It’s no exaggeration to say the rise of artificial intelligence is the defining technological trend of our era. While it’s too soon to fully understand the long-term impact of AI on the business world and society at large, one thing’s for certain: nearly every technology-driven organization will be using some form of AI in the near-future. Already, 77% of businesses are currently using or exploring the use of AI (source).
If you’re a finance leader or sales compensation manager, the potential impact of implementing AI is particularly enticing. But, it’s important to recognize that using AI to improve financial processes comes with its share of risks.
In today’s post, we’ll review some of those risks and key considerations— and provide you with best practices to avoid any unintended consequences of AI.
The Benefits of AI-Powered Finance Technology
Before we get to the risk factors, it’s important to emphasize the incredible benefits AI can deliver.
AI is capable of completely mitigating the inherent inefficiencies of complex financial processes. Take commission plan creation, for example. This process typically includes many steps and involves working with complicated formulas. An AI-powered tool that can automate plan creation based on simple inputs transforms an arduous and time-consuming activity into a hyper-efficient process– leaving compensation managers with more time to be strategic.
The insights that AI can generate will dramatically improve your ability to make smarter, faster, and more informed decisions. AI can rapidly analyze large data sets that would otherwise take hours for a human to conduct— and then provide you with recommendations that enhance the accuracy of your forecasting and the impact of your financial strategies.
The ability to streamline complex workflows is another key selling point for AI. The learning curves associated with running and maintaining financial systems are steep. But, with AI, complex formulas and calculations can be translated using Natural Language Processing. The output of which doesn’t require years of experience and specialization to understand. As a result, a larger number of finance employees can play a role in processes they’d otherwise be excluded from— and the team as a whole can become more agile and equipped to handle change.
The overwhelming adoption of AI means that businesses who don’t leverage AI in some way risk lagging behind the early adopters. Specifically, AI’s ability to analyze market trends and make informed predictions enables you to stay ahead of the curve, adapting to shifts in the industry and the economy before your competitors do.
All of the above advantages coalesce to yield the most important benefit of all: driving more revenue for your organization. The efficiency and power that AI provides will enable you to consistently optimize and refine your strategy, make impactful changes faster, and uncover new revenue-driving opportunities hiding within your different datasets.
We’ve covered the benefits and use cases of AI in the past, so we’ll move on to the main topic of today’s post. But, make sure you check out this post if you’re interested in learning more: AI Won’t Replace Sales Compensation Managers: Here’s Why.
5 AI Risk Factors and Key Considerations for Finance Leaders
Now, let’s take a closer look at some of the major risks associated with AI. Keep in mind: this is not a list of reasons to avoid AI— it’s actually the opposite. As with any new or emerging technology, there are still areas of AI that require fine tuning and awareness. Consider this list more of a user-guide to leveraging AI correctly rather than a list of reasons to avoid AI altogether.
1. Bias and discrimination
When you play a role in determining how employees are compensated, you have an ethical responsibility to ensure that your operations are fair and unbiased.
On the surface, AI may seem like an inherently unbiased tool. After all, it’s reliant on data, not human beliefs or opinions. But, it’s important to remember that the results produced by AI are reflective of the data you provide it with— and biased or discriminatory practices have an irrefutable impact on financial data.
Here’s an example: let’s say a female sales rep earns slightly less commission than one of her male counterparts and therefore doesn’t qualify for an accelerator. Here’s the catch- the accelerator was an AI generated recommendation intended to reward and reinforce over-performance.
Because the male rep in this example met the accelerator threshold, he was able to take home a significantly bigger paycheck despite having conducted the same number of activities and having a similar caliber of work as his female colleague.
Here’s the issue, in this example, AI ignores the bias faced by the female sales rep, who has achieved success despite operating in a male-dominant environment and receiving less hands-on training and resources than the male sales rep. In the end, AI only reinforced existing biases.
Tip: There are a number of steps you can take to mitigate bias and discrimination in AI implementation. First, perform regular, deep audits of your financial records and compensation history to ensure that diversity and inclusion is reflected in the data you feed into an AI-powered solution.
And, make sure to engage with HR leaders or experts in the ethical implementation of technology. Gaining information from AI is one thing— but before you use that information to make decisions that impact employees’ earnings, make sure you have a system of checks and balances that include a range of diverse human perspectives.
Recommended reading: Sell Like a Girl: Earn Less [+ Startling New Sales Commission Data]
2. Diminished transparency
The way you communicate about AI— and the extent to which you put AI in the hands of the employees it will impact— is just as important as the way you use it. Unfortunately, people in positions of power too often use AI to obviate their sense of responsibility for their decisions.
For example, it’s easy to brush off an employee who is unhappy about a change to their compensation plan by saying, “Sorry, but the system and the data proved that this is the correct decision for us to make.”
Of course, not every decision (AI-influenced or otherwise) is going to make employees happy. But, you’ll face long-term consequences if you foster a culture in which decision-makers distance themselves from the impact of their choices by assigning responsibility to a machine. This can justifiably cause employees to distrust and resent the leaders who are calling the shots. In turn, sales turnover rates will rise.
