This is the fourth article in our 10-part series on the key questions posed by CHROs and senior HR leaders about AI implementation. The series explores the implications for work, talent, trust, ethics, regulation and human connection. Each article stands alone, and together they build a practical view of what responsible, commercially useful AI adoption requires. In the interests of transparency and openness the data sources for all ten articles are provided at the end of each article.
Key points:
- If AI ambition is ahead of workforce adoption, employees will rarely or never use it.
- AI usage is uneven, with white-collar workers far ahead of frontline and production teams.
- Most current use is basic.
- The biggest barrier is not technology, but guidance.
- There is a lack of policy guidance, training and communication.
- Clear communication drives confidence, making employees far more likely to feel prepared and comfortable.
- AI literacy is achieved through upskilling, practical guardrails and ‘Centers of Excellence’.
- “Nudgetech” can help adoption, by prompting better AI use in the flow of work rather than through heavy training.
Despite the high-level strategic prioritisation of artificial intelligence within the corporate boardroom, there is a disconnect between executive intent and frontline workforce execution. This disconnect manifests as an adoption and awareness gap that throttles return on investment. Interestingly, according to Gallup, in the U.S. nearly seven in 10 employees report that they never utilise artificial intelligence in their professional roles, a statistic that remained stubbornly and essentially unchanged from 2023 to 2024. The utilisation that does exist is highly bifurcated by job type and socioeconomic class; while 81 percent of frontline and production workers never utilise the technology, 46 percent of white-collar workers do, with 15 percent of the latter group reporting at least weekly usage. Despite the hype there is some way to go before there is widespread and consistent usage.
When employees do engage with these systems, their primary use cases are generally elementary, focusing on generating ideas (41 percent), consolidating disparate information (39 percent), and automating highly basic administrative tasks (39 percent). The root cause of this failure of adoption is a deficit of communication, guidance, and training. Currently, 70 percent of employees explicitly state that their organisation has zero established policies or frameworks governing the acceptable use of these technologies at work, and nearly half of the workforce currently experimenting with these tools independently have received no formal training from their employers. This raises all sorts of ethical concerns about the way data is being used and what is being uploaded into the cloud to become widely available to anyone.
Communication is a powerful catalyst for adoption: when an organisation communicates a clear, coherent strategy, employees are nearly three times as likely to feel prepared for the transition, and 4.7 times as likely to feel comfortable integrating the technology into their daily workflows. Given what we know about communication and behaviour change this, perhaps, is not surprising. Communication helps manages expectations but it is training, coaching, mentoring and centres of excellence that will help people understand ‘how’. Companies leading the charge on awareness are establishing dedicated, cross-functional AI Centers of Excellence and actively running comprehensive literacy and upskilling programs. To foster organic adoption, some companies are experimenting with "nudgetech", an emerging category of hyper-personalised, algorithmic prompts delivered directly within the flow of work. These methods foster positive behavior change without requiring heavy, out-of-context training modules that disrupt daily productivity.
However, it is a change in the context, such as the operating model that will really drive the benefits. But this change in context in the absence of some form of people development underpinned by clear communication will fail to deliver the value AI can deliver.
Questions you may want to think about:
- Where and how are you looking to learn AI and it’s ecosystem from?
- Are we inadvertently forcing our workforce to independently navigate, and potentially compromise corporate data just to keep up with their daily workloads?
- How can we design tailored AI literacy initiatives to ensure our entire workforce is upskilled, rather than allowing an internal digital divide to form?
- How can we move away from traditional, heavy training modules that disrupt productivity, and instead leverage strategic communication, AI Centers of Excellence, and "nudgetech" to build capability seamlessly within the daily flow of work?