Integration Innovation, Inc. (i3)

Mark Zais

Decision Intelligence Champion

Mark Zais, PhD, is Senior Technologist and Director of Data & Analytics at i3-Corps (Integration Innovation, Inc.). A former Army Colonel and Chief Data Scientist at USSOCOM, he holds a PhD and a Master's degree in Operations Research from the University of Colorado Boulder and Georgia Tech, specializing in data science and machine learning for government and military applications.

Shaping Defense Futures

As Senior Technologist and Director at Integration Innovation, Inc. (i3), I work with defense organizations applying data, analytics and emerging technologies to address complex mission challenges. My work focuses on advanced analytics, artificial intelligence (AI) and operations research in environments where informed decisions matter most. Throughout my career, I have seen that technology creates the greatest value when it helps people make better decisions.

My path into technology leadership began as a helicopter pilot before I transitioned into operations research and data science. During a twenty-six-year Army career, I worked across economic analysis, maintenance, intelligence, operations and policy, including assignments supporting senior government leaders within the Office of the Secretary of Defense. Exposure to those diverse roles taught me that technical expertise only creates value when it is translated into information decision-makers can trust, understand and act upon. It also taught me how to communicate complex analytical insights to senior leaders responsible for high-consequence decisions.

Working across multiple domains reinforced another important lesson. While technical skills can transfer relatively easily from one field to another, leadership often requires credibility within a specific sector and a deep understanding of its mission and operating environment. Whether supporting intelligence operations, maintenance planning, economic analysis or policy development, success depends on combining technical expertise with operational understanding and building teams that understand the technology and the mission.

Turning Analytics into Decision Advantage

One of the biggest challenges organizations face is turning investments in analytics and technology into meaningful business value. While technical capabilities continue to advance, the real obstacles are often organizational rather than technical.

Trust, data literacy and legacy architectures continue to stand in the way. People need confidence in analytical outputs and the ability to interpret them effectively. Even when the analysis is sound, fragmented workflows can keep insights from reaching the right people at the right time.

  ​We balance innovation with disciplined delivery ensuring emerging technologies meet security compliance and reliability requirements while aligning research investments with mission priorities and customer needs.   

Another common challenge is problem definition. Organizations are often eager to build tools, models and AI-enabled capabilities, but success begins with clearly understanding the problem they are trying to solve. Without that foundation, even the most sophisticated systems can fall short of expectations.

Moving from military service into industry offered a different perspective on technology development. Industry environments often provide greater organizational stability, but they also place a stronger emphasis on disciplined execution and measurable outcomes. Compared with military environments, there is often less tolerance for failure, which has reinforced my belief in balancing innovation with incremental progress and practical delivery.

Aligning Research Investment with Mission Needs

Defense organizations must adopt emerging technologies while meeting demanding security, compliance and reliability requirements. Earlier in my career, I was hesitant to deploy models when I could not clearly explain how they reached their outputs. As AI systems have advanced, however, traditional approaches to explainability have become increasingly difficult to apply.

Research has found that large language models can sometimes reach the same conclusion in different ways. Understanding how a model arrives at an answer is still valuable, but it does not provide the full picture. Organizations also need clear policies, oversight mechanisms and risk controls to guide how AI is developed, deployed and used, especially in environments where mistakes can have serious consequences.

These challenges are especially important in the defense sector. New technologies can create significant advantages, but adopting them requires careful attention to security, compliance and operational needs. The stakes are even higher when AI is used in mission-critical environments, where reliability, accountability and trust are essential.

Meeting that challenge requires more than creating new technologies. It also depends on how quickly new capabilities can be acquired, developed and delivered to users. While efforts to streamline government acquisition processes are intended to speed adoption, they can create distinct challenges for medium-sized companies.

For medium-sized firms such as i3, with about 800 to 900 team members, research and development investments must be carefully aligned with customer needs. Larger organizations often have greater freedom to invest ahead of potential requirements and absorb the uncertainty that comes with those decisions. Medium-sized firms generally have less room for error and face greater financial and operational risk when requirements have not yet been fully defined.

Although streamlined acquisition processes are designed to accelerate innovation, they can sometimes favor larger organizations with the resources to invest ahead of anticipated requirements and absorb uncertainty more easily. As a result, compressed acquisition timelines can place mid-sized companies under greater pressure, potentially reducing the diversity of organizations able to bring innovative solutions to the defense sector.

Preparing for the Next Inflection Point

I believe agentic AI represents the next significant inflection point in decision-support technology. For organizations operating in high-tempo environments, these capabilities may represent the next significant step in the evolution of decision-support technologies.

At the same time, enterprise data platforms are beginning to address longstanding challenges related to fragmented information. As organizations gain access to trusted, integrated data, their ability to generate insights and support better decisions expands. In many cases, solving data fragmentation may prove just as important as adopting the latest AI capability.

Security remains a critical concern. The gap between AI capability and AI security continues to widen, introducing risks such as model poisoning, training-data manipulation, adversarial inputs and prompt injection attacks.

AI security introduces a unique challenge because vulnerabilities can remain hidden for months before they surface. That makes them harder to detect and address than many traditional cybersecurity threats. In defense environments, the consequences are not just technical. AI security failures can create strategic vulnerabilities that jeopardize mission success and erode trust in critical systems.

Part of my role involves ensuring AI innovation and AI security receive equal attention.

Developing the Next Generation of Leaders

When I speak with aspiring technology leaders, I encourage them to focus on becoming effective translators between technical practitioners and decision-makers. Advancing into senior leadership requires more than building models, tools or systems. It requires speaking the language of the mission or business with the same credibility you bring to technology.

I encourage professionals to seek experience across industries and mission areas. Exposure to multiple environments broadens perspective, strengthens judgment and helps leaders develop the expertise expected in senior roles.

Throughout my career in aviation, operations research, analytics, defense missions and technology leadership, one lesson has remained constant. The best outcomes occur when technology, people and mission objectives are aligned around real-world challenges. The same principle applies to leadership. As AI and advanced analytics continue to evolve, I remain focused on applying them in ways that deliver meaningful results and advance i3's mission.