Thank you so much for joining us in this interview series. Before we dive into our discussion our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path?
Sure. Growing up the youngest of three girls with a single mom who immigrated to Chicago in her early 20s and worked in a factory all of her life, I knew I wanted something different. During my school years, the internet was becoming more common and presented a lot of opportunities in terms of career path, earning good money and job stability, so I decided to venture into technology and pursued a Bachelor of Science degree in Telecommunications Management. When I graduated, Information Security was emerging as a big field because the internet introduced new risks and threat vectors, and HIPAA was also on the rise, disrupting the healthcare industry. I landed my very first job as a security analyst for a regional medical center that operated multiple hospitals and clinics in Michigan. It was an incredible experience that allowed me to grow both personally and professionally. That’s how I got started.
What do you think makes your company stand out? Can you share a story?
You can get technology anywhere and you can buy services and products from anyone. However, what sets US Signal apart is our unwavering commitment to providing our customers with an exceptional experience. We care deeply about our customers and how they experience our brand. I have not seen an organization-wide commitment to this extent in any organization I’ve worked for before.
I may have seen it in pockets where you have people who are very customer-centric, but not organization-wide. A story that I can share that illustrates this is about a month after joining US Signal. There was a fire in Jackson, Michigan, that ended up causing a major fiber outage. Unfortunately, the fire included a facility that had asbestos, so the Environmental Protection Agency (EPA) got involved, which limited our, along with other carriers’, ability to go in and do the repairs for safety reasons.
Our team could have given up and told our customer, “We can’t do anything until the EPA allows us in, and you’ll be down for the next few days until the cleanup is completed.” Instead, the team came together and figured out a path forward to restore service to our customer. They worked diligently and installed the cellular failover service in the meantime, until permanent repairs could be made. To me, it’s just that dedication that sets us apart. They worked tirelessly overnight and into the weekend to make sure that the customer was restored as quickly as possible.
You are a successful business leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
I don’t think we ever take enough of a pause to be introspective like that, but the three I came up with were perseverance, openness, and gratitude.
Perseverance: I don’t back down at the first sign of resistance, difficulty, or setbacks. In my last role, before I joined US Signal, I led the technology group at an energy provider, and there was a lot of friction between the engineering and technology groups. That friction had been ongoing for decades and it was just part of their culture. When I tried to tackle the problem, I was faced with a lot of resistance and reasons why it wasn’t going to work.
During my time there, I remained steadfast on the goal of making sure that we could foster a bond and collaboration with both groups because it was instrumental in order for us to be successful. This was an energy provider and with technology/grid modernization, IT and engineering really needed to work collaboratively, so I didn’t give up on it. I implemented a multifaceted approach and by the time I left the organization, there was a lot of great collaboration going on with the teams. One of the most successful projects that resulted from creating that bond and fostering a culture of collaboration between those two groups was the addition of Cradlepoint units to the trucks that would go out on the field. Because our lineman, distribution designers, and engineers served remote areas, they often found themselves without service and unable to connect to our ERP, document work, or access information they needed. We collaborated with them to figure out the best technology and how to implement it. That served as a catalyst that really demonstrated to the engineering teams that technology could add value and that we weren’t going to dictate the technology, but were willing to work in collaboration with them.
Openness: In terms of openness, I’m curious by nature and love to learn. I firmly believe that everyone, regardless of their experience or background, can add value to the conversation. I always try to make sure that I’m promoting that with the new teams that I’m working with. In this current role, I came into a project that the teams had been struggling to bring across the finish line for about three or four years.
One of the things that I did was work to identify the stakeholders who are impacted by this initiative and bring them into the conversation, so that we could all hear their perspective and better understand their pain points. I was interested in hearing their ideas and vision for what this initiative should deliver. Fast forward a few months into it, we’re well underway to deliver the first iteration of this project in the next few months as a result of hearing people out and giving everyone an opportunity to contribute. It’s given people that sense of ownership because they’ve had the opportunity to weigh in and contribute to the project in a meaningful way.
Gratitude: I’m very intentional about giving myself time to reflect on what I do have to be grateful for and to express that gratitude to others. I don’t think we stop often enough to tell people how much they’ve helped us or how much of an impact they’ve made, so I really make an effort to thank people.
We have a platform here at US Signal called Bonusly. Whenever I come across a situation where I either observe someone who has done something to help a customer, teammate, or a project that I’m leading, I make a point of taking a pause, provide that recognition, and let them know that they’re appreciated. Being intentional about that in both your professional and personal life is best.
