AI Archives - Senior Executive

As we step into an increasingly diverse and interconnected world, the conversation surrounding diversity, equity, and inclusion (DEI) continues to evolve at a rapid pace. The next five years promise to bring forth a multitude of challenges and hot-button issues that will shape the DEI landscape. From the intersectionality of identities to the role of technology in workplace equity, leaders across various sectors are tasked with anticipating and addressing these emerging concerns.

Below, nine DEI Think Tank members share the key issues expected to dominate the DEI discourse and provide insights into proactive strategies leaders can adopt today to navigate these turbulent waters tomorrow.

Kimberly Morgan

1. Not Having DEI Leadership Roles or Efforts

Kimberly Morgan

DEI Sr. Director, GOJO Industries

I shudder when I hear leaders or others say that they hope one day we do not need DEI leadership roles or efforts. As the world continues to become more diverse, so should our respective industries and organizations. As leaders of this work, we must keep a pulse of what is happening relative to DEI and how it impacts our organizations and employees. We can’t expect business as usual, as if the issues happening out in the world do not impact or inform our thinking and decision-making processes.

Adrienne Collins

2. Replacing DEI Work with AI

Adrienne Collins

Director of DEI & People Strategy, Lovesac

As our world continues to evolve, I think about dealing with AI in the DEI space. There are many companies that may think eliminating the human connection of DEI work by replacing it with AI will be a cost-effective solution — it is not! The only way to be intentional about DEI is through human connection and experiences. There is no replacement for that.

Teresa Malcolm

3. Separating DEIB and Well-Being Strategies

Teresa Malcolm

System Vice-President of Diversity, Equity, Inclusion & Belonging, Dartmouth Health

DEIB and well-being are linked in multiple ways and organizations should focus on synchronizing initiatives rather than treat them as “separate but equal.” The need to support clinicians and staff through a holistic approach to well-being will be a hot topic in the future. Leaders can recognize that different daily experiences affect overall well-being outcomes and that individuals underrepresented in medicine have dramatically different experiences.

Nsombi Ricketts

4. Varying Accommodations Needed for the Multigenerational Workforce

Nsombi Ricketts

Vice President for Diversity, Equity, and Inclusion, Pratt Institute

With the potential of six different generations in the workforce at once, there will be varying needs for accommodations, expanded benefit options, inclusive technology solutions, and customized DEI training to support all employees. To prepare, leaders should learn as much as possible about invisible and visible disabilities, invest in comprehensive mental health and physical wellness resources, and provide the flexibility needed to ensure that everyone in their organization can thrive at work.

Courtney Peterson

5. Algorithmic Bias and the Fair and Ethical Use of AI

Courtney Peterson

Vice President, Chief Diversity Officer and Chief Human Resources Officer, Edison Electric Institute

As technology continues to play a significant role in our lives, concerns about algorithmic bias and the fair and ethical use of AI are likely to become even more prominent. Leaders will need to grapple with ensuring that AI systems are designed to be equitable and inclusive and they should be having those conversations now.

Eric Johnson

6. Responding to Climate Change

Eric Johnson

Senior Program Manager, DEI, Papa John's International

We are already seeing the devastating effects of more frequent occurrences of severe weather disasters, and the modern approach to DEI is apt to answer the call of the climate crisis. There’s an opportunity for the field to respond to the imminent civil rights injustices of climate change which will likely most intensely, adversely impact cultural groups who historically and currently have been required to traverse multiple landscapes of prejudice and bias.

Kellie Sauls

7. Increased Legal Challenges and DEI-Eliminating Legislation

Kellie Sauls

Director of Culture, Outreach, and Engagement, Teacher Retirement System of Texas

With increased legal challenges/lawsuits and DEI eliminating legislation, leaders will need to be strategic and specific about what they are doing, its purpose, and to what extent. Leaders need to know and understand what these laws and judicial decisions mean as well as their implications. Mostly, leaders need a comprehensive strategy for normalizing and embedding DEI in their organizations.

Karen Perham-Lippman

8. Managing Cross-Generational Collaboration, Communication, and Values

Karen Perham-Lippman

Diversity, Equity, and Inclusion Director, Jensen Hughes

With five generations in the workforce, managing cross-generational collaboration, communication, and values only grows in importance. Incorporating generational age bands into our diversity data at Jensen Hughes enables us to develop strategies that support inclusion for employees at all career stages. Our proactive approach enables us to foster mutual understanding and bridge generational gaps.

Ivan Lee

9. Focusing on Product Innovation and Integration with Revenue-Generating Departments

Ivan Lee

Director, DEI

The No. 1 value driver for corporate DEI will be to focus on product innovation and integration with revenue-generating departments. For example, Workday sells a SaaS DEI module, so DEI is directly revenue-generating. DEI and ERG leaders have opportunities to tightly integrate into sales and marketing departments as well, finding market opportunities among a global and diverse customer set.

