts through the noise with three questions that clarify what innovation really means, what AI actually changes, and where real value sits—so boards can shape the conditions for safe, scalable impact.
Feature velocity can mask structural drag. Real scale comes not from shipping more features, but from building reusable platforms—shared data, APIs, and infrastructure that compound value. Sustainable growth happens when organisations reduce friction and create foundations others can build upon.
When deadlines are fixed and scope is unclear, the real risk isn’t speed but misalignment. In 2026, redesigning under pressure means more than improving usability—it means intentionally designing the data layer so products can learn, adapt and compound in value after launch.
Scale is often treated as an unquestioned goal, yet much of what organisations call scale is simply expansion that adds complexity and dilutes impact. This article argues that true scale occurs only when growth strengthens the system itself, creating compounding value rather than just wider reach.
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