The modern battlespace of land, air, and sea is creating an increasingly large and near-infinite amount of data. Sensor data, target information, operational data, and now even financial and administrative data, are part of what both the U.S. and our adversaries are using to see the full war-fighting picture. Artificial intelligence (AI) has emerged as the path to fully optimize how we run the operational, tactical, and business work conducted by the Department of Defense.   

There’s no denying that AI is inherently changing the landscape of the national security sector. Digital transformations are reshaping business as we know it—for the better. If we are smart about applying AI to the initiatives we face, it can be a transformative enabler for our military branches.  

The path to AI optimization is not the availability of powerful AI tools, but the fundamental requirement is for these tools to access usable data. The massive amount of data coming off today’s battlespace must be ready, clean, transparent, organized, tagged, and usable. Without a “data-ready” organization, these powerful AI tools will range from lacking accurate results to wholly unusable outputs.    

Is your DoD organization AI-ready?  

If it were as easy as seeding data into an AI system, we’d all be up and running by now. But the fact is, these complex systems—which help drive decision-making and critical automation—are heavily reliant on:  

• Compliance, especially with federal mandates (DoD, NIST, CMMC),  

• Security and scalability, and  

• Quality data.  

The truth is that AI is only as good as the data these systems are given. We must ensure that the data at the tactical edge is decision-worthy and has undergone disciplined and analytical rigor to assess data readiness. These systems need high-quality, clean, and consistent data to work effectively. If your data is riddled with inconsistencies, inaccuracies, and errors, your AI models will inherit these flaws, leading to inaccurate results and unreliable insights. Building a reliable system requires accurate, relevant, and complete data. 

At Ignite Digital Services, we’re helping DoD clients with AI data readiness by first asking: 

• Is your data aligned with governance and compliance needs? Usually, this means implementing stewardship, policies, and regulatory measures to achieve this critical alignment. 

• How’s your data’s quality and standardization? Whatever you need to do to bring data to a state of accuracy, completeness, and consistency, do it. Then, enact protocols to maintain this level. 

• Do you have security and access controls? Now is the time to enact or enforce Zero Trust, RBAC/ABAC, and encryption processes. 

• What is your data infrastructure and interoperability like? It wouldn’t hurt to pull ETL, cloud integration, and data pipeline levers to strengthen your comprehensive data framework. 

These questions lead you to the core consideration you should ask before you begin an AI project: Can you support AI and analytic processing with your data sets? You need structured, bias-free, scalable data sets to power AI work. Full stop. What does your organization need to make this happen? 

Behind every impressive AI application, from predictive analytics to personalized recommendations, lies an unsung hero: Data readiness. Is your data ready?