I’m not as good at this as I should be, but I do try to also express to my husband how grateful I am for his support. I spend most of my time working and a lot of the family slack falls on his shoulders. I take time to let him know, “Thank you. I’m grateful for having you and I appreciate you.” Without him, I wouldn’t be able to do what I do.
Let’s now move to the main point of our discussion about AI. Can you explain how AI is disrupting your industry? Is this disruption hurting or helping your bottom line?
It is absolutely disruptive but in a very good way. All disruption has its good, bad and ugly, but for the most part it’s good. Some of the areas where I think AI is disrupting our industry are shifting skill sets, evolving service offerings, security and transparency, growth at scale, speed to market, and customer expectations.
Shifting Skill Sets: The automation of tasks through artificial intelligence (AI) is leading to a decreased need for some of the traditional data center jobs and cloud-based roles. However, new roles focused on managing and developing these new AI systems within our data centers and system stack are evolving. It’s not that it’s replacing human capacity, it’s augmenting it and changing how we work. It’s going to require a workforce that has a blend of technical expertise, AI literacy and the use of soft skills. I can’t emphasize enough how important it is to make sure that we continue to foster soft skills, like communication skills, critical thinking, creativity, adaptability, problem-solving, and emotional intelligence. These skills are important because they help individuals work collaboratively and effectively with others, navigate complex situations and challenges, and adapt to changing circumstances, which are all important in the context of AI-powered work environments.
Evolving Service Offerings: I think another area where it’s being disruptive is its evolving service offerings. For example, if you think of AI, there is a large amount of resources it takes in order to train models and deliver AI. For example, GPU as-a-service is a new service offering that could potentially create new revenue streams and attract new customer segments that weren’t previously accessible to companies like US Signal.
With the massive amounts of data that AI is generating, processing all of that data in a centralized cloud data center isn’t efficient anymore either. That could potentially lead to maybe more edge computing products and that data processing can happen closer to where the data is being generated. It’s a positive because it’s helping us to develop new products that are relevant to the needs of our customers.
Security and Transparency: As AI becomes more integrated into our business, there’s a lot of security and privacy concerns that come with that. We just need to make sure that we are transparent about our AI practices and make sure that we have good education and training for our staff and customers.
Growth at Scale: AI allows us to do some pretty cool, innovative things, deliver new products, enhance efficiency, and achieve operational excellence at scale. For example, when you deliver a new product, it typically requires new skillsets and creates maintenance, support, and administrative overhead, introducing the need for additional resources. Now, that work can be augmented with AI enabling existing staff to handle support of new product offerings.
Speed to Market: AI has revolutionized the way developers work by enabling them to analyze large sets of data and code more efficiently. This is particularly valuable in software development, where developers often deal with complex codebases and datasets. One key benefit of AI is its ability to assist in quicker iteration. Through techniques like machine learning, AI can analyze patterns in code and data, helping developers identify areas for improvement or optimization. AI-powered testing tools can automatically generate test cases, identify bugs, and even suggest fixes. This can all lead to faster development cycles and more agile software development processes.
Customer Expectations: If you think about customers nowadays, their expectations have risen and rightfully so. They expect to have self-service, the information they need and want right at their fingertips, and they expect 24×7 support. They want to be able to help themselves with simple troubleshooting/queries and expect us to be more proactive when it comes to problem detection and mitigation strategies to reduce downtime. Customer expectations are evolving and they’re expecting more from their providers, so I think that’s very disruptive to our industry.
Based on our road map for how we plan to use AI and adopt it, we expect that it’s going to help our bottom line by allowing us to meet revenue growth goals and heightened customer expectations at scale. Our delivery teams are going to be well positioned to absorb increased sales activity through intelligent workflow automation and data insights. We’re going to supercharge our support team with AI-powered virtual assistance, chatbots, self-service, real-time sentiment analysis, and intelligent next-steps guidance. From the perspective of our road map, we really do anticipate that it’s going to help the bottom line.
Which specific AI technology has had the most significant impact on your industry?
Natural Language Processing (NLP) has had the most significant impact on our industry. If you look at chatbots and virtual assistants, they really have enabled users to interact with technology in a more efficient way. Users can ask questions, get support and perform tasks using natural language.
