A 5S Model for AI Adoption

Implementing a productivity AI tool can often be an overwhelming prospect, particularly when faced with the disconnect between potential outcomes of AI adoption and the current reality of what it can do well.

Through observing several organisations go through the AI Adoption process, I'm seeing the emergence of a 5S model that focuses on adopting the tool into simple workflows while building the foundations for deeper integration in more complex areas.

Here are the 5S's that can guide your AI adoption:

The first three S components provide some quick wins to get users to focus on initially:

🗒️ Summarise

Summarising meeting transcripts or lengthy documents. This low-risk activity brings a range of benefits, from allowing meeting participants to focus rather than take extensive notes, to letting your team save time in understanding long documents.These quick wins can greatly ease the AI adoption process.

🧼 Sanitise

Sanitising communications is an augmentation that can really shorten the cycle time in communication. Again, sanitising content is low risk compared to greenfield generative content, but it can significantly improve your team's ability to communicate with clients, particularly when technical information needs to be communicated simply.

📊 Structure

Going from zero to one is often the slowest progress, particularly when it comes to larger documents, presentations, or projects. Using the AI tool to provide, and iterate on, a framework can give the team momentum in their work.

The last two components focus on setting the foundation for exploring the edges of how AI adoption can aid your business with its current capabilities and preparing for how those edges may move in the coming months and years.

🔎 Search

Shift your team to an AI-first approach to their research. While relying on a single response over a range of options has risks, the goal here is to create comfort with how prompts can shift the output being generated, not to fully replace your team's capability to research across multiple sources. The biggest shift AI is creating is in the value migrating from knowing the answer to knowing the question to ask.

📖 Scrutinise

Train your team to think critically about AI outputs. The risk of inaccuracy in data, bias in decision-making, and diminishing capability exists if a team becomes reliant on AI without scrutinising and understanding the outputs.

Running a simple implementation of ChatGPT, Copilot, or your preferred flavour of general AI bot via this 5S model can pave the way for successful AI integration, driving efficiency and enhancing the quality of work across your organisation.