AI training for employees: How employers can get – and stay – ahead of an AI-powered future

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The time to get started with AI training was yesterday.

There’s no getting around AI employee training. But where do you start when upskilling at scale?

In this employer’s guide, we'll cover:

→ Trends in the AI training landscape today
→ New employee survey data on AI usage and sentiments
→ How to get ahead of the crucial “hype cycle” 
→ Real-world examples of how AI can streamline frontline work across industries

Table of contents

• Chapter 1: The AI training landscape: What is AI and why do your employees need training?
• Chapter 2: Who is embracing generative AI? Beware the growing equity gap.
• Chapter 3: Getting – and staying – ahead of the AI curve: Why your entire workforce needs access to AI training today 
• Chapter 4: Real world implications of AI across industries
• Chapter 5: An equitable framework for organizing AI learning needs: Introducing AI skilling bundles

Chapter 1

The AI training landscape: What is AI and why do your employees need training?

Is generative AI as transformative as the personal computer and the internet for businesses? Are employers effectively stepping up their skilling strategies to keep up?

In this chapter, we'll cover these questions and more, plus:

→ A quick overview of the advancements in AI
→ The transformative business impact of generative AI
→ Why employers need to move quickly on employee training

What is AI and why is it such a big deal for employers? 

Before we get into our framework for AI training for employees, we first need to address what AI is. Artificial intelligence (AI) is a machine’s ability to perform the cognitive functions we associate with human minds, such as:

• Perceiving
• Reasoning
• Learning
• Problem solving
• And even exercising creativity

And it’s been around for a long time, with mainstream machine learning experiments starting back in the 1950s. 

The first large breakthroughs from those experiments were machines that we have all come to know and depend on, which perform daily tasks faster and more accurately than humans. Think:

• (1960s) Personal calculators
• (1970s) Personal computers
• (2010s) Personal assistants like Siri and Alexa 

Today, generative AI – an artificial intelligence model that generates content in response to a prompt, like ChatGPT – has the potential to completely transform the jobs we know today. And quickly. 

ChatGPT is the fastest growing application in history.

UBS study, February 2023

The rollout of ChatGPT took the world by a storm in November 2022, and in less than a year, racked up an astonishing 180.5 million users – setting world records for the fastest growing application in history.

Now, quickly building on the success of ChatGPT, AI solutions galore are inundating business leader’s LinkedIn feeds and inboxes. These solutions helping white-collar workers ideate and create original:

• Text
• Audio
• Code
• Images
• Simulations
• Videos
• …and more.

Bill Gates believes generative AI is as revolutionary as the personal computer, mobile phone and the internet itself.

Is generative AI really that revolutionary? Bill Gates thinks so. 

In his post on the age of AI, he rattles off a list of ways that generative AI is slated to boost employee productivity, becoming a white-collar co-pilot to handle daily tasks like:

• Email writing
• Managing inboxes
• Scheduling
• Document handling 
• Service 
• …and more

By 2030, activities that account for up to 30% of hours currently worked across the US economy could be automated — a trend accelerated by generative AI.

McKinsey Global Institute

McKinsey Global Institute estimates that a whopping 30% of hours spent on tasks today could be automated – a trend which has been accelerated by generative AI. 

“We’re about to see a major disruption in how everyone works, and I do think that the frontline population will be impacted most,” commented Bijal Shah, Guild chief experience officer & head of platform, at a CNBC Disruptor 50 event on AI. 

But what about frontline job displacement?

Instead of replacing jobs, we believe AI will predominantly be used to come alongside workers, freeing them up to do more high-value tasks, such as:

• Human interaction: Automate everyday tasks (merchandising, in-take paperwork, etc.) to allow more time for key human interactions that improve customer experience
• Instant data-backed recommendations: Instantly provide enhanced customer data to provide better recommendations on the phone, in-stores, or healthcare facilities 
• Strategic work: Shore up time from administrative, HR, or IT tasks to focus on strategic projects

For a comprehensive list of examples by industry, check out chapter 4. 

Bottom line? Employees need to get comfortable with AI quickly, and employers need to pave the way for this discovery.

“We’re about to see a major disruption in how everyone works, and I do think that the frontline population will be impacted most.”

Bijal Shah, Guild chief experience officer & head of platform at a CNBC Disruptor 50 event about AI

Businesses stand to gain tremendously – if they can figure out how to train their employees quickly and equitably.

While companies embracing AI have the potential to quickly become more efficient and profitable, the value of AI isn’t in the systems themselves but in how companies use those systems to assist humans. 

But employees don’t trust their employers to get them there.

The majority of workers (six in 10) believe they need to learn new skills as a result of AI, but 88% don’t trust their employer to support them in understanding the technology. 

Employers should consider this a wake-up call. 

