Most enterprise AI rollouts focus on training and prompts, then leave employees to figure out the rest. In this article I outline a simple, scalable approach to building AI workflow capability across an entire organisation: an experience to expose the skills gap, tools to close it, and evidence to guarantee permanent transformation.
In my recent article Why enterprise AI will fail without workflow capability, we discussed the importance of building workflow capability before giving everyone AI.
But how do we approach building capability across an entire organisation?
Well, this has been a perennial challenge for L&D - the belief that we must either:
operate at an enterprise level e.g., “everyone needs critical-thinking training!” - which inevitably ends up with generic content that stays too theoretical to help anyone, or
focus on a specific use case and design a highly customised solution that only benefits one team e.g., “the sales team isn’t selling enough widgets, can you help?”.
Thankfully, with the approach outlined below, we can avoid both of these scenarios by giving people the skills and tools to improve their own work.
Why AI courses are doomed to fail
I’d like to start by crediting Nick Shackleton-Jones. In his book How People Learn, Nick talks about the insanity of building “courses”. His suggestion comes from the misguided belief that by cramming everything in a two day event or three hour online module, we’ll be equipped to perform better at work.
For those of us unfortunate enough to experience these courses, we know this to be a faulty assumption. We end up succeeding despite the course, rather than because of it.
Instead of courses, Nick suggests we focus on:
experiences to shift mindsets, and
resources to help people perform.
He explains this in the context of ‘push’ versus ‘pull’.
When we want to increase someone’s motivation, we should push an experience towards them (think about those pretend phishing emails sent out by enterprise cyber security teams that force people to think twice before clicking a potentially risky link because of the consequences of failing the test).
But when we want to improve someone’s performance, we should provide a resource they can pull from at the moment of need (think about a handy tooltip in the software interface that shows people how the functionality works).
And so, the approach to building a best practice enterprise-wide workflow improvement program takes this exact approach:
1. Experiences: help people feel the problem
Our first job is to help people realise that AI can’t operate without well defined work, which creates motivation to master the skill of defining work. And then once they’ve acknowledged this, give them a chance to practice.
And we can actually do this at the same time. Because what better way to demonstrate a skill gap than to experience that gap first hand? How often do we think “that looks easy” but when we try the thing, we fail abysmally?
So, by providing an activity in which people have an opportunity to define a workflow and a safe place to fail, we can help people see the gap in their own abilities. And once they recognise this gap, their motivation to build that skill will increase.
I’ve found the most effective way to do this has been with an everyday example of a workflow, something we’re all familiar with like making a cup of tea. And then asking people to deconstruct that workflow into a sequence of steps, providing enough detail that a novice could execute each step.
The mindset shift comes from the realisation that much of what we do comes from outside of conscious thought and is therefore missed when giving instruction to AI.
Once we’ve identified the skill deficit, we can give people tools to ensure that they don’t make the same mistake again. And then create space for them to use these new skills and tools on their own workflows.
The outcome being that once they have a well-defined workflow, the opportunity for how to leverage AI, automation or make other workflow improvements becomes immediately obvious.
And the beauty of this approach is that this experience doesn’t have to be delivered by a central learning function every time. It can be facilitated in a live session, run by teams themselves, allowing it to scale across an organisation.
2. Resources: help people improve their work
As part of the experience mentioned above, we can give people resources to help them define their workflows:
to the correct level of granularity, and
with the correct level of detail.
A simple rubric can help with this.
But once the workflow has been defined and detailed, we can also provide more advanced tools to guide people on how to improve their work (with or without AI).
As we know, with enough context and instruction, AI is extremely helpful. And so, with the defined workflow and a thoughtfully crafted prompt, AI can recommend how our work can be made easier, faster or better.
Because when it comes to using AI, the most common problem people have is not knowing how to use the technology in their specific use case.
Why prompt libraries don’t work
As AI becomes the norm, most organisations are seeing a cottage industry of prompts:
“Try this prompt for writing a report”
“Here’s a prompt for summarising emails”
“Check out this prompt for creating spreadsheets”
And whilst these can provide inspiration, it also tends to create overwhelm and noise.
A good comparison is the difference between the half-time commercials during a football game, versus tailored adverts in your social media feed. The former are generic whereas the latter are personalised and optimised for your specific tastes. I imagine the conversion rates on these different types of advertisements are wildly different.
And so, the same dynamic exists within organisations. Help everyone and you actually end up helping no one (there will always be a subsection of early adopters who go the extra mile to figure out how to adapt AI into their own workflows. But the messy middle needs more help).
And so, we can provide tools to:
help people define their workflows, and
make recommendations on how they can use AI to improve those workflows.
And by doing so, we’re not just giving people fish, we’re teaching them to catch fish for themselves. Armed with a well-defined workflow and a tailored recommendation, many will go on to build their own AI solutions.
Evidence: How do we know it’s working?
Providing these tools also gives us other significant benefits. Because once people are using them, we can capture data on:
the problems they’re looking to solve
which steps they find hardest, and
where they want AI to help.
Aggregated across the organisation, this data becomes insight that leaders can act on. Business units can deliver targeted solutions rather than continue the bombardment of generic prompts.
Not to mention, teams already building similar solutions can be brought together to collaborate, reducing duplicated effort.
It also starts to answer the question every leader will eventually ask: is this working?
Momentum: How do we make this a cultural shift?
Once people have built their solution, we can then encourage them to share their stories - the problem they faced, which solution they built and what changed as a result. L&D can play a key role here, creating systems to surface the best stories and help them to be shared across the organisation.
Stories shift mindsets in the same way the experience does, but without needing a workshop for every person, and they bring the next group of people in.
Use creates stories, and stories drive use, creating a powerful flywheel that can drive a cultural change as workflow improvement becomes the default for how the organisation operates.
Thankfully, each of these pieces is simpler to put in place than it sounds.
Over the next few posts, I’ll share what they look like in practice:
how to define a workflow in enough detail for a person or AI to execute it
how to design the workshop that gives people the chance to practise, and
how to build the self-service tool that guides them through it.
And if you’re an L&D professional who wants to master workflow improvement and become the person your business turns to as AI changes work, join my email list today.