Just about every industry in America has been rocked by the Great Resignation, but as any CPA will tell you, staffing shortages are nothing new for most accounting firms. In a 2021 survey by the American Institute of Certified Public Accountants (AICPA), staffing topped the list of concerns for firms of all sizes and has been a top concern since at least 2015. Obviously, the pandemic and ensuing burnout have exacerbated matters, but there are industry-specific issues that make its impact on accounting a different case.

From stagnant wages to stressful tax seasons, the industry as a whole isn’t doing enough to entice younger generations to pursue a career in accounting or to convince seasoned professionals to stick around. While there is plenty of technology available to help firms begin to fill these gaps, accountants have historically moved slowly when it comes to adopting new methods, in part due to the various laws, regulations and tax codes that change nearly every year, making implementation of any new tech tricky at best. Another frequent barrier to would-be adopters is the specialized and ever-evolving jargon of these technologies.

As the founder of an artificial intelligence (AI) bookkeeping software company, I often find that clients’ hesitancy to adopt new technology is mostly due to a lack of understanding of how these developments work generally and how they can support their efforts specifically. Accountants need to understand the technology that’s being marketed to them and the language used to discuss these features in order to ask the right questions and make informed decisions on behalf of their firm—the future of the industry depends on it. Let’s dig in.

A Brief History of Software Development

In order to understand the technology behind AI and why it’s useful for accounting, it’s important to review how we developed AI by exploring the iterations of technology that came before. 

Generally speaking, software development began as an effort to make manual processes faster and easier to replicate. A lot of first-generation softwares were built to aid a human user in doing specific things, not to do those things on their own on behalf of the user. From a labor standpoint, this was still a huge improvement on the old model and provided a measurable jump in the efficiency of storage and accessibility. Once those early softwares came around, we were largely able to say goodbye to shuffling papers and rifling through file cabinets.

Although it was impressive at the time, challenges quickly arose because one software was great at one task and another software great at another task, but neither could be used in place of the other. Suddenly, we had a bunch of siloed applications and people had to utilize multiple apps at a time to accomplish a single task. In the accounting sector, that meant you had an app to pay bills, an app to invoice clients, an app for task management, and so on. 

“New technology can be incredibly intimidating, but don’t let that stop you from bringing your firm into the future.”

Enrico Palmerino

– Enrico Palmerino


To solve for this, developers built systems that allowed you to move data between unrelated parties, making the data more accessible. This allowed us to skip the step of manually duplicating information across systems, a process that took more time and was obviously susceptible to human error. This was the first stage of real automation, which we call robotic process automation (RPA).

Then developers started to think, “Can we program scripts and softwares to replicate what the human is doing in the software?” So, for example, let’s say a lead comes in and the human takes the email address, copies it, types a message and sends it. Developers asked, “Is it possible to build a script that tells the computer to grab this email address, put it in this other email, type a message and shoot it off in a more automated fashion?” Obviously, it was possible, which was great, but at the end of the day, these softwares were designed to work the way that humans work. The downside to this approach is that every time a tool or an interface changes, the technology breaks down.

Here’s an example I like to use: Let’s imagine we’ve tasked a robot to put dishes in the kitchen sink. With RPA, we can tell the robot, “Go forward, take a left, turn right and drop the dishes in the kitchen sink.” But what happens if the kitchen sink moves? You or I, as a human, would understand that the sink moved and adjust accordingly. But the robot would drop the dishes on the ground or fail and do nothing. That’s RPA. And in an ideal world, if one thing changes, the script breaks, and nothing happens. Unfortunately, what tends to happen is one thing changes and the script still executes, but now it’s executing a mistake. When that happens, you have to find all the mistakes, stop them from happening and undo the damage which can be a nightmare. 

Senior Executive DEI Think Tank is a criteria-based membership community for chief diversity officers and senior-level DEI leaders at large organizations to share difference-making tactics, trade valuable resources, and seek the counsel of experienced peers in a private, confidential setting.

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Artificial Intelligence: The Next Frontier

This is where machine learning (ML) and AI came in. Once again, developers aimed to mimic the human user, but decided, this time, they weren’t going to mimic specific actions, but rather mimic the human user’s logic. So, going back to our example, how do we mimic the way a human understands that the sink moved? Well, it starts by understanding what the hell a sink is.

The way we typically learn as humans—and I’m oversimplifying things here—is by seeing lots of examples of different sinks. Even if they’re made from different materials, of various shapes and sizes, in all sorts of contexts, you and I would still recognize the core attributes of a sink. So instead of telling the program, “Drop the dishes at X location,” developers taught the software how to identify a sink so that even if it comes across a sink in an unfamiliar context, the software will still execute properly. Not only that, but it will continue to learn on its own, evolving and continuing to improve over time. 