Tip: When used ethically, AI can actually increase rather than diminish transparency. Tools with Natural Language Processing capabilities can explain complex concepts to anyone, whether it’s a finance employee creating a comp plan or an entry level sales rep trying to understand their commission statement.
Make sure to leverage these capabilities to build trust rather than using them to create inaccessible data silos. During and after the implementation process, host educational sessions where all employees can learn, ask questions, and raise concerns about how AI will be used moving forward.
Recommended reading: AI vs. ML and the Implications for Sales Commission
3. Compliance issues
As a finance leader, you’re responsible for ensuring that your organization adheres to a growing list of laws and regulations concerning compensation reporting, pay transparency, and more. Not only are these regulations constantly evolving, but they’re incredibly layered and complex.
If you use an AI-powered solution to manage financial processes, you might assume it’s safe to trust the same tool to maintain ASC 606 compliance, generate adequate reports, and handle other compliance activities.
But, many tools that ostensibly offer AI-powered compliance reporting capabilities are not built to address the specific laws and regulations your organization may be subject to. If you blindly rely on these tools, you’ll be at risk of creating errors or omissions that may lead to legal consequences and devastating financial ruin. In fact, studies show that organizations lose an average of $4 million in revenue due to a single non-compliance event (source).
Tip: When evaluating AI-powered finance technology, dig deep into the details around automated data management and expense reporting. Make sure you understand how the tool pulls and organizes data, and what guardrails it has in place to avoid compliance risks.
More importantly: no matter what tool you’re using, don’t remove human judgment from the compliance reporting process entirely. An experienced finance professional should oversee expense report creation and submission, as it’s critical to search for errors, miscalculations, or gray areas the AI may have misinterpreted.
Recommended reading: ASC 606 Compliance: Choosing a Commission Expensing Solution
4. Cybersecurity threats
AI is so powerful because of the massive amount of data it continuously pulls and analyzes from a wide variety of sources. While this wealth of data analysis leads to key benefits, it also presents newfound cybersecurity risks.
Think of it this way: if one data source suffers a breach, the consequences can be severe— but an isolated security threat is easier to prevent from occuring and easier to swiftly address if it does occur. Now, imagine an AI-powered platform that collects data from hundreds of sources suffers a security breach. The sheer amount of data at risk could produce catastrophic consequences.
Tip: It goes without saying that data security should be a top priority when evaluating AI solutions. Include IT and cybersecurity leaders in the evaluation process to ensure that the vendor has sufficient protocols in place to mitigate the risk of a security breach.
It’s also important to put additional internal guardrails in place whenever you implement AI. Audit your existing security protocols and make sure they’re able to monitor for vulnerabilities. And, make sure that any employees who interact with AI directly receive training on how to safely and responsibly use the tool.
Recommended reading: The Impact and Administrative Overhead of a Bad Sales Commission Process
5. Uncertain longevity
In some ways, the remarkable power of AI can be both a blessing and a curse. If you implement the right types of AI, it can have a transformational impact on your financial processes. Suddenly, you’re uncovering all sorts of insights that lead to new revenue gains. You’re generating new compensation plans with a few clicks of a button. Projects that once took weeks now get done in minutes.
And then…your organization grows and the AI solution isn’t scalable, resulting in all sorts of errors that didn’t occur when you first adopted the tool. Or, the vendor goes out of business or discontinues the product— and you’re suddenly left without the tool that has been so instrumental in your success.
If this sounds like nothing more than an unlikely worst-case-scenario, think again. The AI technology market has become so saturated in such a short span of time, so it’s inevitable that a large number of solutions won’t last.
Tip: For starters, make sure that whatever AI solution you implement is built to grow alongside your company— meaning it will perform with the same power and efficiency when met with higher volumes of data, an expanded number of users, and more complex financial workflows.
But, those measures don’t change the fact that no solution’s future is certain. So, above all else, be wary of any financial strategy that is over-reliant on a specific AI system. Leverage the benefits of AI without abandoning the effective practices— and the skilled, experienced human employees— who keep your business running regardless of the technology at their disposal.
Recommended reading: 8 Soft Skills for a Successful Career in Finance or Accounting
With great power comes great responsibility, as the saying goes— and the potential power of AI is nearly limitless. So, as a finance leader, it’s your responsibility to be extremely vigilant when assessing any AI system that will impact your finance strategy, employees, and the organization as a whole.
Remember: just about every technology or software provider is trying to break into the AI space. All of these tools promise great benefits, but not all of them are trustworthy, flexible, and built to last. So, it’s imperative that you distinguish the responsible vendors from the rushed and reckless innovators. When you settle on a tool you can trust— and create your own plan to identify and mitigate risks— you’re ready to reap the amazing benefits of AI.
Spiff is a new class of commission software that combines the familiarity and ease-of-use of a spreadsheet with the power of automation at scale- enabling finance and sales operations teams to self-manage complex incentive compensation plans with ease. Spiff is designed to facilitate trust across organizations, motivate sales teams, increase visibility into performance and earnings, and ultimately, drive top line growth. The platform’s intuitive UI, in-depth reporting capabilities, and seamless integrations make it the first choice among high-growth and enterprise organizations.