There’s a lot of talk about AI in Learning & Development (L&D), and many people use it, so it’s not just talk. But is the talk and execution of AI for L&D working, or is it fast-tracking the way to “learning” mediocrity?
I’ll be looking at things from the perspective of narration for eLearning, which seems to be one of the biggest uses of AI that I’ve seen. Other big uses include creating images and scripts for eLearning.
But narration is the focus here. That is, putting a script into an AI narration tool (that uses synthesized voices), and it spits out audio for eLearning. Updates to Articulate’s Storyline make it extremely easy because this capability is built right in.
But is that all good, or is it mostly bad?
That entirely depends on how things have been done in the past. Were they already pretty bad, and you’re moving from one bad narration to the other, or were things pretty good, and now they’re getting boring and robotic?
There are many benefits to AI voiceover for narrations, but I believe there are far more drawbacks than benefits. AI narration only helps eLearning that already had poor narration and bad scripts to boot.
While it undoubtedly offers the efficiency of standardization, is it inadvertently fast-tracking the production of dull, lifeless training materials that fail to resonate with people?
Imagine sitting through a training session where every voice and every module sounds eerily similar—uniform, impersonal, lacking the dynamism that sparks curiosity and engagement. The innovation behind L&D using AI, particularly in voiceover narration, seems promising at first glance, offering seamless consistency and scalability.
Is AI making it easier to create dull and lifeless eLearning and making more narration worse?
However, the real question beckons: in our pursuit of efficiency, are we sacrificing the depth and richness that storytelling brings to corporate training? Are we losing the very essence of what makes training relatable and memorable?
This post focuses on AI’s role in L&D and eLearning narration specifically, examining whether it’s truly solving challenges or merely glossing over them with a coat of technological convenience.
The Rise of AI in Learning and Development
Artificial Intelligence (AI) has emerged in various industries for better or worse, and Learning and Development (L&D) is no exception. Integrating AI into L&D processes has opened up new possibilities (both good and bad) for training and education.
With its ability to analyze vast amounts of data, identify patterns, and make intelligent decisions, AI has the potential to make decisions that humans can’t.
One key area where AI is being heavily used is eLearning narration. Traditionally, creating voiceovers for eLearning was an imperfect task. You might hire an expensive professional or have someone in-house willing and able with the right (or maybe even not so right) equipment.
One of the most used features of AI for eLearning is synthesized voiceovers.
With AI-powered narration tools, all eLearning developers have access to the same consistent and always available voices. There is no reliance on an employee who may or may not work there anymore. With a little tweaking for special words, a voiceover can be available within minutes.
This automation saves time and offers consistency across different modules, courses, and even departments. While standardization is undoubtedly beneficial in terms of efficiency and scalability, it raises concerns about the impact on engagement, for example.
Using AI in eLearning narration may result in a homogenized experience where every module sounds similar. This lack of diversity can lead to disengagement and reduced learning outcomes. To be fair, a person can also do that, but it truly depends on what AI narration is replacing and the overall goal of your department.
The Impact of AI on eLearning Narration
AI-driven narration tools have made creating voiceovers for eLearning modules easier than ever. Want an English speaker with an Indian accent? Done. Need a British English speaker? Easy. Also, Jessica from England in AI is always available and will always have a consistent voice.
This level of automation has undoubtedly streamlined the production process for eLearning materials. But at what expense?
There’s a trade-off between efficiency and personalization.
While AI-generated narrations may sound fine, they’re typically stiff and boring. Even when the AI company advertises emotion, it’s typically pretty cheesy and doesn’t express the same feeling as a human is capable of.
AI is making it faster than ever to produce eLearning with dry lifeless narration that also doesn’t hit the business mark.
Yes, AI narration can be extremely boring and sound monotonous, and even with the best attempts at emotion, it typically falls pretty flat. If a script is well-written with emotion, silliness, and various other human traits, AI has a nearly impossible time translating those into quality voiceovers.
So, it ultimately comes down to this:
AI narration is perfect for replacing a poorly written script with dry and monotonous delivery from a real person, but it absolutely can never compete with a well-written script that has human emotions written into it and is delivered by a voiceover artist who’s good at what they do and delivers the true intent of a quality-written script.
