How AI agents will transform the frontline employee experience

Since 2000, the joke about AI was that it was ‘shorthand for technology we don’t have yet.’

In 2025, that joke no longer applies. While we may still be far from a General Artificial Intelligence, AI in its broader sense is now having a real impact on how humans work, every day. In doing so, it’s already bringing significant value to end users and the wider business.

For back office ‘knowledge workers’ in particular, recent AI developments have augmented employees’ capabilities, transforming the process of completing day-to-day tasks. With tools like ChatGPT, workers are now able to quickly generate ideas, debug code, produce draft content, and much more. 

When it comes to frontline work, automation has been baked in since the industrial revolution, and AI already sits at the heart of many frontline systems and tools (think manufacturing robots, or retail inventory management tools). 

Yet frontline employees frequently lack access to more recent developments which would allow them to interact with AI agents to augment their own thinking, problem-solve, and access information more easily.

Businesses who can successfully put these innovations at the fingertips of frontline end users will unlock further value. To help, we’ve put together this guide to AI agents and the frontline workforce, covering their benefits, where they can be used to optimise frontline work, and how to overcome common barriers to their deployment. 

Let’s dive in.

AI is an umbrella term, referring to the ability of computer systems to simulate or replicate aspects of human intelligence or human behaviour. 

For our purposes, that doesn’t mean a computer that has the full spectrum of human cognitive capabilities (artificial general intelligence). Thankfully, we’re a long way off from the robot uprising.

Instead, AI refers more broadly to technologies able to complete tasks that rely on information comprehension, problem-solving, reasoning, learning, and/or decision-making. 

Types of artificial intelligence

With AI technology only recently making real strides, many of the commonly accepted schemas for understanding artificial intelligence can be hard for businesses to apply.

In 2018, PWC offered a more useful model that remains relevant. Its AI Quadrant breaks existing (and future) artificial intelligence technologies down into four categories based on their level of human involvement and their ability to learn:

The left column of PWC’s model brings us onto the next big thing in applied artificial intelligence: Agentic AI. Tech CEOs and industry media alike predict that 2025 will be remembered as the ‘year of the AI agent.’

How do AI agents work?

AI agents are a form of automation that can perform tasks without human involvement. As such, they constitute either automated or autonomous intelligence, based on their ability to adapt, learn, and create new ways of working.

While some AI systems incorporate machine learning, it's automated, hard-coded AI agents – or what IBM’s Maryam Ashoori calls ‘LLMs with function calling’ – that currently make up the bulk of practical AI agents.

AI agents, natural language processing (NLP), and large language models (LLMs)

Where the input is text or speech, agentic AI makes use of natural language processing in order to reach its outcome. 

Put simply, NLP is the technology which allows AI agents to interpret human input – to process natural language. It encompasses methods which enable a computer to ‘read’ a request and ‘understand’ its intention, forming the basis of many virtual assistants, chatbots, internal support agents, and voice-activated tools like Siri. 

Under this umbrella sit LLMs like ChatGPT. Large language models are a development in natural language processing which allow AI agents to interpret inputs more effectively, handle a broader range of tasks, and adapt to new tasks with minimal retraining.

Automated intelligent agents vs. autonomous intelligent agents

Automated, hard-coded AI agents are more common than autonomous agents because they are deterministic – they guarantee a fixed output given a set of inputs:

Autonomous adaptive systems, on the other hand, are non-deterministic (or ‘stochastic’); inputs can result in a wide range of possible outcomes. This introduces risk – especially if the agent cannot accurately judge intent.

For businesses to adopt an AI agent, it must be able to do three things:

• Accurately interpret user intent from unreliable or partial human prompts

• Return deterministic and reliable results

• Ensure data privacy and security while doing so

As a result, these systems are largely theoretical at present. Meanwhile, the combination of both power and reliability makes other intelligent agents a valuable addition to frontline workflows.

In 2024, Professor Yasmin Weiß declared that AI at work was good for ‘everything that’s dumb, dull or dangerous.’

When deployed effectively, AI agents can enable businesses to:

Automate tasks

AI and automated technologies minimise or replace human intervention for dangerous, low-value, time-consuming, and/or repetitive work. In doing so, they can save time, reduce errors, and increase worker safety. 

Optimise ways of working

AI agents can help streamline existing workflows, removing unnecessary steps that typically require human input. In doing so, they reduce the friction associated with accomplishing tasks, simplifying work for human agents.

