Using AI For Effective L&D: From Buzzword To Business Impact
Here's the problem with how L&D uses AI right now ?? It's driven by efficiency.
Now there's no problem with being efficient, as long as the thing you're trying to do more efficiently is the right thing you should be doing.
In our latest webinar with Talaera , we tackled some of the challenges and solutions of doing that in practice.
As always, keep scrolling for some key lessons, and check out the full conversation here:
The relationship between efficiency and effectiveness
Mel shared a great quote that “it's the difference between doing things right versus doing the right things.”
And it’s not an either or issue, because nobody is going to argue that you shouldn’t do the right things or try to do things right.
“I think the problem is though that it's easier to do things right. Being efficient is easier than being effective. And I think part of the reason for that is we just have much more practice at it.”
Imagine you enter a new role, you get given a set of tasks, and then you’re taught to perform those tasks to reach a specific outcome.
Then you can bring in tech to perform them more efficiently as it emerges.
“The problem is that you don't get as much opportunity to practice being more effective. To really step back and think, what are the right things that I should be doing or that we should be doing as an organisation?”?
And Mel believes the rise of AI is an opportunity to address this…
“As organisations, we need to rethink what is effective. What are the right tasks to be done? And I think there's two traits of companies that will not just survive, but excel off the tailwinds of this change.?
“The companies that understand this is the new paradigm that we're in right now and change needs to happen. And then the companies that are able to capitalise on that change effectively leverage AI to adapt and move forward.” - Mel MacMahon.
How are companies currently using AI?
“Recent research by Deloitte said that companies that were predominantly using AI for automation were actually seeing 50% lower return on investment versus organisations who are using AI for strategic benefits.
“And that’s supported by a report that IBM recently put out saying that organisations who are using AI for innovation, rather than just cost cutting, we're six times more likely to see financial gains.” - Nelson Sivalingam.
The trouble is that a lot of early AI adoption has been about being more efficient, which could mean that we’re doing the wrong things more efficiently.
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And as the data shows, we need to focus on being strategic and doing the tasks that support the business in reaching its goals.
Never start with the tech, start with the problem to be solved
“Love the problem, not the solution. And I'm a big believer in that because the problem is what we're there for, it's the motivation, it’s what we're trying to solve. And it's solving the problem that gets us the desired outcome that we want to see."
And if leveraging AI is going to help you solve that problem, go for it.
The trouble is that we’re seeing people trying to fit AI into everything.
“What will help us prioritise how we leverage AI will come down to those big, meaningful problems that we need to solve… and the organisation that will win is the one who knows the customer's problem better than the customer does.” - Nelson Sivalingam
Those fundamentals won’t change, regardless of the latest tech advancement or trend.
A data-driven mindset and good data infrastructure will help
“AI is going to do better with the more data you can provide to it… We talk about personalisation, that comes up a lot with AI, and if you’re going to personalise something, you need know about that person… you need to understand as much as you can about them.”
Start with individual information, like their performance reviews and job descriptions.
But also look at how that person fits into a team. What are the objectives of that team? And how does that team fit into the wider organisation.
“If you have the data infrastructure that's capturing all of this in a structured manner, then you can feed it into AI that really will allow you to be able to generate more personalised learning or understand what different components of an organisation need to learn or need to do in order to get where you want them to be.” - Mel MacMahon.
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