Phew, that was a mouthful, but it had to be said. AI narration sucks when competing with good scripts and good people. Here’s the simplistic breakdown:
Poor script + AI = Bad
Good script + AI = Bad
Poor script + bad human narrator = Bad
Poor script + good human narrator = Mediocre
Good script + good human narrator = Magic
AI will never come close to a quality-written eLearning script with a good human narrator recording the voiceover. Pure magic happens with that mixture, and it’s the way all eLearning should be delivered.
The engagement of a script and voiceover of high quality will be through the roof. People connect with you, they feel like you’re talking to them, they learn better, and the outcomes are almost always through the roof.
Unfortunately, good quality wasn’t what most eLearning departments worked with in the olden days before AI. That’s unfortunate.
We’ve gone from poor quality that should never have been the reality to even more poor quality delivered by our emotionless AI overlord (or soon-to-be).
Human narrators can infuse emotions, intonations, and nuances into their delivery, capturing people’s attention and creating a connection. AI-generated narrations, on the other hand, can sound robotic and monotonous and fail to engage people emotionally.
Standardization vs. Personalization: Striking a Balance
The debate between standardization and personalization in eLearning is not new. While standardization ensures consistency and efficiency, personalization allows for a more tailored learning experience that people learn from (as long as it’s high-quality).
When people connect with your message, the person delivering the voice, and the content they see in an eLearning course, magic happens. People learn instead of consuming mindless drivel because they were told to.
AI-powered narration tools have undoubtedly brought standardization to eLearning narration. Organizations can now ensure that every module has similar voiceover quality (for better or worse), eliminating variations caused by human factors. Not only that, but course updates are now a breeze because the narrator is always there no matter what. And, of course, we know that keeping eLearning up-to-date is essential.
This standardization also enables scalability, as organizations can easily create voiceovers for multiple modules without relying on external resources. But there’s always a downside, and the downside with AI narration is a doozy, which I think isn’t worth it.
AI makes voiceover standardization easy but at what expense?
The downside of this standardization is the potential loss of personality and storytelling elements. People are more likely to connect with content delivered in a relatable and engaging manner. That takes a quality script and narrators who don’t drone on with a monotonous voice.
Human narrators can bring stories to life through their unique interpretations and expressions. AI-generated narrations may lack this personal touch, resulting in a less immersive learning experience.
So, if a company’s Learning & Development department is already churning out poor-quality eLearning with badly written scripts and bad narration, AI isn’t going to do much harm. But then I’d argue, what’s the point anyway?
That’s an eLearning department that I could argue is simply churning its gears, creating useless junk, and trying to justify it with the number of courses developed and the number of employees taking training. What good is that? It’s likely better just to cut that work out entirely and save a lot of money.
However, if a company produces high-quality eLearning with high-quality narration, AI can potentially destroy the good that eLearning is doing.
Engaging People: The Role of Storytelling in Training
Quality eLearning starts with the right goal and, secondly, a quality script and narration. Storytelling has been an integral part of human culture since time immemorial. It has always been a powerful tool for conveying information, engaging emotions, and fostering connections between individuals.
In corporate training, storytelling is crucial in capturing attention and facilitating retention. With the right goal for a course that will benefit the company, storytelling, and scenario-based learning will be invaluable.
While AI-driven narration tools offer efficiency and consistency, they fall very far short of what truly matters: connecting with people and drawing them into the story. A quality script and human narrators inject life into training content by using humor, emotion, and empathy to create a captivating narrative.
Although technically proficient, AI-generated narrations cannot evoke emotions and create a memorable learning experience. Even the best of them, with their best effort to mimic human emotion, are pretty bad at it. It makes it a lot easier to create poor-quality eLearning. That’s about it.
The Psychology Behind AI Narration in L&D
While there’s not much research easily available about AI narration in training, there is some. One we found was done on Chinese language speakers, which means it doesn’t directly apply to the English language but should still be considered.
