The 9 key use cases - how exactly is AI going to change your teams' working life?

                                                                                                        Image via Carnegie Mellon University.

The human-like paperclip would try and guess what you were doing in each Microsoft programme, make suggestions and offer to be of service. Here’s a trip down memory lane before Clippy disappeared for good in 2007.

The principle a responsive, intelligent helper and time saver within an app is not new - but it’s certainly come a long way since Clippy arrived on our screens on a bicycle.

Microsoft’s Chairman and CEO, Satya Nadella, talks about the era of copilots and how “there will be a copilot for everyone and everything you do”. In fact, Microsoft has begun to talk about itself as ‘the copilot company’ ← hugely telling.

So, what exactly is a co-pilot?

Copilot is an assistant within an existing programme that can help you:

• search and retrieve data

• support human service provision

• content: drafts, proofreads notes, and simplifies complex sentences

• image creation

• respond to queries

• brainstorm ideas

• plan and organise

We think of this just as a typed interaction on our devices - but it will become part of hardware and physical devices and products, changing how we work with everything around us.

Aeronautical engineer working on a plane: “Copilot, what brand of widget was used when this cooling system was last serviced?”

Farmer in tractor: ”Copilot, which areas on this field had reduced yield due to drought last year?”

Image credit: Alexandre Eisenchteter and the AI Tinkerers Club.

The challenge with copilots is that there are already so many and Microsoft, as the frontrunner, has a plethora - so many, it's hard to fit them in one visual!

Image credit: Mason Whitaker on LinkedIn.

You can expect this space to become (even) huge(r) and (even) messy(ier) over time as more players develop their own complex ecosystem. Sorry about that.

So that’s copilots - and now let’s look at GenAI use cases for collaboration that span copilots and way beyond…

1. Scheduling, agenda building and other meeting-specific AI use cases

If there’s one thing that AI does really well - it’s match time/place/people/topics. AI schedulers will automatically schedule and reschedule our meetings and other appointments, resolving conflicts and optimising your time and energy to best meet your goals.

AI can also create agendas based on previous topics, previous meeting minutes/actions, analysing past data and suggesting relevant agendas and attendees for the next meeting.

Here’s an example from AgendaAI by Charma:

And beyond meeting agenda creation, lies workshop design including creation of a plan, the slide, the facilitators’ notes and the participant workbook. Again, mind blown…

What else?

• Real time translation so meetings and events can be held in different languages simultaneously

• Scheduling assistants are already trying to provide emotional as well as practical assistance e.g. Koko is designed to detect the emotional state of the human and ask questions / suggest reframes.

• and of course, AI is already blurring screens, creating closed captions and adding cat ears in many of our meetings already!
  
  
  

2. Capturing collaboration outcomes and history

Nice obvious one to start off with. Every time we meet or communicate, a vast data are generated. Until now, we’ve reduced this to 2d and summarised it ourselves, essentially by:

• writing and sharing minutes and actions

This has been manual and limited.

GenAI has the ability to capture, interpret and so much more data - instantly.

• create and distribute key points and actions from a meeting - yes, tick - and with surprisingly high fidelity (faithfulness to the actual conversation).

• record who spoke most and least, who dominated the conversation (I was a bit shocked to learn that in some of my interviews, I talked for nearly 40% of the time - eeek!)

• capture engagement, sentiment (again, with pretty high fidelity), bias (wow) and charisma (goodness!)….

• develop and structure what was discussed in the meeting, creating tables, analysing pros/cons etc.

• recap the meeting - creating a short highlight reel personalised for a stakeholder, so they can consume the meeting quickly without having attended…

• … and the ability to jump straight to the recording of a specific part of the meeting to watch in full, where needed.

Do you have this tech already in our org?

• If you have MS Teams, you can already access meeting transcriptions

• If you have MS Teams Premium, you can get a lot of these features

• If you have MS 365 Copilot, you will have all of this.