The ability to go in and ask a question, the way you would ask a colleague or another individual and be able to get the information that you need, has been a game changer. From a troubleshooting and support perspective, NLP has enabled our industry to analyze and understand user queries, delivering automated responses and routing support to the most appropriate individual that can solve the problem the quickest, which enhances that customer experience.
From a data analysis and insights perspective, NLP has helped us extract intelligent insights from unstructured data, which has been a challenge with traditional data warehouses and data lakes.
I would also say that sentiment analysis is another area where NLP has helped, where we can analyze how our customers are experiencing our brand in a way that doesn’t require a survey. For the most part, a customer could be truthful in a survey, but a survey is also a snapshot in time. Maybe the customer had a bad day or maybe they had a great day and are feeling super generous. We’ve had customers who may not have had a great experience, but they like our people and they don’t want to throw anybody under the bus.
NLP has allowed us to look at that interaction in real time and, based on the words being used, tone/inflection, and pauses in the conversation, it allows us to get a much more accurate view of how our customers are experiencing our brand.
Can you share a pivotal moment when you recognized the profound impact AI would have on your sector?
Sure. I started working at US Signal last July and my very first week there we were putting together our five-year strategic road map. It was at that moment when we came up with some very ambitious goals for the organization and as a member of the executive team, I’m responsible for helping us execute that strategic plan. I looked at our current state and recognized that AI would be crucial to our success. For me, that was the moment.
How are you preparing your workforce for the integration of AI, and what skills do you believe will be most valuable in an AI-enhanced future?
First and foremost, it’s education. Making sure people understand what AI is, when AI is and isn’t appropriate, and what some of the pitfalls of AI are important. AI is not perfect and is still very much an emerging technology with many kinks to get worked out. Making sure our workforce is educated about AI and then upskilling them is key.
We want to make sure that they have the new skills required to work with AI. Some of those skills that are relevant to AI are still obvious things like coding, which is a very valuable skill set. Data skills, specifically data analysis, interpretation, and visualization, are going to be crucial for working with AI tools.
We’re investing in training programs that are going to strengthen data fluency amongst our workforce. Human skills are not going to be replaced as I mentioned before, such as soft skills, specifically. AI can’t critically think, be creative, problem solve or communicate in the way that humans can, at least for now. We want to make sure that we are strengthening those skill sets amongst our workforce, while also providing them with reassurances that their jobs are changing, not being replaced. Jobs are just being enhanced by it.
Domain expertise is another part. Regardless of one’s industry, we can’t rely on AI blindly that it is going to solve every problem. Deep industry knowledge is going to be critical to determine which tasks will really need human judgment or expertise, and which tasks can be outsourced to AI. I think that’s going to be important.
What are the biggest challenges in upskilling your workforce for an AI-centric future?
The rapid pace of change is the first challenge. AI has been in the works for a while but if you think about the first iteration of ChatGPT, we are already on the most recent version of ChatGPT4. There’s a rapid change of AI and every day it feels like a new AI platform has been invented and is being published along with being free and accessible to everyone. It’s constantly evolving, and I think that makes it very difficult to design training programs that can stay relevant for an extended period of time.
Increased cost and time are also a challenge. When upskilling your workforce, it requires an investment in time, resources, and new technologies for training. In our industry, most people are already overworked, so you have to find the time to fit in all of this new training in addition to their regular job responsibilities.
Employee motivation and fear is a challenge. You can tell people, this is a tool and it’s not replacing your job, but people may still be wary. There’s still a certain amount of fear that people feel in terms of job displacement that needs to be addressed, and I think that’s certainly a challenge.
The last challenge is integration with existing workflows. Integrating AI technologies into existing workflows and business processes is going to be very complex and will require changes to your organizational structures and practices.
Those are the main challenges that come to mind: a rapid pace of change, increased cost and time, employee motivation and fear, and integration with existing workflows.
What ethical considerations does AI introduce into your industry, and how are you tackling these concerns?
Privacy, bias, accountability, and job displacement would be the four ethical considerations that come to mind for me.
From a privacy perspective, with the access to large amounts of personal data, it’s raising concerns about privacy and data protection. For us at US Signal, we’re tackling that challenge by restricting the AI platforms that can be leveraged with restricted data. We published a policy and are educating our teams. We’re letting them know when it’s ok to use ChatGPT or Google’s Gemini versus when you have to use Microsoft’s Copilot or Salesforce’s Einstein. We’ve made very clear distinctions of when you can use sensitive data and when you can’t because we want to protect customer privacy and employee privacy as well.
