AI & Learning Teams | What to Avoid
Harald F. A. Overaa
Learning Nerd and Tech Advisor @Docebo | L&D Coach | Here to help you navigate the learning tech jungle ????
Part 1: Why a Product Mindset is Key to Working with AI in Learning
Recently, I have been thinking a lot about how teams should work with AI, and what they need to avoid.???
I got inspired to explore product mindset in L&D, and specifically about its use of AI after listening to? Egle Vinauskaite 's appearance on the Learning Hack podcast with John Helmer .? I then went back to watch a Youtube video from Egle speaking to Kevin Alster on the Synthesia podcast where they discussed Product Mindset in L&D.?
I got further inspired by this from Egle and Donald H Taylor 's Learning Technologies webinar on AI last week and subsequently their AI study from last year.?
So what is a product mindset??
A Product Mindset is a “way of thinking that focuses on creating product solutions that provide real user value”.?
It’s about keeping the customer/end user front-and-centre and having this as the core lens in which you develop your programs.? Developing a Product Mindset means pushing yourself to understand users and revisit your value proposition on an ongoing basis.?
People with a Product Mindset aren’t interested in creating products and pushing out features for the sake of it; rather, they are wholly focused on how effectively their product solves the user problem they set out to solve.
For me, this is the opposite of throwing stuff to the wall and seeing what sticks.?
It’s not a bit of gamification to fix an engagement issue.?Or giving a huge content library without meaningful curation relevant to roles or skills.?
It is about understanding who is the target audience, and what problems are they facing.?A product mindset tells us to start with the problem and focus on the user.?
How Product Mindset Relates to AI:
We need to be deliberate about how we’re using AI. When AI has so much potential, it is tempting to solve the wrong problems.
In essence, product mindset relates to AI in L&D by starting with the problem, and avoiding scaling what doesn’t work quicker.?
A lot of teams are only focusing on solving a content creation problem.?
For me, this is the very first layer AI can help with. But it shouldn’t stop there.?
A lot of teams follow AI in this order 1. Content creation → 2. Skills Development → 3. Learning Strategy → 4. Business strategy.?
I would argue it should be the opposite. Start by understanding the business strategy, and then build your learning strategy around that.
From there, you can use the product mindset to assess the best use cases of AI within the context of solving business problems.?
AI can help your business strategy, and be a key enabler in building learning programs that support this.?
But it can also be approached in the wrong way. Without a product mindset, and as a way of plugging holes.?
If you want more info on product mindset, see these great links I reviewed to write this below:?
Product School - How to Build a Product Mindset
Medium - What is a Product Mindset?
How NOT to work with AI as a learning team.?
1. Do not Assume AI will solve all your problems.?
It’s a toolbox, but you need to ensure you use the right tool. As a builder, you look at what you’re building and subsequently, what tool to use. AI is the same, diving head-first without a purpose is a recipe for disaster.??
AI is not a silver bullet that does it all. It can enhance your work if used intelligently, but it can also lead you astray. Take time to research and experiment with your work. Apply your context for use cases.?
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2. AI is not a Learning Strategy
It’s an enabler, not the strategy itself. AI is an enabler, or a way to reach your strategy faster. It's not the strategy itself.
Your learning strategy should not focus on AI, it should focus on your end goal, increasing business value through your people:
? AI can help you get to these outcomes quicker, but it's not the end goal.
???? Make AI your friend, a helping hand and an enabler of strategy.
3. Only staying in the "L&D bubble"?
If your organisation is investing in Microsoft Co-pilot, you should be doubling down on this. Within the product mindset, focus on how to build better experiences for your end customer (employees). Focus on how to enable upskilling/reskilling on AI and copilot in this context.?
It is critical that learning teams understand the wider business strategy and how AI fits into that before they dive head-first into AI themselves.?
It is tempting to outsource our thinking to AI, as we are looking for shortcuts and ways to optimise without the necessary effort.?