• You can also get it via other systems like Read.ai or Jamie. Have a browse of the vast world of AI-meeting assistance here to have mind officially blown.

Clearly the potential for a vast about of manual work to be done instantly is huge. And in tomorrow’s email we’re going to talk about the extensive spanners this new capability is going to throw into your organisation’s wheels 🙂  (and in later emails, how to think about handling them).

3. In-meeting consultation, story sharing and feedback

Getting a meaningful response from a lot of people at once (by a lot I mean as few as 7+ people) is time consuming. Many ways of managing responses can over simplify and miss nuance (e.g. polling) but AI changes all of this.

A tool like Remesh.ai will pose questions of large groups and then analyse them in real time.

It will allow participants to engage with each other anonymously, generating new questions and discussion points based on previous answers.

This creates an entirely new dynamic and access to a new level of consultation and discussion.

Does it create some issues… oh wow, yes! More on that tomorrow.

4. Creativity and innovation

ChatGPT and now Microsoft Copilot has given everyone a taste of AI-assisted brainstorming.

• A range of potential solutions or options can now be generated almost instantly
• Providing requirements and constraints introduces new solutions the team might not have thought of - beating fixation (where idea and solutions gravitate around a handful of already known possibilities).
• And set aside new product design for now - we all draw down on creativity every day to develop ideas and bring them to life e.g. from new strategies to email titles, event names and way beyond. Tools likeSparkItUpwill help us do this better and faster as part of our every day work.

5. Thought partner

The more data these LLMs have received, they have started to generate emergent capabilities - spotting new patterns and working with higher and higher level concept. GenAI can role play, discuss issues, provide advice, coach and teach

You can use GenAI to make an idea more robust by asking it challenge you on the limitations and then help you generate better arguments.

If you want to learn a new skill, you can ask GenAI to teach it to you in a way that is perfectly personalised for you.

6. Knowledge management

If you work in a 12,000 person knowledge company in 35 countries, knowledge and information is everywhere but it’s hard to retrieve. You want to find out if anyone has done an embedded software project in this niche and language before? Previous like finding a needle in a haystack, AI will find that information instantly.

As knowledge, information and data explodes, the interfaces and platforms we use to handle it have increased expotentially too. No longer can you ‘find it on the P:drive’). AI will unify and democratise this information.

7. Decision making

Clearly AI can analyse huge data sets without error - no surprises there. But GenAI can also help you evaluate the pros and cons of a set of options in a solution space or any group of choices.

Now, much of the use of AI in collaborative decision making will come down to decision mechanics (who is making the decision, using what criteria) and decision philosophy (is it by pure data and logic or by human judgment?). Needless to say, AI can help teams integrate data and logic and contribute human-like judgment.

8. Content creation

Perhaps what ChatGPT is best known for, GenAI takes us off what Microsoft’s Alexia Cambon calls ‘the blank page’ - instantly creating sensible first drafts.

This is a vast area but through the lens of collaboration, GenAI means we can now:

• create a draft of something in a specialist area not our own - without needing to get help in the first instance from a colleague

• reduce the amount of time spent creating slides, reports and articles

• improve the quality of the writing we’ve already done

9. Co-presence

Immersive 3d spaces for example Microsoft Mesh will create a 3d world in which your avatar interacts with others - the idea being that you feel you are all there together. It’s designed to replicate the feel of a real-life in person experience including foster serendipity, reducing distractions and increasing focus and allowing attendees to interact spatially with the matter at hand.

And if you want to explore how GenAI is likely to be used for your specific role and situation, ask it.

“My job is to X. My biggest challenges are Y. How can you help me?”

I have drawn the line here at AI for risk management, project management - all relevant to collaboration but worthy of their own email series.

That was a lot! Hope you're still with me. Next, it's about to get REALLY interesting - as we talk about the challenges and shifts in norms and culture that these tools will kick up. This is the stuff you need to understand as leaders....

Next:
Get to grips with the 10 challenges AI will raise for your organisation’s culture, norms and behaviours.