But what does this mean for accounting? It means that tasks like bookkeeping, forecasting, payroll and many more can be largely automated, freeing up your time to focus on other tasks, like communicating with your clients, that robots will never be able to do.   

The Future of Accounting

New technology can be incredibly intimidating, but don’t let that stop you from bringing your firm into the future. Now that you have a base understanding of how these tools work, you can keep up with the jargon and ask the right questions of potential providers before you commit to implementing their software. Seek out technology that will help stop the bleed now and make workflows easier in the future, whatever that means for your firm. 

It’s time for a reality check on your data-gathering efforts. You’re probably monitoring basic workforce demographics, and you should feel good about the weekly “pulse” surveys you’ve implemented to broadly track employee satisfaction.

But what about specific departments? Do you see data that would reveal team-wide disengagement before it becomes a retention problem? Do you act on it?

Or even a specific worker, one of thousands of employees… working in a remote country? Is he happy? Does he have any lingering questions or concerns about employee benefits or company policies?

“The biggest handicap I see for HR individuals and HR executives is [not] having real-time data and metrics,” says Patricia Sharkey, senior director of human resources at IMI, a company that provides resources and software to automate distribution facilities across the globe. “That’s the way we’re going to be taken seriously.”

The company uses a homegrown, AI-driven HR platform called Rhonda to engage employees regularly, execute key HR functions such as performance reviews, and collect and analyze data to identify HR hotspots for leaders to act on. “What Rhonda does for HR, and what it brings to this company, is that our CEO has real-time metrics and data that he can make decisions based on,” Sharkey says. 

Senior Executive Media recently interviewed Sharkey about the company’s approach to employee communication and engagement. Read on for edited excerpts from our conversation.

“The biggest handicap I see for HR individuals and HR executives is [not] having real-time data and metrics. That’s the way we’re going to be taken seriously.”

Headshot of Patricia Sharkey

– Patricia Sharkey


Senior Executive Media: How is Rhonda regularly engaging employees and improving employee retention?

Patricia Sharkey: We have weekly surveys that go out, and employees rate, on a scale of one to five, how their week has gone… It’s a simple weekly, like, “Hey, please let us know how you’re doing.” And this goes out to the entire company. If an employee scores a three or lower, they’re going to get contacted by their manager, or by HR, and in some cases by the CEO directly, which is awesome.

I have employees that, every once in a while, I think they want to put a two because they want to talk to [CEO] Rudi [Asseer] because it turns out things are pretty good.

We run weekly reports that measure how many people are responding to us… I receive weekly reports of who’s engaging… If they’re not responding, or we’re getting a low response, we ask the manager, “Hey, how come your team isn’t responding?”

Senior Executive Media: What else does Rhonda do?

Patricia Sharkey: It’s a big part of the safety culture. We send out safety messages every Thursday. People can talk to us about any safety concerns.

We also have a weekly “hustle” that we send out via Rhonda, which is a newsletter, which reminds employees to respond to Rhonda and lists the employee of the week, by the way, too. So they’re engaged in the employee hustle because they may also see rewards.

Our employees can ask questions to Rhonda, like, “Hey, what’s up with my bank account?” … While we have an HR help desk and different areas where employees can contact us, the most successful is the AI application.

And with AI, it’s been much easier for us to get [performance] reviews back from the employees… This approach has increased accuracy, speed and employee satisfaction because it’s so easy for them to complete.

Senior Executive DEI Think Tank is a criteria-based membership community for chief diversity officers and senior-level DEI leaders at large organizations to share difference-making tactics, trade valuable resources, and seek the counsel of experienced peers in a private, confidential setting.

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Senior Executive Media: During the actual conversations within the performance review process, how does the data you’ve collected come into play?

Patricia Sharkey: Managers… talk to their employees about their [self-evaluations] and how, say, for example, the employee gave themselves a three [in a certain area], but the manager scored a four for them.

Then I’m given all that information as well. Not only am I able to see the scores of each employee and what the managers are giving them, the AI also does the average of what the department’s overall score is, which is pretty interesting—great data for the CEO. Because it takes some of the subjectivity out and goes, “Alright, you’ve got your divisional lead, maybe saying he has the greatest department in the company. But look at these overall scores.”

Senior Executive Media: You’re gathering so much data. What are the most important or most interesting metrics that you specifically look out for?

Patricia Sharkey: What I’m looking for, as I’m doing a temperature gauge on my employees: Are they happy? Are they going to stay with us? Through data, you can see patterns of behavior, right? I can tell if someone’s not happy if I see that I’m getting a lot of twos, right? I have to not only do a one-time check in, but now I have to go and say what’s going on? What systemically is happening in this department if I see, you know, in one department, I’m getting lower scores, or people not responding? (People not responding is almost the same thing as giving a low score, in my opinion.) And the question is not about the employee, it becomes about the company and systemic practices. What are we doing well, and what aren’t we doing well?