What Embracing the AI Platform Shift Really Means

Just like the introduction of computers, the internet, and mobile phones before it, AI might have started out as a fun novelty – and we certainly used it that way to generate quirky pictures and poems for laughs, but it is rapidly transitioning to a business necessity.

The evidence of this trend playing out at unprecedented speed surrounds us. There is an expanding ecosystem of AI-native startups, accelerating enterprise adoption, and the unmistakable reality that organisations failing to adapt risk obsolescence.

Here’s the big statistic to go with it: 92 per cent of CIOs believe that AI will be implemented in their organisations by the end of 2025. Being one of those eight per cent that aren’t working with AI is going to start looking like how it must have to those organisations that still held on to their typewriters for too long.

For established companies like nCino, the imperative here is clear. Staying relevant means rethinking foundations and rebuilding with AI embedded throughout the organisation, right across strategy, culture, and people, and it’s not an incremental change; this is a story of transformation.

Strategy First: AI Is Not a Silo

The most common misstep companies make when approaching AI is creating a standalone “AI strategy.” This siloed thinking inevitably leads to technology adoption for its own sake, resulting in scattered experiments that fail to deliver meaningful business outcomes.

Leading organisations understand that AI must be embedded within their core business strategy, not alongside it. Netflix doesn’t have an AI strategy separate from its mission to entertain the world. AI simply amplifies how effectively they deliver personalised content. Similarly, Jordan Brand leverages AI to strengthen its connection with sneaker culture, and nCino uses it to rethink banking in financial services.

The integration of AI into business strategy necessitates an elevated focus on data. With AI, data is no longer just a record of past performance but the fuel that powers future capabilities. Organisations that recognise this shift are investing heavily in data infrastructure, governance, and literacy across teams. As nCino has demonstrated, when data strategy becomes inseparable from business strategy, AI can transform customer experiences and operational workflows in ways previously unimaginable.

Innovation Culture: From Theory to Action

The gap between AI aspirations and results remains stubbornly wide for many organisations. Despite increased spending — particularly in the banking sector — many institutions report disappointing returns on their AI investments.

Gartner’s prediction that 30% of AI projects will be abandoned after the POC stage is looking pretty accurate, and mirrors the challenges that organisations have had with transformative technologies in the past.

It’s not technical capability that’s making AI adoption difficult, however. The difference between success and failure often comes down to culture.

Companies succeeding with AI foster environments where teams can experiment, fail fast, and quickly incorporate learnings. They recognise that perseverance through initial setbacks is essential for breakthrough results.

This cultural shift extends to process as well. Development cycles that once stretched across months or years must compress to match AI’s capabilities. The evolution is clear: from waterfall methodologies to agile frameworks and now to even more dynamic, AI-accelerated development cycles. Companies like nCino are adapting their processes accordingly, enabling faster ideation-to-implementation timelines while maintaining necessary controls.

Humans at the Helm: Empowering the Workforce

Perhaps the most pernicious myth about AI is that it eliminates the need for human involvement. The reality is more nuanced: AI doesn’t replace people—it transforms the roles they play.

Human judgement, ethical considerations, and critical thinking become even more valuable in an AI-enabled organisation. Consider the cautionary tale of a startup founder who built an application entirely with AI, bypassing human oversight of security protocols, and then focused more on building the company than the application. The result was a spectacular (to say the least) crash.

Working with AI successfully on any level – whether to support the business or as the product the business sells – depends on upskilling people and embedding accountability across teams. This means investing in training programmes that help employees understand not just how to use AI tools but when and why to apply them. It means creating clear governance frameworks that delineate responsibilities for AI outcomes. And it means fostering a culture where humans and machines collaborate rather than compete.

The companies that thrive in this new era will be those that view AI not as a technological add-on but as a fundamental reshaping of how they operate. They’ll integrate AI into their strategic foundations, foster cultures of practical innovation, and empower their workforces to leverage these new capabilities effectively.

To be sure, it is a challenge as well as an opportunity. But given that AI isn’t optional, the best time to start grappling with this challenge was yesterday.