Improve process governance

AI and automation are capable of a much greater level of consistency compared to human agents. As such, they help businesses ensure that the tasks and processes that should happen, do happen – regardless of external circumstances. 

This is especially valuable in fast-changing environments like frontline-dependent industries where circumstances can quickly become more demanding and resources such as staffing levels can vary day-to-day. 

Improve quality of work

The consistency of automation and AI agents doesn’t just ensure that work is always done – it ensures that it’s always done correctly. By reducing the need for human intervention, they also reduce the impact of human error.  

Surface knowledge and resources

While many of the business benefits associated with AI agents centre around completely automating certain aspects of human work, much of their business value lies in how they can augment human intelligence. For many businesses – especially in frontline-dependent industries – it’s not that the information and tools required to do the job consistently and to a high standard don’t exist. It’s that this collective intelligence is difficult to find and/or access. 

Armed with access to the systems that hold this information, AI agents can help surface knowledge and resources to be used by human agents, ensuring that where human input is indispensable, it’s always informed by the most accurate and complete information.

Frontline workplaces face distinct challenges that harm the deskless employee experience and put downward pressure on productivity. 

These challenges include:

• Inefficient and ineffective communication

• Existing skills gaps in the workforce and the threat of further brain drain 

• Limited access to training resources

• Inconsistent and/or incomplete onboarding processes

• Poor feedback mechanisms between the business and frontline employees

• Low worker satisfaction, engagement, and retention 

AI agents’ ability to reduce friction, increase efficiency, make resources readily available, and empower human agents with better information make them especially well-suited to these frontline work environments.

With the challenges facing the frontline workforce in mind, where can automation and intelligent agents be deployed to best improve or optimise the employee experience?

Here are three key focus areas:

Onboarding and training

The challenge

According to Flip research, less than half of frontline employees (49%) received proper training for their current role. This doesn’t mean that they’re left to fend for themselves, though. Instead, onboarding and training takes place on an ad hoc basis, with 79% of managers spending a lot of time onboarding new team members. 

These challenges onboarding and upskilling workers have far-reaching impacts from safety and compliance to productivity and retention. Nine out of ten frontline managers report missing targets every year due to a lack of skills on their team. 

How AI & automation can help

Automation can ensure that existing resources and training materials are reliably delivered to the right employees at the right time. This reduces pressure on frontline managers and human resources, and avoids the training and onboarding gaps that inevitably result from ad hoc approaches. 

Communication and knowledge management

The challenge

According to Flip research, 33% of frontline employees said poor communication impacts their work quality and/or productivity, and 40% of employees say they find it difficult to get quick answers and help. 

This leads to workers spending an average of 14 hours a week helping coworkers. That’s more than 18 weeks of lost productivity per employee, costing their employers five-figure dollar sums per employee per year. 

How AI & automation can help

The information that employees need in order to work productively already exists – it’s just that finding it can require a wild goose chase. AI agents can help surface that information on demand, making it accessible to workers from the frontline.

Recognition, appreciation, and feedback

The challenge

According to Flip research, feeling recognised and appreciated emerged as one of the best predictors of an employee’s engagement. Employees who feel valued in this way are 8.5 times more likely to be satisfied with their job, and over three times more willing to go the extra mile at work than their peers. 

Unfortunately, less than half of frontline workers (47%) feel recognised or appreciated, with a fifth admitting to only doing the bare minimum at work. 

How AI & automation can help

Intelligent assistants can embed recognition and appreciation processes into business-as-usual, building a culture where employees feel valued without extra human effort.

Deploying any solution – let alone emerging technologies – is often easier said than done. Reaping the benefits of agentic AI on the frontline requires overcoming objections to get buy-in elsewhere in the business – both from other functions (e.g. ExCo, IT, Operations), and from frontline workers themselves. 

These objections are likely to include…

Overcoming objections from across the business requires a combination of selecting the right software tools, clearly articulating their purpose and value, addressing concerns proactively, and managing change effectively. Though good vendors will be able to provide you with support convincing internal stakeholders, here are some pointers to help you make the case for AI-powered software tools:

AI based agents have revolutionised the world of work for office-based employees. Now, they have the power to transform the frontline employee experience in the same way. 

By automating manual processes, simplifying complex tasks, and surfacing existing resources, AI agents remove friction for frontline workers. In doing so, they can help businesses boost productivity, increase engagement, and reduce employee turnover. 

In order to reap these benefits, however, businesses must deploy AI agents in the right way. That requires a clear use case, thoughtful selection of software tools, and enthusiastic buy-in from stakeholders in both the back office and the frontline workforce.