Guardians of AI: Sean Hauver of Alorica On How AI Leaders Are Keeping AI Safe, Ethical, Responsible, and True

An interview with Gabriel Borden | Reposted from Authority Magazine

As AI technology rapidly advances, ensuring its responsible development and deployment has become more critical than ever. How are today's AI leaders addressing safety, fairness, and accountability in AI systems? What practices are they implementing to maintain transparency and align AI with human values? To address these questions, we had the pleasure of interviewing Sean Hauver.

Sean Hauver is Chief Information & Technology Officer at Alorica, where he leads the company's global technology organization and drives the modernization of enterprise technology that supports both operations and client delivery. His primary responsibility is helping the business leverage technology to drive growth and deliver high-performing outcomes for clients. He plays a key role in advancing the technology strategy, strengthening digital infrastructure, and enabling secure, scalable platforms that support next-generation customer experience solutions. With more than 30 years of experience, Sean has held senior leadership roles at Alorica, including Chief Architecture Officer, and previously led innovation and growth initiatives at Lighthouse Computer Services and Spyglass Solutions. Earlier in his career, he spent over two decades at The Hanover Insurance Group, developing expertise in business strategy and transformation, enterprise architecture, and technology strategy.

Thank you so much for your time! I know that you are a very busy person. Before we dive in, our readers would love to "get to know you" a bit better. Can you tell us a bit about your 'backstory' and how you got started?

Looking back, I realize how fortunate I was, especially in the early chapters of my career.

I was fortunate to begin my career with an organization that truly cared about leadership and talent development. Opportunities were provided to grow quickly, explore different career paths, and take on new roles and responsibilities.

I started my career as a software engineer supporting the HR and Corporate Services organization, working alongside a great team and exceptional business partners. For someone like me, who was just as interested in learning about the business as the technology itself, I could not have asked for a better place to begin my career.

I moved quickly across a variety of roles within the organization and was fortunate to have a leader and mentor who believed in me. At a relatively young age, I was given the opportunity to take on the role of Chief Architect and, a few years later, the chance to build a truly global software delivery organization.

After more than 20 years, I decided to pursue an exciting opportunity with a leading consulting practice as its Chief Innovation Officer. This role gave me the opportunity to work with a wide range of organizations, from Fortune 100 companies to startups, across many industries, helping them advance their business transformation journeys.

It also provided invaluable experience and insight into the models, philosophies, and leadership qualities that differentiate exceptional companies from those that struggle.

My journey came full circle when I joined Alorica as Chief Architecture Officer in 2022, which turned out to be yet another fortunate opportunity to work with a talented team that is passionate about enabling customer success.

None of us can achieve success without some help along the way. Is there a particular person who you are grateful for, who helped get you to where you are? Can you share a story?

From a personal perspective, I was very fortunate to grow up with an uncle who was like a father to me. He was one of the most caring and genuine human beings I have ever met. He also happened to work in the technology industry and was always an early adopter of new technology. He cultivated my passion and curiosity for technology at a very early age.

I got my first PC - a TRS-80, for those old enough to remember them - from him when I was 8 years old, and I was hooked! Even before the internet, he taught me how to "surf" the Bulletin Board Systems (BBS), and he created one of the first "sites," called Paddy's Place, which was very popular in those early days.

My uncle was the most influential person in my life and helped shape me into the person I am today. I would not be where I am without his love, support, and guidance!

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?

Servant Leadership - This has always been core to who I am. For me, it was never about individual achievements, accolades, awards, or anything like that. I grew up in a large family, playing team sports, and spending lots of time with family and friends which helped shape my perspective and mindset. It is more important and fulfilling to me to see how I have helped contribute to someone else's success, whether that is a teammate, a business partner, customer or someone within my own team.

Integrity - I believe in always acting with integrity, establishing trusted relationships through continued transparency, delivering on commitments, and taking accountability for the good and the bad. Things are not always going to go how you planned, so it is critical that you are communicative, transparent, and demonstrate your commitment to success especially in those challenging times. You have nothing if you lose the trust of your team or your customers.

Open-mindedness - It is important as a leader to make sure you continuously take in all the information to make the most informed decision. Always approach matters and decisions with a "seek to understand" mindset first. Ask yourself: How did we get here? What was known at the time? What is the best path forward? Be confident in your right to change your mind and make a better decision if, and when, new information is presented or your first solution is not providing the expected benefit or desired outcome. That is a strength, not a weakness from my perspective.

