With all the buzz surrounding AI these days, it's no surprise that many business leaders are still deliberating over the big questions: Can we trust it? Is it reliable? Is it more hype than help? And perhaps most importantly, when it comes to making an investment decision, is the juice worth the squeeze?
Of course, these are all valid concerns, and we hear them all the time. While early adopters may be touting some big wins, others are taking a more cautious approach, unsure whether AI is truly ready for prime time or just another shiny object that overpromises and underdelivers.
If you find yourself in the skeptical camp, you're certainly not alone. However, you might be surprised to learn just how many mature, battle-tested AI models are already out there ready to be put to work in practical, targeted ways. We're not talking about far-off, futuristic scenarios here. Instead, we're talking about real-world use cases where AI is quietly handling repetitive tasks, surfacing insights that often go unnoticed, and generally helping teams work smarter.
In this article, we’ll take a closer look at what AI transformation projects really look like in the real world. We’ll work through how to build a strong business case for AI automation, separate the real opportunities from the hype, and show how the right strategy can make a real difference to your bottom line. By the end, you’ll have a clearer picture of how to put AI to work in ways that actually move the needle for your business.
Capacity Gaps & AI as a Workforce Multiplier
Since the dawn of business, organizations have been continually asked to do more with less. That usually means trying to balance an equation with fewer people, tighter budgets, and shorter timelines on one side, and ever-growing expectations on the other.
For decades, the go-to business strategy was relatively straightforward: gain a competitive advantage, scale it up, and defend it for as long as possible. Then, once you found something that worked, the name of the game was efficiency. In other words, squeeze every last drop of value out of it before the next disruption hit.
As Eric Ries put it in The Lean Startup:
“The old management paradigm assumed that you could figure out the one best way to do something and then just keep doing it.”
That approach made sense in more predictable, slower-moving markets. But today, most organizations operate in a constant state of flux. Market conditions shift overnight. Customer expectations evolve by the minute. And the “find it and freeze it” mentality simply doesn’t hold up.
In this new environment, agility is everything. The shelf life of any competitive advantage is short, and the ability to adapt quickly has become a defining trait of successful organizations. That’s why many are moving away from rigid systems designed for stability and toward flexible tools built with agility in mind.
Bringing this back to the topic at hand, AI automation fits perfectly into this new way of thinking. In this new paradigm, it’s not about locking in a single best practice, it’s about equipping your team with agents to help them move faster, learn from what’s working, and adjust on the fly. It creates space for experimentation, accelerates what works, and helps your teams pivot without adding overhead.
OK, OK, that's enough business philosophy. What say we put these theories to work with some real-world scenarios? While it’s fun to wax poetic about agility and disruption, what really matters is how this all plays out on the ground within your organization. In the next section, we'll roll up our sleeves and look at how AI automation is being used right now to solve everyday business problems (and maybe even save a few people from spreadsheet-induced burnout).
Behind the Savings: A Department-Level View
To understand the true value of AI automation, it's helpful to zoom in and see the savings on a department-level basis. For the purposes of this exercise, we'll focus in on the HR department as that's an area of the business that most everyone is familiar with. Of course, we could just as easily have focused in on finance, operations, or procurement, but the concepts we'll review here apply universally across the entire organization.
Meet Ben E. Fits: HR Manager Extraordinaire
To further ground our business case, let's zoom in on a specific role within the HR department. Meet Ben E. Fits, an HR manager that plans, coordinates, and directs HR administrative functions across the organization. Ben has over 10 years of experience in the field and brings a wealth of knowledge, leadership, and people skills to the table. Simply put, Ben’s very good at what he does.
According to the U.S. Bureau of Labor Statistics, the median annual pay for an HR manager of Ben’s caliber is around $140,030. When you factor in benefits, overhead, and other costs, that typically translates to an internal cost of somewhere between $70 and $80 per hour.
Now, to be clear: we're not trying to put a price tag on Ben’s worth. Nor are suggesting that we replace him with a series of bots. Far from it. Instead, our primary aim is to develop a strawman formula to help assess the potential value of AI automation in practical, measurable terms.