From a biased perspective, we know that AI algorithms can be biased. There’s plenty of examples out on the Internet about things that have happened, where it leads to unfair or discriminatory outcomes. The way we’re tackling that is by education and making sure that our people understand that there are guidelines for the data sets that can be used to train AI models. Right now, we’re working through figuring out a monitoring process where we can identify where we are at risk for bias or other ethical concerns.
From an accountability perspective, it can be challenging to assign responsibility for the decisions that are being made by AI systems. What happens when something doesn’t work out as intended and it has a negative consequence? What we’re doing is establishing mechanisms for accountability to make sure that there are clear lines of responsibility for AI-related decisions. So, in our policy, as an example, Trevor Bidle, who’s our CISO, has a certain set of responsibilities. Mary Whiting, who’s head of compliance, has a certain set of responsibilities, as well as myself, as CIO. We just want to make sure that those roles and responsibilities are clearly defined and those who are responsible understand it so we can’t say AI did it. AI didn’t do it without us having a role in it.
As AI technologies become more widespread, it is going to lead to job displacement to some extent. While for the most part, AI augments human work, there are certain things that are better served by AI such as repetitive tasks and data analysis to a certain degree. There are going to be instances where certain tasks that are currently performed by a human being are going to be offloaded to AI.
Some of the things that we are doing to address job displacement are retraining, upskilling, communicating and working collaboratively with people to identify where it makes sense to use AI. If there is some job displacement, we are making sure that we have internal mobility opportunities for our people. Maybe there’s a different job or role that they can move into. Maybe their job is only 25% being shifted, which creates an opportunity for them to contribute to a strategic initiative or project based on their expertise. Those are some of the things that we’re doing in order to make sure that we’re addressing those considerations.
What are your “Five Things You Need To Do, If AI Is Disrupting Your Industry”?
- Identifying Processes: The first thing you should do is identify processes in your business that are well suited for AI. You need to understand your business so that you can understand where the applications for AI are in your business. You then need to develop a strategy on how you’re going to execute against and mitigate some of the risks that come with it, such as ethics and a variety of other things.
- Governance Framework: The second thing is you need to implement a governance framework that establishes those protocols and policies, defines roles and responsibilities, and ethical guidelines. Without governance, it’s the Wild West and you can’t have that with AI.
- Interdisciplinary Committee: The third thing that I would recommend is an interdisciplinary committee that can review new AI projects to make sure they’re aligned with your ethical guidelines, strategically aligned, and generally make sense. Sometimes we want to do things just because they’re cool but we’re not really solving a problem. By having a cross-functional team that can really evaluate these new ideas, you can really put some guardrails around when you’re going to use AI and when you’re not.
- Education: The fourth thing is education. You absolutely have to educate your workforce on what AI is and isn’t, what the boundaries are, and the ethical considerations just so that they can understand where the applications are appropriate. It helps make sure everybody’s on the same level of understanding when it comes to AI.
- Monitoring: The last thing is monitoring. Sometimes we do all of that work, and we assume that everything’s being followed and done, AI is doing its job, and people are doing their job — but in reality, you have to inspect what you expect. You should have a monitoring program in place to make sure that AI is functioning as expected in your organization, given whatever outcomes and strategies you’ve established for yourself. You can do that through regular audits where you are reviewing the data, algorithms, decision making processes of the AI system, and feedback from the users. You can always get feedback from users who are interacting with AI that will help you understand whether or not there are gaps or issues that you need to address. The other thing that you can do to establish a good monitoring program is by building algorithms that can detect and mitigate bias in AI systems. Algorithms can analyze the data and the decisions being made and then maybe trigger an alert and have a report of some sort that helps you understand the need to investigate in case something just doesn’t seem right.
What are the most common misconceptions about AI within your industry, and how do you address them?
There were two that came to mind. First, the belief that AI can replace human beings is flawed. To counter this, a thorough understanding of your specific business to determine the tasks that require human judgment and expertise and those that you can entrust to AI.
The second one is that AI is failproof. We see many examples of where AI is not failproof, and putting blind trust in AI can lead to misinterpretations, bias, and other negative outcomes. There’s a common misconception that you can trust AI since it’s been trained, but it’s important to educate and emphasize that AI’s reliability is contingent on the quality of the datasets used for training the model.