AI demands a new type of in-the-job learning, on that is:

• Agile: Adaptable and ready to expand when new technologies emerge
• Varied: From basic to expert level training
• Equitable: Accessible to all workers in all roles
• Flexible: Ability to attend enroll in self-paced classes

The value of AI isn’t in the systems themselves but in how companies use those systems to assist humans.

But who is actually adopting AI today?

And how can employers stay ahead of the curve by stepping up their strategy and skilling investments? Read on to chapter 2 and chapter 3 to find out.  

Chapter 2

Which workers are embracing generative AI? Beware the growing equity gap. 

While AI is expected to impact the masses, AI training programs are typically only accessible to white-collared “high-potential” employees — leaving frontline workers behind.

How do employers stop a skills gap from turning into a skills chasm? 

In this chapter, we'll cover:

→ Statistics about current AI usage 
→ Why frontline workers are most likely to be negatively affected
→ How employers can turn frontline AI training into a competitive advantage

AI is expected to impact many, yet AI programs are usually only accessible for the few. 

Out of the 60% of workers who believe they will need to learn new skills as a result of AI (see chapter 1), a third think they’ll need to do so within the next year. 

But there are almost no AI training for employees in the market for workers without bachelor’s degrees — who make up the majority of all workers and more than 80% of the frontline workforce, which totals 112 million people.

Guild’s research on the AI training landscape has shown that more than half of the available AI education programs require a bachelor’s degree and they’re designed for either engineers or executives. 

More than half of the available AI education programs require a bachelor’s degree and they’re designed for either engineers or executives. 

Guild internal research

There’s very little training available for the non-tech professional – much less the frontline worker. That has to change.

AI survey results: Who is thinking about or currently using AI – and what does it tell us about equity?

Of the 5M+ eligible members that Guild serves nationwide, we recently surveyed a group of 355 members (252 of which are enrolled in programs) to ask about their sentiments toward AI and the impact they feel it will have on their careers.

Here were some of the statistics, and the unfortunate inequity that they highlight:  

AI and gender:

• Men outpace women in believing AI will require them to learn new skills by 2.4x
• Men expect AI tools to make their jobs easier by 2.4x
• Men believe AI tools will make it easier to navigate and land new jobs by OVER 3x

AI and income:

• Surveyed members making over $100k outpace their lower-paid co-workers in believing they will need to learn new skills by at least 16 percentage points, with most pay ranges clustering around only 25% saying they would need to learn new skills

AI and race:

• White members believe they'll need to learn new skills at 1.5x higher than their Black or Latinx coworkers

AI and education level:

• Members without a degree lag 12-17% in seeing the need to learn new skills tied to AI

AI tool usage is highest among younger, affluent, educated white men in financial services.*

*Guild survey of 355 members and learners, June 2023

To summarize: Higher-income, white-collar “desk” workers who see the immediate benefit from using generative AI tools like ChatGPT are keenly aware of the need to acquire new skills – especially technical skills – to better use AI and remain competitive in their roles.

As a result, AI skills swiftly concentrate at the top, and what was a skills gap rapidly turns into a skills chasm. 

And while AI usage may be highest among desk workers today, employers who figure out how to arm frontline workers with AI skills have a tremendous opportunity to improve productivity and profitability at scale (more in chapter 3) – but they have to act fast.

Keep reading to learn why.

Chapter 3

Getting – and staying – ahead of an AI- powered future: Why your entire workforce needs access to AI training today 

As excitement around generative AI peaks, employers have a short window of opportunity to build their talent.

In this chapter, we'll cover:

→ The impact of the Gartner Hype Cycle
→ Where most employers are today
→ Competitive advantages they stand to gain by investing in AI training right now

Employers have a short window of opportunity to build the skills needed for an AI-powered future. 

As with any exciting new technology, employers have a short window before the “hype” dissipates to drive employee engagement, adoption and the integration of new AI skills into daily work.  

Gartner calls this the hype cycle. 

The story goes like this:

1. Innovation triggers new excitement across industries, organizations, and populations
2. Window of opportunity opens to skill employees for the future before they become confused and frustrated on their own 
3. Trough of disillusionment when employees try their hand and early failures dampen excitement
4. Slope of enlightenment as commercially available solutions are found and ecosystems built
5. “Plateau” of productivity where the technology becomes mainstream, and employers who acted early are reaping the benefits

The window of opportunity to act – start offering AI training for employees – is now (early 2024). 

The most successful companies will be those who lean into today’s excitement to build the hard-to-obtain skills that will be indispensable tomorrow.

The most successful companies will be those who lean into today’s excitement to build the hard-to-obtain skills that will be indispensable tomorrow. 

But most employers haven’t clearly addressed the usage of AI tools to their workforces. Spoiler: They need to take a stance.

To-date, most employers/managers – and schools/professors – have not extensively addressed or provided clear guidelines for the usage of AI tools. 