In fact, as we’ll explore later, one of the biggest opportunities with AI automation isn’t about cost-cutting at all. Rather, it’s about freeing up talented individuals like Ben to focus on higher-value, more strategic work. Because the more time Ben spends chasing down forms, wrangling spreadsheets, or answering the same questions over and over... the less time he has to tackle the initiatives that actually move the business forward.
From Busy to Productive: Using AI to Transform Ben's Daily Grind
On paper, Ben has all the tools he needs. He has access to a modern HRIS system designed to automate workflows and free up time for more strategic work. But in reality, a significant portion of his week is still spent chasing missing forms, correcting data errors, managing onboarding checklists, and answering the same routine questions over and over again.
In the upcoming sections, we’ll look into where Ben’s time really goes and how AI automation can help shift the balance.
Personnel Management
To start with, a lot of Ben’s work week gets eaten up by routine personnel administration tasks. Some common examples include:
Creating and maintaining employee records for new hires, promotions, and termination requests
Processing onboarding and offboarding requests
Managing address changes and other employee updates
Tracking asset returns (laptops, badges) during offboarding
Coordinating reorganization efforts including updates to reporting structures, job titles, and org charts
While most HRIS systems provide some kind of self-service portal experience for employees to perform these tasks on their own, a lot of these requests still end up on Ben’s desk. Employees either forget the portal exists, can’t find what they need, get stuck trying to use it, or simply prefer to ask for help rather than navigate the system themselves.
Figure 1: Navigating Employee Self-Service Portals
These interruptions only get worse when you add contractors, temps, and seasonal workers into the mix. These users often have limited system access, little to no training on self-service tools, and may need extra help just to complete basic tasks.
Even though these types of interruptions might only take up a handful of hours per week, this is actually a great place to dip a toe into the AI waters. With low-code AI tools like Microsoft Copilot Studio, we can build smart agents that guide employees through common HR tasks step-by-step.
Figure 2 illustrates what one of these conversational agents looks like running in Microsoft Teams. Armed with information from instruction guides and job aids (e.g., Word or PDF files), these agents can utilize the power of generative AI technology to answer routine questions (even the vague ones), collect information, and automate various administration tasks on an employee's behalf.
Figure 2: Using Conversational Agents to Promote Self-Service Administration Tasks
Given the relative low-cost barrier to entry with custom conversational agents these days, replacing clunky self-service portal experiences with easy-to-use conversational agents is kind of a no-brainer. Employees get quick answers without the hassle, and Ben gets to spend his time working on things that actually make an impact instead of answering the same questions over and over again.
Recruiting & Performance Management
Recruiting is another area where AI automation can make a huge difference. Even with an applicant tracking system (ATS) in place, a lot of manual effort goes into the hiring process for HR teams. Tasks like screening résumés for basic qualifications, coordinating interviews across busy calendars, and chasing down feedback from hiring managers can easily eat up hours each week, especially when hiring activity ramps up (e.g., seasonal hires, project-based staffing or unexpected spikes in demand).
While these types of tasks have been nearly impossible to automate in the past, recent innovations in the deep reasoning capabilities of generative AI models have opened up a new world of possibilities. As you can see in the video link below, autonomous agents can process information, reason through complex scenarios, and make real-time decisions based on context and priorities. This new level of capability makes it feasible to automate dynamic workflows—like managing recruiting activities—without losing the nuance and attention to detail that good HR operations require.
When configured correctly, autonomous agents can take on many of the repetitive, time-consuming tasks that bog down the recruiting process. From analyzing résumés against job requisitions to scheduling interviews, collecting feedback, and keeping both candidates and hiring managers in the loop, these agents can handle the heavy lifting without constant human oversight. They also help close communication gaps and keep processes moving.
And it’s not just recruiting where AI can step in. Performance management is another area filled with tedious tasks that slow HR teams down. Think about the amount of time Ben spends chasing managers and employees to complete performance reviews on time, manually compiling training completion records for certification renewals, or tracking goal completions and OKRs.
Of course, this isn’t to say that these tasks become completely hands-off. There will always be times when Ben or someone on his team needs to step in. But what if we can automate 75–90% of the mundane scheduling, tracking, and coordination tasks? During heavy hiring or review periods, that could easily give Ben back 20–40% of his work week.
