According to Experian's tech CEO, the most contentious decisions involve enforcing standards by retiring tools that developers and clients love. These migrations are costly, create friction, and require careful, consensus-driven planning to manage the human element of change.
Despite proven cost efficiencies from deploying fine-tuned AI models, companies report the primary barrier to adoption is human, not technical. The core challenge is overcoming employee inertia and successfully integrating new tools into existing workflows—a classic change management problem.
The biggest resistance to adopting AI coding tools in large companies isn't security or technical limitations, but the challenge of teaching teams new workflows. Success requires not just providing the tool, but actively training people to change their daily habits to leverage it effectively.
While Experian's tech CEO aims for consensus, he makes final decisions based on a clear hierarchy of principles. He will override his team's recommendation if it compromises a core value like security, even if their choice is more economically sound.
When Mozilla leadership pushed to adopt the WebRender engine based on "vibes" and momentum, they ignored valid concerns from the expert graphics team. This dismissal of deep technical expertise in favor of top-down enthusiasm proved toxic and led to the departure of key senior engineers.
When selling to senior technical leaders, do not assume the conversation will be about technical vision or features. A CTO at a top 50 company was more concerned with how a new technology would affect thousands of workers and how the vendor would support that transition. The human and organizational impact often outweighs the technology itself.
Enterprise software budgets are growing, but the money is being reallocated. CIOs are forced to cut functional, "good-to-have" apps to pay for price increases from core vendors and to fund new AI tools. This means even happy customers of non-mission-critical software may churn as budgets are redirected to top priorities.
MongoDB's CEO argues that successful pivots during tech transitions like cloud or AI are fundamentally change management challenges, not technical ones. The biggest risk for established companies is complacency. Leadership must force the organization to lean into new platform shifts, even when their maturity is uncertain, to avoid being disrupted like Nokia or BlackBerry.
To prevent redundant work and enforce standards in its federated tech organization, Experian runs a monthly 'Technology Executive Board.' Chaired by the tech CEO, this forum brings all CTOs together to disclose roadmaps and align on shared platforms.
Even if legacy code is stable and functional, it should be replaced when the user experience it provides becomes obsolete. When user expectations (e.g., mobile access, modern UI) have fundamentally shifted, the old system becomes a liability regardless of its technical stability.
To transition to AI, leaders must ruthlessly dismantle parts of their existing, money-making codebase that are not competitively differentiating or slow down AI development. This requires overcoming the team's justifiable pride and emotional attachment to legacy systems they built.