And for the employers who have, the sentiment has been mixed between encouragement and discouragement, leaving employees confused and ultimately concerned for the future of their jobs. 

Executives and HR leaders have the responsibility – and the opportunity – to create a culture energized about a friendly future with AI.

Dean Carter, Guild’s CHRO and ex-Patagonia Chief People Leader, recently wrote about how HR leaders should fundamentally approach AI, notably:

• Think like a scientist: What work streams can be improved by AI? Who can we employ to run small-scale trials?
• Protect the inputs: What guardrails did we need to create for employees yesterday? How do we define proprietary or confidential data?
• Make sharing a habit: How do you ensure information about AI is accessible to all employees? How do we foster cultures where employees are excited to learn how to do their jobs better using AI?

Once the foundations are set, employers need to think about launching training initiatives during this peak window of opportunity. More on these programs in chapter 5.

Chapter 4

Implications of AI on retail, healthcare, and beyond: Freeing frontline employees for meaningful work

What implications does AI have on frontline work across industries? 

And more importantly – what are proactive ways companies can equip frontline employees with AI skills to not only improve their efficiency today but also mitigate the impending skill gaps in the future?

In this chapter, we'll cover:

→ Why employers that roll out AI for frontline workers will have a competitive advantage  
→ AI applications for frontline jobs across industries 
→ How closing the equity gap will require AI training from the frontline to the c-suite

Employers who prioritize AI training for frontline workers will be more productive and competitive. 

From retail to healthcare and beyond, proper AI training for employees can help shore up enormous amounts of time for frontline workers everywhere. In the very short-term, companies who fail to train their employees on AI will be far less productive and competitive. 

Let’s look at some of the implications that early AI training can have on various industries.

Implications of AI in retail frontline roles

Retail leaders can lean into AI to increase the productivity and accuracy of manual frontline tasks. This shores up valuable time for employees to focus on interactions with clientele at brick-and-mortar locations. Some examples of retail tasks that can be improved by AI include:

• Merchandising: Flag incomplete merchandising jobs with image recognition technology 
• Stocking: Track performance of key products, prompting employees when they need to check product displays
• Predicting demand: Help grocery stores analyze large sales data to determine which items to promote when and for how long to eliminate employee guess-work 
• Recommendations: Analyze customer behavior and provide staff with real-time insights and recommendations to enhance customer engagement

Implications of AI in healthcare frontline roles

AI can relieve overworked frontline healthcare workers by handling important, data-driven tasks, allowing employees to focus more closely on patient care, customer service, and innovation. AI can help with frontline healthcare tasks that include:

• Diagnostics: Streamline the accuracy of diagnostic and treatment processes
• Data analysis: Sift through and immediately summarize large logs of data 
• Address common questions: Quickly answer employee IT & HR questions to reduce time and money spent on administrative costs 
• Paperwork: Potentially generate discharge summaries in a vast number of languages, to reduce employee friction and misunderstandings

Implications of AI in insurance frontline roles

Generative AI’s ability to codify conversational data into a structured database will be revolutionary for the frontline insurance workforce, which communicates heavily with end-users via various mediums (phone calls, texts, emails, etc.). Employers can use AI for insurance frontline tasks such as:

• Rectifying simple claims: Use large data sets to correctly process and settle simple claims with higher accuracy  
• In-message coaching: Prompt customer service representatives (who typically have high turnover rates) on which are the next best personalized questions to ask based on prior conversations to save time and frustration
• Automate triage: Rapidly distill information from customers about their claims and route them in the right direction, allowing agents to focus on best possible outcomes

Implications of AI in hospitality frontline roles

Customer service is key in the hospitality and tourism industry, and AI can help frontline hospitality workers: 

• Booking rooms & experiences: Use customer history and current deals to help recommend and books personalized travel experiences, freeing up countless hours for on-property travel agents
• Streamlining guest reviews: Take the onus off of the hospitality worker to constantly be on top of finding and responding to online reviews and automatically generate responses 
• Upsell with personalized recommendations: Use guest purchase history and preferences to come up with personalized recommendations to upsell, helping frontline workers meet and exceed quotas

Bottom line? While there is a serious gap between the current AI training that exists today – primarily for white-collar “desk” workers – and the 82% of Americans that are in frontline roles and could benefit from AI, there is also a serious opportunity for employers that choose to open the AI floodgates for their entire workforce. 

Closing the equity gap in AI skilling is not only the right thing to do, it is critical to stay competitive when we inevitably hit the “productivity plateau” in the not-so-different future.

From the frontline to the C-suite: Companies that deploy AI training for every level of their workforce will see serious business, talent, and ESG advantages.

Chapter 5

An equitable framework for organizing AI learning needs: Introducing AI skilling bundles

Companies need to manage the culture around AI in their organizations and upskill their entire workforce. 