Benefits Management & Compliance
While many HR systems are great at managing internal data, payroll and benefits management often pulls Ben and his team into a messier, more unstructured world. Here, we're talking about things like navigating external benefits portals, chasing down missing information, and cleaning up discrepancies that inevitably pop up when multiple systems have to stay in sync.
Take payroll and benefits reconciliation, for example. Even with solid systems in place, it’s common to find mismatches between what's recorded in the HRIS and what’s reflected by external benefits providers. Sorting through these discrepancies isn’t a quick job and it usually requires logging into third-party portals, manually reviewing records, and following up on missing or mismatched data.
Before, companies may have dabbled a little bit with some robotic process automation (RPA) to automate parts of these tasks, but the results were mixed. Now, with tools like the AI Recorder in Power Automate shown below, we can use natural language instructions to develop end-to-end automation solutions that collect information from emails, organize attachments, and upload data into external applications or benefits portals. These are tasks that would normally take up a lot of manual effort.
Then there's the never-ending stream of benefit-related questions:
What’s this deduction on my pay stub?
Am I eligible for vision benefits yet?
How many PTO hours do I have left?
Assuming this information is maintained in HRIS or accounting systems/services, we can incorporate these as conversation topics within the HR self-service bot we introduced earlier. That way, employees can get quick, accurate answers without needing to submit a ticket or getting Ben and his team involved.
Employee Relations & Compliance
Managing employee relations and compliance issues requires Ben and his team to work a different set of muscles. While equally time-consuming, these tasks aren’t obvious candidates for automation. Instead, they require more intense research, focus, critical thinking, and brain power. We're talking about complex tasks like investigating employee complaints, managing complex leave cases under FMLA and ADA, tracking compliance training completions, and preparing documentation for audits.
This is a place where tools like the Researcher and Analyst agents in Microsoft 365 Copilot can make a difference. These agents move beyond basic search functionality by reasoning through complex scenarios, pulling information from multiple sources, and presenting it in a structured, useful way.
To see how the Researcher agent works in action, check out the video below. It gives a quick look at how it can be used can gather, organize, and summarize complex information from a variety of sources.
After research materials are collected and organized, Ben and his team can use the Analyst agent shown in the video below to deeply analyze the information and compile the appropriate response.
Collectively, these tools give rise to a whole new type of automation where Ben and his team effectively gain access to their very own research assistant. This new kind of support doesn’t just help them work faster; it also arms them with the data and insights they need to make more informed decisions. What's more, these AI agents are often more thorough than manual reviews, catching small discrepancies, details, or patterns that human beings might miss.
AI Automation Benefits: By the Numbers
Now that we’ve explored a few ways AI can help lighten the load, it’s time to talk about the numbers. When you start looking at potential productivity boosts across tasks like recruiting, benefits management, and compliance tracking, small improvements can add up quickly. The question is, by how much?
Based on what we observed in the previous section, it's not unreasonable to imagine that AI automation could help Ben recoup as much as 16 hours per week. In some cases, it might even be more, but let's play this out conservatively and look at what happens if we could free Ben up for 8 hours a week. Assuming Ben works 48 weeks a year after accounting for holidays and vacation time, the cost savings formula would look like this:
Cost Savings Formula
Hours Saved per Week: 8 hours
Cost Rate per Hour: $80
Number of Weeks: 48
Total Savings = 8 x 80 x 48 = $31,220 per year
Reducing Ben’s workload is a meaningful start, but let's see what happens when we start to scale those benefits across the entire department. Based on a recent study from Sesame HR, Table 1 outlines the approximate HR department headcount for organizations of different sizes. Depending on the size of your organization, it’s not too difficult to visualize a path to six- or even seven-figure savings just by tackling a few of the low-hanging fruit opportunities.
Table 1: Estimated HR Staff Count for Organizations of Different Sizes
While the potential cost savings aren't necessarily linear, streamlining processes across the HR team can create opportunities for economies of scale, making it easier to handle a growing workload without necessarily needing to add more resources. Of course, not every automation opportunity will be worth chasing. It’s important to weigh the cost and complexity against the benefit and pick the areas where AI can make a clear difference.
