Hello,

December's end-of-year rush got me thinking about productivity and AI. While I've found ways to use AI effectively, I see healthcare teams struggling. So let's fix that!

Here, I will share the common mistakes teams make when adopting generative AI in healthcare and how to avoid them. Teams are pressured to " innovate with AI," yet lack the right guidance.

As a result, I see ( 😡😡) an increasing number of bullsh*t use cases that waste resources, energy and add complexity, keeping AI from delivering its true value.

What you’ll take away today:

What are the most common misuses of generative AI.
How can you scan your team's activities and find your bullsh*t use cases?
Tips to start simply and increase your team’s AI confidence, with no bullsh*t 😅.

"A fool with a tool is still a fool.”
Grady Booch

✨ Spark

✏ The most common generative AI tools

For generative tools here, I am talking about ChatGPT (OpenAI), Copilot (Microsoft), Gemini (Google), or maybe Claude (Anthropic) or Mistral (🇫🇷). Most of my clients have Copilot and ChatGPT.

They can create new content - from text and code to images and music - based on the patterns they've learned from training data.

"The danger of AI is not that it will revolt but that it will do exactly what we ask it to do."

So what are the main useless cases I see in corporate healthcare teams?

**✏ What is a bullsh*t use of gene AI?**

Bullsh*t AI usages are for tasks that don't need it, create more complexity than value, and often require more effort to maintain than the problem it solves!

So here are 5 most common bullsh*t AI usages.

**✏ 5 most common bullsh*t AI usages.**

Delegating tasks to AI without simplifying processes:

Instead of eliminating redundant tasks, teams layer AI onto inefficient workflows. Sometimes, it is faster to delegate to AI than to decide to stop doing things or change the process.

Replacing team alignment with AI-generated outputs:

While tools like transcription are helpful, they miss the nuanced human interactions that foster accountability and connection. Like meeting notes, for example. Your AI tools might capture the words, but they don't help you to get your team aligned - and we know nobody reads meeting notes (😉 not before AI, not after AI..).

“Innovation is not about tools; it’s about simplicity and alignment.”

Shiny object syndrome:

Teams adopt too many AI tools without optimizing their current processes. They fall into the trap of "this is new, this is so cool," so let's try. At the same time, they don't even leverage the already available AI tools.

Overcomplicating use cases first:

Teams often start with ambitious, complex AI projects instead of focusing on foundational tasks.

By fundamental tasks, I mean to leverage individual productivity and personal development first.

Not talking about AI enough:

AI adoption shouldn’t be a “one-and-done” conversation. If it is not a standing topic in your team meetings, this doesn't exist.

"The best way to predict the future is to implement it with purpose."

So how could we fixe that.

✨ Hack

Here are my tips on how to help the teams I am coaching to integrate AI faster with more open discussion and lasting impact.

✏ Create space and time to discuss it

Make it a standing topic for discussion in your team meetings.

Each team member will have their own personal path to integrate AI into their work (from the pioneer to the hostile to AI).

Create a safe place to share concerns and best practices. It is where a team coach can help you to design and facilitate this discussion.

✏ Treasure hunt to find the best available tools

Most of my clients have different tools for different divisions in the organization, but they do not have the same features!

You might have Copilot and ChatGPT or 2 different chatGPT. You might have one for your R&D organization and one for the business, or one in the US vs. Europe. One tool is more powerful.

Look for what is available and ask for access to the best tools. Some of my clients still don't have tools with vision mode (not able to upload or read documents..). This is a feature I use at least 3 times just to do this newsletter.

✏ Start with productivity and personal development

Instead of ambitious, complex AI projects, focus on productivity and personal development.

You have 3 steps to integrate AI in your work as team:

Personal productivity and development
Business operation (back-end operations)
Client services (front-end operations )

Focus on step 1 first. Discuss with your teams how they use AI for

Meeting notes: Transcribing and summarizing key points
Email management: Writing drafts, sorting priorities
Research: Finding and synthesizing information
Idea generation: Sparking creative solutions
Personal learning: develop new skills.

Discover our 6 weeks acceleration program ScaleU

I now use AI to draft my coaching session summary notes, cutting my admin time in half! But remember, it's like having a smart intern - you still need to review and adjust everything.😉.

✏ Simplify first your business operation, then delegate to AI

Step 2 is about your business operations. It could be writing an access and pricing dossier or developing an innovation pipeline for new ideas or new services to key account hospitals.

As a team, first, identify the tasks to eliminate, then use AI to streamline the rest. For ex automating repetitive documentation after redefining its core purpose.

“Success isn’t just about what you add, but also what you remove.” – Marie Kondo (The KonMari Method is a simple but effective method to organizing system - I wish my teenagers would apply that 😅)

You might want to start a simple Excel document where you list the best way to use it.

Finally, select the best use case, where to use AI for a key and /or recurring tasks of your team with a matrix-type effort needed to implement vs impact,

Now you are all set! That's it for today.

See you in two weeks. Keep the spark alive, and be intentional :).

Spark to Hack ✧

5 Bullshit Use Cases for Generative AI (your team Is probably doing one) StoH# 35