Employees want to understand – and feel good – about what’s happening, and for doors to open to new opportunities.

AI skilling bundles are designed to meet these strategic needs.

In this chapter, we'll cover:

→ Why AI training should meet employer and employee needs
→ The foundational elements of good AI investments
→ How Guild’s AI skilling bundles provide equitable learning opportunities to employees at every wage-earning level

How can employers define the culture of AI as we head toward a job revolution?

The job evolution is coming. 

With the 12M job switches that may be needed by 2030 – and the $8.5T unrealized revenue caused by talent shortages – we need to ask ourselves as a country: who is preparing the workforce for the wave to come?

Employers are largely defining the culture around AI training for employees in this country. Their decision to treat it with either excitement or skepticism will have great ripple effects on their business performance when we reach the “new normal” (or according to Gartner, the “plateau of productivity”). 

In the last 12 months alone, application submissions for AI programs have skyrocketed 800% for employer partners who offer AI courses in their Guild catalogs.³ 

So we leaned into the numbers. 

How can we accelerate the proactive – and equitable – adoption of AI to help businesses and their employees thrive?The first step is to identify what our employers and employees need, and then help them meet in the middle.

What do employers and employees need out of their AI training? 

Innovative employers don’t want to just “check the AI box”. They are taking a good look at their business needs and their employees' desires to bolster their employer value propositions and make them a distinguished company to work for.  

Here’s a quick glance of what’s top-of-mind for both parties:

What employers need

• Manage culture: Assess growing fears around how AI is changing work
• Upskill the whole business: Leverage AI training for employees focused on productivity-driving solutions across their workforce - not just mid-career workers. 
• Integrate AI into products and solutions: Drive both existing and new lines of business
• Develop leaders: Lean on strong leaders to effectively deploy emerging AI technologies

What employees need 

• Hone an understanding: Grasp what is happening and why it matters
• Make their work easier: Learn tools and skills that allow them to do their job faster and better
• Open doors: Access new, high paying career paths by expanding the technical skills they already possess
• Strategic awareness: Understand how AI is changing the business world to develop pattern recognition and drive business strategy

Keep in mind that different employee populations have different AI needs – but the programs in market serve primary leaders and executives. See the differing needs of employee populations in the graphic below.

The top 3 foundational elements of effective AI skilling investments

Let’s define our top 3 objectives:

• Objective #1: Skills-adoption Upskill technical and non-technical employees with the necessary skills to understand, work with, and leverage AI effectively to boost performance in their existing roles or move into other positions
• Objective #2: Employee engagement  Engage and retain employees through programming that helps them navigate AI transformation effectively 
• Objective #3: Accessibility Equitably future-proof your workforce by ensuring all employees have access to relevant programs that are aligned to their unique needs and that can be agile as technology evolves

To reach these objectives, our experts suggest implementing these foundational elements in your AI skilling investments:

1. Put employees in the lead 

Offer employees what we call a “skills garden”, or a suite of curated options that helps get them where they need to be. Refrain from an “assembly line” approach, requiring all workers in a certain role to take the same upskilling courses. 

Allow employees to self-serve given their own career ambitions. This will lead to higher employee engagement. 

2. Focus on AI literacy training

A focus on AI literacy will be required to prevent further workforce equity gaps. 

As we covered in chapter 2, the highest adoption of AI is by white males, and at least half of AI training for employees currently requires them to have a bachelor’s degree to enroll. 

Offering accessible programs will be key to future-proofing your entire workforce.

3. Develop durable skills

The most future-proof skills of all won’t be technical skills, but the ability to learn and adapt.

You should focus on building adaptive learners so that they can build their “growth muscles” versus skilling them with routine skills. 

We need to rethink what is being taught and how to provide durable skills.

The equitable AI skilling framework: Introducing Guild’s AI skilling bundles

Combining the foundational elements listed above, Guild recently launched our AI skilling bundles across four core learning areas: 

• AI Fundamentals: Focuses on AI literacy, ethics, and implications.
• AI in Practice: Teaches how to understand and use AI tools.
• AI Expertise: Covers building and scaling AI technologies in the business environment.
• AI for Leaders: Instructs on creating and implementing strategies for AI in business.

This framework helps employers: 

• Organize their AI learning needs
• Provides for a wider range of education options
• Accommodate their entire workforce – from frontline to c-suite – with curated, high-quality programs

Leveraging our learning marketplace, we quickly expanded our AI offerings to ensure applicable content for all learning areas and innovated with partners where necessary to fill gaps. 

This comprehensive strategy ensures that employees across all levels and departments can effectively engage with AI technologies.

This comprehensive strategy ensures that employees across all levels and departments can effectively engage with AI technologies.

The window of opportunity is now. If you’re interested in how you can launch effective AI skilling at scale, reach out to our education experts below.