This blog explores whether AI in learning and assessment can be trusted. Drawing on insights from Sha Liu, it looks at:
the opportunities AI brings,the concerns that hold back wider adoption
the questions L&D teams should ask when choosing AI tools
practical ways to build trust across the organisation
Reading time: 4
88% of L&D and HR professionals say AI and technology are already shaping their learning strategies, but only 38% of organisations currently apply it to track progress and assessment. That shows the potential, but also why trust cannot be assumed.
What benefits can AI bring? Where should L&D be cautious? But most importantly, can organisations trust AI at all? These questions don’t have simple answers, that’s why we interviewed Sha Liu, Test Development Researcher (Productive Skill) at the British Council, who works closely with organisations on AI-enabled learning.
She shares her takeaways on where AI adds value, where concerns remain and what L&D leaders should consider before trusting these tools.
The opportunities AI brings to workplace learning
Let's start with the positives. AI is already making a difference in how people learn at work and Sha points to several areas where the benefits are clear:
Scalability and personalisation
AI can reach large groups of learners at the same time while still tailoring support to the individual. Sha describes it as ‘having your personal tutor geared towards your own level and your own preferences 24 hours a day.’ That combination of scale and personalisation makes learning more flexible and relevant. It also supports engagement, since learners are more likely to stay motivated when the content feels designed for them.
Accessibility and confidence
AI can make learning more accessible by giving learners unlimited time to practise and review at their own pace. Some may also feel more comfortable experimenting with a chatbot before sharing ideas with peers or a manager. This flexibility supports confidence building, particularly for those who prefer to prepare in a low-pressure setting.
Instant feedback
AI tools can provide feedback in real time, helping learners understand their progress straight away. This does not replace the value of human guidance, but it can complement it by giving quicker pointers that learners can act on immediately, while teachers and trainers focus on more in-depth support.
The concerns slowing down AI adoption
But, despite all the benefits, why are organisations still cautious? In Sha’s words, trust needs to be ‘informed trust’ and there are good reasons for hesitation:
High vs low stakes
AI can be helpful in low-stakes settings such as guiding practice, supporting feedback during learning or formative assessment during courses. It can also work well for pre and end of course benchmarking. However, when it comes to high-stakes assessment, such as tests that allow university admission or immigration for work or study, confidence can drop sharply.
Bias and fairness
Some AI tools still show accuracy gaps. For example, automatic speech recognition has been found to perform less well with certain language backgrounds, which can lead to unfair results. For global organisations, this can raise concerns about equal opportunities in assessment.
Privacy and data safety
There is still uncertainty about how learner data is stored, shared and used to train AI models. Many leaders want clear safeguards before they feel comfortable integrating these tools at scale.
Impact on autonomy
Another concern is the risk of overreliance. Sha notes, ‘It’s like all of a sudden, I can’t work without the scaffolding of AI tools. That’s definitely not the future we want to step into.’ So, how can trust be earned?
What L&D teams should look for when choosing AI tools
Well, first of all trust is built on knowledge. Yet only 30% of HR professionals say they’ve had job-specific training in AI. This shows why many organisations are still unsure about how to use these tools safely and effectively. That’s why, Sha suggests some key questions to ask yourself before adopting AI in your organisation:
Does the technology really fit the learning purpose?
Not every AI tool is built for the same outcomes, so you need to check alignment with your goals before investing.
Do I feel safe enough about how my learning data is stored and used?
Trust depends on clarity. You should ask whether data is anonymised, how long it is stored, who has access to it and whether the provider complies with local and international privacy rules.
Is the tool backed by solid learning theory?
Sha stresses that AI in learning should be guided by educational theory and ideally validated by research, not just adopted because it is new.
Building trust inside the organisation
Once you are on board, how do you bring the whole organisation with you? Trust in AI tools grows when teams can see and experience the benefits directly and there are three practical steps that can help. Involve learners early: start with pilots or small trials so employees can test the tools in a safe environment. This builds confidence and gives you valuable feedback before scaling up.
Share the results: collect data on engagement, progress or time saved and show it to stakeholders. As Sha puts it, ‘Usually data speak for themselves. If we can prove benefits, that would be a good way of building trust.’ Build AI literacy across roles: not everyone needs the same depth of knowledge, but giving teams a basic understanding of what AI can and cannot do helps reduce scepticism and misuse.
Looking ahead
So, should you trust AI or not? The answer, as Sha puts it, is both yes and no. At least at this stage, L&D should be AI-assisted, AI-enabled, but not AI-driven.
That means using AI with care. Start small with pilots, be clear about how data is handled and give teams the training they need to feel confident. Used well, AI gives the opportunity to make learning quicker, more personal and more engaging, while keeping people at the centre.
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