Thank you for all that. Let's now turn to the main focus of our discussion about how AI leaders are keeping AI safe and responsible. To begin, can you list three things that most excite you about the current state of the AI industry?

We are still in the early stages of AI's potential

Despite the tremendous innovation we've seen from technology providers over the past few years, what excites me most is that we are still only at the beginning of the AI journey. From a business adoption and transformation perspective, most organizations are still just scratching the surface of what's possible. AI capabilities will continue to evolve, become easier to consume, and lower the barriers to adoption. Over time, this will enable AI to fundamentally transform industries by improving efficiency, enhancing decision-making, and creating entirely new ways of working.

The evolution from conversational AI to transactional AI

We are rapidly moving beyond basic conversational AI and knowledge-based chatbots that simply answer questions. We are now beginning to move forward with transactional AI, intelligent systems that are deeply integrated into business processes and capable of taking action, automating workflows, and driving outcomes. This evolution has the potential to significantly improve operational efficiency while allowing employees to focus more of their time on higher-value activities, complex problem-solving, and delivering a better overall customer experience.

The acceleration of rapid prototyping and solution development

AI-powered code generation and development tools have improved dramatically, even within the last 12 months, and the pace of improvement continues to accelerate. These capabilities are enabling organizations to prototype, test, and deploy business solutions much faster than ever before! Even more importantly, the built-in security test case generation and execution is ensuring we are building more secure solutions than ever before as well. The result is a significant reduction in time-to-value, faster innovation cycles, and an increased ability to scale new capabilities across the business.

Conversely, can you tell us three things that most concern you about the industry? What must be done to alleviate those concerns?

The pace of innovation is outpacing governance and risk management

AI capabilities as we discussed are evolving incredibly quickly, but many organizations are still developing the policies, controls, and governance frameworks needed to use AI responsibly. At the same time, we are relying on the AI capabilities that our technology partners and vendors are rapidly introducing into their solutions to keep pace with innovation and deliver value more quickly.

What must be done:

We need to all be diligent across the ecosystem before deploying AI solutions or new AI capabilities in existing solutions to fully understand the risks around bias, privacy, security, and regulatory compliance. Organizations need to establish clear AI governance programs that include risk assessments, human oversight, transparency standards, and ongoing monitoring. Responsible AI cannot be treated as an afterthought; it has to be embedded into the development and deployment lifecycle from the beginning. Similar to the "defense in depth" security strategy many of us have been diligent about over the years, we need the same rigor applied here to AI governance and risk management within our organization and expect the same from our vendors and partners.

Overreliance on AI without sufficient human accountability

As AI becomes more capable, there is a risk that organizations begin trusting automated outputs without appropriate validation or human judgment. AI should augment human decision-making, not replace accountability.

What must be done:

Especially now since we still are in the early stages of AI advancement, companies need to maintain "human-in-the-loop" processes for critical business decisions, especially in areas that impact customers, employees, financial outcomes, or compliance. AI literacy and employee training will also be essential so teams understand both the strengths and limitations of these systems.

The growing gap between AI adoption and workforce readiness

Many organizations are eager to adopt AI, but their workforce may not be prepared to adapt to the operational and cultural changes that come with it. There is understandable concern around job disruption and how roles will evolve.

What must be done:

Businesses must invest first in awareness training into the concepts of AI to level set on the terminology and understanding of the capabilities. They also will need to invest in upskilling and reskilling programs to help employees work alongside AI effectively. The organizations that succeed will be the ones that position AI as a tool that enhances human capabilities rather than replacing them. Our people, as everyone knows, are our most important assets. To help solve this challenge, we have introduced AI literacy and awareness courses through our Alorica University program for all employees across our organization. We are also investing heavily in the technology organization's skills and capabilities to accelerate our business transformation and the value we provide for our customers.

As a CTO leading an AI-driven organization, how do you embed ethical principles into your company's overall vision and long-term strategy? What specific executive-level decisions have you made to ensure your company stays ahead in developing safe, transparent, and responsible AI technologies?

As a CTO, I believe ethical AI has to be built into the company's culture and strategy from the start, not treated as an afterthought or compliance checkbox. It was important to work closely with our business partners to first align and make sure everyone had a common understanding of what was meant by ethical AI principles. Then, it meant creating clear internal standards around transparency, privacy, security, and responsible AI use.