In one study not in the training field but still important, Chen Gong found that “… listeners’ cognitive activity was greater when listening to the audio of a human voice newscast than AI synthesized voice broadcast…”
The human voice is more engaging and persuasive than synthetic voices generated by AI, no matter how similar they become. While most people may not be able to distinguish, our brains likely still will activate differently when exposed to a synthetic voice compared to a real person.
The human voice is much easier to connect with than AI even if we may not know it.
Human voices can convey emotions, build trust, and establish a connection with learners. AI-generated narrations may be efficient and consistent, but they fail to elicit the same level of emotional response.
AI narration will never be able to compare to a well-written eLearning script paired with a quality voiceover artist. However, it will be on par with poorly written eLearning scripts and poor-quality voiceovers.
Unfortunately, AI is typically replacing this, something that likely shouldn’t exist in the first place and is doing more harm than good.
Navigating Efficiency and Effectiveness in Training Materials
Organizations should strive for efficiency and effectiveness when it comes to training materials. The problem is that you can’t pair quick with quality, which L&D often fails to see. There is no way to develop eLearning quicker while also maintaining effectiveness. As an industry, there’s a whole bunch of quicker development going on with even poorer quality than before.
While AI-driven solutions offer unparalleled efficiency by automating various aspects of content creation, that’s not always the best method. There are limited places where AI can improve L&D rather than make it quicker to make poor-quality training.
A well-designed training program goes beyond standardized voiceovers or automated content generation. It takes into account business needs, training people can connect with, and a human touch of story, humor, and all those beautiful emotions that AI will never be able to duplicate.
Impactful training can only come from quality, which can be done efficiently but can’t be done quickly. Quality is difficult to achieve, and many L&D departments aren’t making the cut. They’re simply doing poor-quality work even faster using AI and producing more poor-quality training that doesn’t help people learn their jobs better.
User Experience: Assessing People’s Receptivity
Assessing employee’s receptivity to AI narration is essential before incorporating AI-driven solutions into eLearning. Doing it because it’s easier for L&D is a huge red flag. It should only be done if there aren’t many drawbacks for employees, and it also provides a significant enough boost for L&D.
While standardization offers benefits such as consistency and scalability, gauging people’s feedback on AI-generated narrations is essential. Is L&D simply throwing it onto employees without knowing if they hate it?
Learning & Development is about helping people do their job better. Does artificial narration help employees learn better and do their job better?
Talk to employees and survey them on the narration. Is feedback glowing for many courses where people love the narration, then AI is introduced, and that love is gone? I know in many of the courses we develop at techstructional, the personality and narration are huge pluses. It would be a travesty to lose that connection and never even know how it affects employees.
By actively involving employees in the process, organizations can refine their approach to AI-driven narration and make sure it’s not having a negative impact.
Future Prospects: Evolution of AI in Learning and Development
There may be a future for AI in L&D, but I’m not sure it should have the impact or approach currently being pursued. While AI may get better, it’ll never achieve the personality of a person who does a good job; it will only continue to get better than a person doing a poor job.
It’s unfortunate that L&D still produces poor-quality training, though, and it’s a travesty that AI narration is often compared to this poor quality and only held to its standard.
As technology continues to advance, AI-driven solutions will become more sophisticated, offering enhanced personalization capabilities while remaining efficient. Again, they’ll never achieve the same level as high-quality writing and narration, though—not even close.
Wrap Up
The rise of AI in Learning and Development has undoubtedly brought about significant changes in how we approach training in a corporate environment, for better or worse. There are good uses for AI, but narration isn’t one of them.
There are efficiencies that L&D can explore and achieve, but a lot of quality and effectiveness are lost when synthesized voices are used for narration. To be fair, a lack of quality also comes from poorly written scripts that don’t have the personality needed to help employees connect.
Ultimately, it shouldn’t always be about what’s easiest for L&D but what’s best for learning outcomes and employees. There are other places where AI can be used without interfering with the effectiveness of eLearning, but narration isn’t one of them. It can potentially do quite a bit of harm and waste much more time than it saves.
If you want to explore how some of our eLearning courses are written to incorporate stories and personality, check out our course on starting a Microsoft Teams meeting. When you’re ready to work with instructional design consultants who strive for quality and effectiveness, schedule a free consultation.