The way we’re addressing it is via education and reinforcing the need to really understand the data behind the training models. Understanding that data lineage such as what data is being used to train AI models and where that data originated from are beneficial. When you learn what the entire data life cycle looks like, you can really start to understand where you might potentially be able to have greater trust and other areas where you would have to put some checks and balances to make sure that AI is accurate.
Can you please give us your favorite “Life Lesson Quote”? Do you have a story about how that was relevant in your life?
Sure. I don’t know if it’s a quote, but a mentor of mine would always say, “Fail, fast.” The reason I think it resonates with me and I really like it is because it motivates me to drive towards change. It’s ok to fail, have a setback, or an obstacle, as long as you quickly recognize the need to pivot. We know that in order to succeed, you have to fail, but sometimes we get so attached to the idea that’s failing, that we are blind to the need to pivot so, “Fail fast,” was always something that really resonated with me because it was a reminder that while it’s ok to fail, you have to quickly recognize when something’s not going to work out.
Several years ago, I worked at a traditional managed services and professional services company, and we merged with a data center and cloud services provider company. During that merger, we agreed to a new organizational structure, and I had my doubts about the proposed organizational structure. After voicing my concerns and talking through it, we decided to try it anyway. Within a few months, it was very clear that the organizational structure wasn’t working and because of that fail-fast mentality, I advocated for change, and we made that mid-course correction that put us on the right trajectory. We were much more successful with the new organizational structure. We tried it and what helped was that quick recognition of knowing what wasn’t working.
Off-topic, but I’m curious. As someone steering the ship, what thoughts or concerns often keep you awake at night? How do those thoughts influence your daily decision-making process?
Change fatigue is one aspect that really sticks with me the most. We’ve been talking about AI for a long time and there’s some much more emerging technology coming out. There’s also competition such as first mover advantage. There’s an increased cost of everything, especially post-COVID. The cost of everything has gone up so everyone’s having to scramble to get creative as to how they can maintain margins and still deliver quality solutions, products, services, and efficiency at scale. All of those things are driving tremendous change in how we do business and it’s not just unique to our industry, it’s global.
Change has the potential to give us that competitive advantage and really accelerate our ability to meet those strategic goals that we’ve set for ourselves. It can also result in employees getting burned out and being disengaged, which will negatively impact your organizational outcomes. At the end of the day, you’re not going to reap the benefits of the work being done if people are burnt out and they’re disengaged.
Traditionally when we look at tackling a new initiative, project, or any kind of change, we look at the value, strategic alignment, cost, or ROI. Those are the things that we focus on, but we don’t ever have the conversation about how a change will impact employees. How much change have they recently undergone? Is this the right time and should we maybe pause?
If you still have to go through with the change, thinking about that concept of change fatigue in your organization and having that conversation allows you to address it. You can figure out the organizational change management plan that will help reduce the potential for burnout and disengagement in your workforce for your employees.
When I identify a new problem or new opportunity, I take a pause and think about the impact of change. How much change is this going to introduce and how are people going to perceive this change? I make sure to talk to employees who are impacted, acknowledging the change and just helping them understand the why behind needing to tackle it.
Giving them an opportunity to express their fears, concerns, and contribute their ideas, goes a long way. That’s how it influences my daily decision making. I don’t just think of something and start running with it. I try to slow down just a little bit to have those conversations and make sure that we’re addressing it.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. 🙂
If I could start a movement that would bring the most amount of good to the most amount of people, it would be to unlock understanding and listen first. In today’s world, there’s a lot of noise and everybody’s vying for their five minutes of fame, whether it’s a Tik Tok video, a YouTube channel or Instagram post. Everybody’s chirping, but not really listening.
If that was a movement that I could inspire people to start, I believe it could unlock greater empathy and connection. When you listen and you’re open to what other people are saying, you can really step into their shoes, understand how they’re feeling and maybe value their perspective rather than just dismiss it.
I also think that if we listen more, we can be even more innovative and creative than we are, because now we’re listening to the ideas that other people bring to the table. We are creating space for others to share and open up.
It would improve communication and it would bridge divides across all sectors, such as the political landscape. Everybody’s talking, but no one is listening. So, for me that’s a movement that would probably be one that could do the most good to the most amount of people.
How can our readers further follow you online?
The best place I would say would be LinkedIn, as I am setting a goal to be more active on that platform.
Thank you for the time you spent sharing these fantastic insights. We wish you only continued success in your great work!