How AI is being used across your workforce: An early look
Research across healthcare, finance, and retail industries highlights opportunities — and gaps
Contributing writer
Today’s business leaders are not only bullish about AI adoption — they’re also eager to find ways to implement it for their workforces.
According to a recent report from KPMG, 72% of CEOs say generative AI is an investment priority, even in an economically uncertain time.
The excitement is understandable, but do organizations have the in-house expertise needed for the broad implementation that executives expect?
For most companies, there are still critical knowledge gaps, though some industries and personas are starting to pull ahead. Demographically, the employees who do seem to be using AI tend to have higher household incomes and have already achieved higher levels of education than employees who aren’t using AI.
The problem is that the significant investments employers are making in AI are at odds with the low percentage of their workforces currently using AI on the job.
That discrepancy puts AI investments at greater risk than companies may realize.
For any employer hoping to see their AI initiatives produce business outcomes, focusing on employee awareness, use, and sentiment toward AI is critical. To gain a better understanding of the current landscape, Guild recently surveyed employees from a range of job sectors and levels.
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Below, we share who’s leading, who’s lagging, and what leaders across the healthcare, retail, and financial services industries can do today to meaningfully prepare their entire workforces for an AI-driven future.
Healthcare
1. Healthcare has been slow to warm to AI.
Significant concerns about managing risk, maintaining patient confidentiality, and ensuring health equity outcomes have made organizations reluctant to adopt AI. As a result, healthcare employees report having fewer opportunities to use AI at work than employees in other industries.
Yet, AI does have the potential to make a significant positive impact on healthcare professionals and patients. “In healthcare, AI can create space for more connection between providers and the people they are caring for,” said Hanna Patterson, Senior Vice President of Healthcare and Applied Learning at Guild. “That can lead to deeper relationships and more time spent aligning on achievable approaches to treatment.”
2. Healthcare workers are skeptical of the potential of AI to impact their careers.
Healthcare employees generally don’t anticipate any impact from AI on their current or future careers.
3. The majority of healthcare workers don’t think they’ll need new AI skills for their current job.
Only 32% of surveyed healthcare employees saw a need to develop new technical skills for their current job as a result of AI.
For AI adoption to take off, healthcare workers — including frontline staff — will need education and support from their employers. Providing the necessary training will require significant investments in digital and AI literacy, among other measures.
"AI skilling accountability sits with healthcare employers,” Patterson said. “Teams will look to leadership for guidance, which should come from the organizational AI strategies that leaders need to develop now to ensure their workforces are ready to use AI as part of their work in the near future.”
Financial services
1. Six out of 10 financial services employees are already using AI. Unlike other industries we surveyed, most financial services employees already used AI.
2. AI use at work is twice as common among financial services employees as it is among healthcare or retail employees. The financial services industry is data-intensive. Compared to professionals in other sectors, financial services employees recognize AI's potential to streamline work through predictive analytics, risk assessment, and risk management capabilities.
3. Nearly 1 in 3 financial services employees say they need to develop technical skills to keep up with AI. Financial services employees responding to a 2023 Guild research survey said they recognized a broad need to develop skills ranging from technical to more durable.
Specifically, for soft skills, financial services employees noted a need for development in communication, teamwork, and problem solving. Of note, 12% said they needed skills for a completely different industry or field.
Retail
1. Retail employees are eager to learn about AI. Eighty percent of retail employees (including hospitality and restaurant workers) said they want to build new AI skills either for their current or future roles.
2. Although AI shifts the types of roles retail employees might consider, AI’s precise impact on career trajectories remains uncertain. Only 9% of surveyed retail employees said they’re expanding their ideas of the roles they may pursue in the future, and 0% felt that AI changed their career goals in a specific direction.
3. Despite concerns about job loss due to automation, only 12% of retail workers said they need to learn skills in a new field or industry. Results from an earlier survey could indicate employees in retail intend to stay in retail. They could also point to a broader lack of awareness of how AI may impact their jobs in the future.
Who's using AI today?
When we look beyond specific industries and focus instead on broader populations of AI users, equity imperatives become clear.
According to Guild research data, the groups of people most likely to use AI tools today are highly educated, affluent, male, white, and young.
Twenty-four percent of people with an annual household income of $100,000 or higher say they’re already using AI for work — that drops sharply to just 9% for households earning $75,000 - $99,000. Roughly half of male respondents said they have used AI tools, compared to one in five women.
The same demographic groups most likely to use AI are also most likely to benefit from its effect on their role performance, competitiveness, and ability to navigate the job market. That dynamic threatens to worsen equity gaps across race, gender, educational attainment, and socioeconomic status.
Getting and staying ahead means addressing skills gaps now
Upskilling takes time. Acting fast can help workforces build future-facing skills proactively. Here's what to do now:
1. Think of AI skilling in terms of job level.
Not everyone will need to know machine learning. Considering AI needs in terms of job level can help talent leaders identify relevant skills needs.
For example, frontline employees may benefit more from learning about AI literacy and ethics, whereas executives may need to build skills to implement AI-driven strategies.
2. Take an accessibility-centric approach to building AI skills.
Talent leaders can disrupt unintentional bias by offering AI upskilling programs that don’t have prior education requirements.
Guild recently worked with our network of innovative learning partners to release an AI skilling bundle of over 40 programs designed to meet a breadth of AI skills needs — including accessible learning options. Most of these programs do not require a prior degree, and several require no prior formal education.
3. Weigh the benefits, risks, and drawbacks of AI-assisted talent management.
There are many ways AI can support talent goals, but as with any new technology, adoption and use should be a strategic, active, iterative process — with solutions designed to improve employees’ lives.
Harvard Business Review recommends a variety of mitigation strategies for AI-related risks, including
- Ensuring diversity and representation across engineering and decision-making teams
- Examining levels of decision control (i.e., is AI making a recommendation or a choice?)
- Reviewing and building internal processes to identify and address potential biases driven by AI
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