The Duality of AI Adoption

The internet is now littered with AI adoption material. There is so much material that your average LLM could potentially generate an adoption plan for your business or team in very little time.

The driving force behind the current wave of AI are the tech giants, and they are building a huge sense of urgency in the market—the pace of change, the promises of scale, and the fear of missing out. The vast learning resources, playbooks, and templates are all there to get us moving. It seems like it's all defined for us... so why isn't everyone getting on top of it?

The truth is, AI adoption is not as straightforward as it seems.

There is a duality to its nature that creates tension and anxiety, holding businesses back from making real progress. On the one hand, AI promises businesses the opportunity to do more with less. Fundamentally, the core proposition is job displacement and automation. OpenAI is already talking about $20k agents to replace business functions. This means that businesses that want to succeed need to start thinking hard and fast about the highest-value use cases where human effort is required and how to scale these using AI.

We call this top-down AI adoption. Leaders analyse their business from the top, identify areas where AI can unlock the most value, and work diligently to implement and scale these solutions. The tension here is—what does the end state look like? How do we assure our people that this is the right approach to take? And how do we ensure we're not just drinking Big Tech Kool-Aid, only to end up in the same place as the 70% of digital transformations that failed in the last wave of tech change (according to McKinsey & Company)?

On the other hand, most people who have learned to use generative AI technologies have already found ways of incorporating them into their daily workflows—whether for work or personal use. We know this technology is transformational. Many who use it do so in ways that possibly breach written or unwritten corporate policies because they see firsthand how much it helps them work faster and better. Yet, when organisations attempt to roll out generative AI tools, they often ban them outright, implement convoluted processes, or offer sub-optimal experiences that steer people away from using the technology. Individuals recognise AI’s transformative power, but organisations struggle to connect these individual use cases to scalable, enterprise-wide adoption.

This is where bottom-up AI adoption becomes critical. Employees need the right tools, training, and opportunities to integrate AI into their workflows effectively. They should be encouraged to share insights, create their own AI agents, and contribute to defining high-value use cases from their lived experiences on the ground. AI adoption cannot be purely a leadership initiative—it must empower employees at all levels to experiment, learn, and innovate.

Balancing the Duality: A New Mindset for AI Adoption

The tension between top-down and bottom-up AI adoption will persist for a long time. It’s healthy, but it requires a shift in mindset. Organisations need to balance strategic AI investments with grassroots AI empowerment. Leaders must identify large-scale, high-impact AI opportunities while also fostering an environment where employees are confident and encouraged to experiment with AI in their workflows. And of course there's a risk-reward balance that must be applied.

The last major technology wave—mobile apps and cloud computing—transformed the business landscape, yet only a small proportion of organisations truly reaped its benefits. This wave, too, was driven by Big Tech, and it came with the same sense of urgency and playbooks. How do we learn from the past and pave a different pathway? How do we make AI adoption more equitable and embed it into a truly transformative approach?

At Seen Ventures, we believe the answer lies in applying a method which enables top-down strategy and bottom-up empowerment through rapid experimentation. Our approach aligns with this duality because it directly addresses the tension of the top-down approach through hands-on experimentation that involves real people and delivers tangible wins—rather than just PowerPoint decks and strategy documents. At the same time, it enables bottom-up capability building, ensuring that people are empowered with AI knowledge, understand both its opportunities and risks, and can contribute meaningfully to how this technology is embraced in their organisations.