To avoid this, start by understanding the problem you solve, and work backwards on how AI can be an enabler to reach this goal.?
4. Do not solve the wrong problems, faster.?
If we are unclear on business strategy, our learning strategy becomes unfocused. This again leads us to solve issues that matter to the learning team, but not the wider business.?
Take content creation, for example, you could create 100 courses quickly with AI. But should you? I would say no. Without a clear purpose and strategy for the problem you are solving, it is not the right way to use AI.??
AI requires us to rethink and unlearn a lot of ways of working. Without a compass guiding what you should do (product mindset and solving business problems), it is easy to solve wrong problems in a faster way.?
5. Use AI without thinking of your end users.
Product mindset is key here,? and the first section of this article was written for this purpose. Do not dive head-first into AI without being clear of your intentions with it.
6. Jump right in with no upskilling on AI -?
Like with any tool, you need training on it. Many teams will give up on prompts before they’ve understood how to do it unless they’re taught on it. Learning teams need to upskill themselves on AI if they are to teach others. There are plenty of great resources to use here, but I recommend Ross’ course on AI for learning teams as a starting point.?
7. Do not assume AI is always ethical, without bias or privacy concerns?
Recommend Jon Fletcher and the LPI’s Seven Principles for Responsible AI here. This is a great resource on what AI should be like. It is important to know that this isn’t always the case.?
Bias/discrimination/hallucinations are common. If the data is not managed securely, the use of AI raises privacy concerns since it requires collecting and storing large amounts of personal information. It is critical to consult with the right teams internally to ensure you are using AI. Your unique voice, tone, and perspective can’t be reflected by AI. In areas such as coaching and mentoring, AI-powered learning may lack the human touch and emotional connection needed for effective learning. My take - stay curious, aware but also apply a healthy bit of scepticism when it comes to AI.
Parting words:?
As shown in this article, AI can enhance a variety of tasks but the hype can also be exaggerated. It’s your job to cut through the noise and decide what parts of AI you wish to incorporate into your learning strategy.
It’s important to use a product mindset and tap into the wider business strategy to solve real issues with AI, not just the quick ones.?
Want more info on AI??
Here is a list of people I get inspired by in the intersection of AI and L&D:??
Stay curious,?
Harald
AI is changing the world - I am here to supercharge that change | Connecting HR and Tech | 12+ Years Leading People & Product Initiatives | opinions expressed are my own
9 个月Interesting read Harald F. A. Overaa, essentially the approach outlined is about Outcome vs Output. Outcome:?are what the business wants or needs to achieve. Output:?the actions or items that contribute to achieving an outcome. Some departments (marketing, sales) are more output-oriented, while a few others (growth) are outcome-based. L&D historically was more focused on output needs to shift mindset with AI to be more outcome led.
Strategic Advisor | Speaker | Anchoring AI Video Communications within Business
9 个月Thanks for the shoutout Harald! I'm designing for 2 reasons: 1?? Make AI avatars a little less scary for everyone 2?? How to meaningfully apply digital tools in Learning
Podcaster, the Learning Hack and Great Minds on Learning | Communications Expert | Fractional Marketing for the Learning/HR sector
9 个月So great to have these kind words from you, Harald ??
Passionate about taking people to the next level no matter what their role.
9 个月A Product Mindset seems so much better than a "content" mindset ??
Head of Learning and Talent Development l Driving Organisational Performance Through People I Eternal Optimist
9 个月Harald F. A. Overaa love this! Is there a danger of AI in learning being the 'best solution looking for a problem', in some cases yes. Your post resonates - there is a strong case for taking learning 'back to basics', I don't mean back to 'overhead projectors' but rather as you point out here - seeking to understand and validating the need. Is this a dying art/skill or is it easier to simply find something shiny and new! What AI is doing and will do for our industry and trade is phenomenal but I couldn't agree with you more - focus on the problem and the value add.