Turning Lost Hours into Real Gains
When we talk about automation, it’s easy to focus strictly on the hours saved. However, a lot of the time what really matters is what those hours could be spent on instead. That's the idea behind opportunity cost: the value of the strategic, high-impact work that gets delayed or missed entirely when teams are buried in manual tasks.
For Ben and his team, freeing up even a few hours each week could open the door to projects that drive real business value. To put this concept into perspective, let's imagine that Ben's able to spend that extra time working directly with external benefits providers to negotiate better deals.
Suppose Ben negotiates a modest 3% reduction in total benefits costs through better contract terms or improved provider offerings. If the company's annual benefits spend is, say, $1 million (a very reasonable figure even for mid-sized companies), a 3% savings would equal $30,000 a year.
Bear in mind that’s $30,000 in recurring savings and not just a one-time boost. And that’s just one project. Multiply that kind of outcome across multiple areas and the long-term financial impact starts to look even more impressive.
The Power of Intangibles: What Happens When HR Has Time to Focus on People
Not every return on investment shows up neatly in a spreadsheet. Some of the most valuable outcomes are more intangible in nature. We're talking about things like:
Driving stronger employee engagement
Building a better workplace culture
Finding more innovative ways to attract high-end talent
Freeing up the time and mental space it takes to focus on programs that make a real difference for employees and the business. These are the kinds of activities that improve employee retention, fuel innovation, and help your organization stand out more in competitive markets.
Catching Issues Before They Become Problems
As one final thought experiment, let's look at the benefits of AI automation from a risk management perspective. When HR teams are stretched thin, critical work like employee relations and compliance can get rushed—or overlooked. Investigating complaints, managing leave cases, documenting findings, and preparing for audits all take time and focus. Without enough team bandwidth, it’s easy for small issues to slip through the cracks.
The problem is that small issues don’t always stay small. A missed detail in an investigation or an incomplete audit trail can turn into costly lawsuits, regulatory fines, or reputational damage. Giving Ben’s team more breathing room isn’t just about easing workloads, it’s also about making sure they have the time to be thorough, catch problems early, and protect the organization. In many cases, the cost of avoiding even one major compliance issue could more than pay for the investment in AI automation.
AI as a Teammate; Not a Threat
When people hear "AI automation," it’s only natural to wonder if the goal is to replace jobs. Perhaps it's just our optimistic nature, but we see the opportunity as being much more positive. For us, this isn't about replacing staff members; it's about giving them their day back.
While AI researchers like to pontificate on when we'll reach a state of "artificial general intelligence" (AGI), it's pretty safe to say that AI's still a long way away from replacing the important, human parts of employee roles. We're talking about things like judgment, relationship-building, creative problem-solving, and leadership.
However, when we pair talented employees like Ben up with AI-powered agents, we're able to unlock productivity boosts that have never been seen before in human history. When you think of AI as a teammate, not a threat, it changes the conversation completely. It’s not about doing less with fewer people; it’s about helping your existing team do more of the work that matters to help you grow your business.
Closing Thoughts
Every company is different, and so is every AI journey. There’s no one-size-fits-all business case for AI automation and adopting technology just for the sake of it is rarely a good idea. If your organization is just getting started with AI and wondering where to begin, the best place to focus is on your people and your processes. By taking the time to understand where teams are bogged down and where workflows could be stronger, you’ll quickly uncover the areas where AI can deliver the most meaningful benefits.
Throughout this article, we’ve explored how freeing up time for your employees can lead to some significant cost savings. But perhaps the biggest takeaway from all this is the fact that AI automation is mostly about giving talented teams the time and space to do the work that truly moves the business forward.
While we get excited about new technology around here, we do try to keep the hyperbole at a minimum with our customers. We understand that your business is complex and that there are limits to what technology solutions can offer. However, for what it's worth, we've never encountered a wave of technology in our decades of IT experience that comes close to matching the transformative benefits that we see with AI automation. So, we hope that this business case will encourage you to sharpen your pencil, do the math, and consider how AI offers the possibility to level up your business in ways you never imagined.