At Alorica, we have implemented a cross-functional AI Governance Committee with representatives from legal, security, technology, procurement and compliance to ensure everyone is aligned, setting standards, and mitigating any risks as they arise. We also have a very thorough architecture review process evaluating all new technology solutions, capabilities, and providers well before we would ever leverage those capabilities internally or for our customers.

Many people are worried about the potential for AI to harm humans. What must be done to ensure that AI stays safe?

These concerns typically stem from how and when safeguards are applied. We need to embed what I would call "golden rules" into these systems from the very beginning, not just add them in later or after a concern has risen. AI should be designed and deployed in a way that prioritizes fairness, transparency, accountability, and respect for all. As mentioned above, human oversight in real-time and reviews afterward are also key to ensure these systems behave in the way we intended over time.

Despite huge advances, AIs still confidently hallucinate, giving incorrect answers. In addition, AIs will produce incorrect results if they are trained on untrue or biased information. What can be done to ensure that AI produces accurate and transparent results?

This ultimately comes down to how we manage data. AI is only as reliable as the data it is trained on and the controls we put around it. If the data is inaccurate or biased, the outputs will be as well.

To address this, we need a continuous validation and feedback loop in the AI lifecycle. Accuracy is not a one-time effort. Data should be regularly refreshed, outputs should be monitored, and human oversight should be used for higher-risk use cases. It's also important to have mechanisms in place that identify and correct errors quickly.

Here is the primary question of our discussion. Based on your experience and success, what are your "Five Things Needed to Keep AI Safe, Ethical, Responsible, and True"? Please share a story or an example for each.

To summarize what I've discussed so far:

1. Start with "Golden Rules"

AI must be built with fairness, transparency, accountability and respect from day 1, not added in later. For example, before deploying any AI capability, we ensure ethical considerations such as bias, privacy, and security are evaluated upfront through our governance and architecture review process.

2. Establish Strong Governance

Clear governance structures are critical to ensure accountability. At Alorica, our cross-functional AI Governance Committee sets standards, reviews use cases and proactively manages risk.

3. Ensure High-Quality Data

Investing in data curation, validation and ongoing data management reduces bias and misinformation. Sources should always be verified and datasets refreshed before they are used in AI models. For example, before we use AI-driven insights, we validate the data sources are accurate and current.

4. Implement Continuous Validation and Monitoring

AI systems need continuous feedback loops to monitor outputs, detect errors and improve over time. In practice, this means monitoring AI-generated responses and feeding any corrections back into the system so it continues to improve.

5. Maintain Human Accountability

AI should augment human decision-making, not replace it. There should always be clear ownership and accountability for outcomes. For higher-risk scenarios, we ensure there are clear human escalation paths.

Looking ahead, what changes do you hope to see in industry-wide AI governance over the next decade?

Over the next decade, I hope to see globally unified AI governance standards emerge, similar to how the cybersecurity industry aligned around frameworks and certifications like NIST, ISC2's CISSP, and OWASP best practices. Establishing widely accepted standards for AI safety, transparency, privacy, testing, and accountability would help organizations develop and deploy AI more responsibly while creating greater public trust and international consistency.

What do you think will be the biggest challenge for AI over the next decade, and how should the industry prepare?

I think the biggest challenge for AI over the next decade will be balancing rapid innovation, keeping it secure and ensuring you are thoughtful and careful with your investments with things changing so quickly. AI is advancing faster than many companies, governments, and regulations can keep up with, which creates risks around misinformation, privacy, bias, cybersecurity, and overreliance on automated decisions.

As discussed prior, to prepare, the industry needs stronger governance and globally accepted standards, better security practices, and more transparency around how AI systems are trained and used.

You are a person of great influence. If you could inspire a movement that would bring the most good to the most people, what would that be? You never know what your idea can trigger. :-)

I would love to see a broader movement around AI literacy. Different age groups have different needs, but all could benefit from understanding how to use AI responsibly and effectively. High school and college-aged students would benefit from knowing how to use AI as a learning tool without relying on it so much that it replaces critical thinking. On the other hand, seniors could benefit from classes that teach them how to use AI in a way that's realistic and simple for them to use in their lives.

How can our readers follow your work online?

You can connect with me on LinkedIn or follow Alorica's LinkedIn for updates on my latest media and thought leadership.

Thank you so much for joining us. This was very inspirational.