The Artificial Intelligence Golden Hexagon

Abstract: The Artificial Intelligence (AI) adoption spectrum across the government is very uneven. While most agencies have implemented simple AI-based applications such as automating simple workloads, developing application specific dashboards, or experimenting with simple machine learning predictive models, others are exploring cutting-edge AI-based solutions for near real-time intrusion and detection, recognizing objects in video data, or performing predictive maintenance. The problem is in the middle of the adoption spectrum. In this paper, we introduce the DATICS framework or the Golden Hexagon, an AI Framework to guide Federal agencies in their AI journey.

Data Science, Machine Learning, and AI are critical pillars in addressing national challenges and empowering Federal agencies to leverage data as a strategic asset and engage in the process of shaping enterprise-level data strategies to address national priorities and support evidence-based decision making, while efficiently and effectively delivering mission outcomes.

The many challenges that impede the adoption of AI and emerging technologies include the lack of a robust strategy, the underwhelming support for the modernization of systems and the development of data-driven platforms and applications, and the unavailability of the workforce to implement, monitor, and leverage data-driven solutions.

Challenges and Opportunities

Data Challenge: One of the most critical components of any operational entity is its data. To leverage the necessary data to support operations and mission-critical applications, a unified data management platform and tools and techniques for collecting, securing, analyzing, disseminating, and managing large volumes of data at high velocity with different data types and flows are crucial.

Innovation Challenge: Driving the transformation of the federal enterprise through innovation is essential to achieve mission outcome. However, innovation is a hard journey. It requires from any organization to transform itself and change its processes, services, business models while integrating risk and change management efforts. Innovation often involves failures as well as successes and happens in the margins while true digital transformation needs to happen at the core. To succeed, a federal agency should proceed with an operating framework that enables it to explore innovative projects with tangible, immediate impact congruent with its national mission.

Integration Challenge: Many functional areas will benefit from AI, but each might have different needs. There is urgency to evaluate if and how standardization and a better understanding of AI different methods can be leveraged for cross-cutting projects.

Scarce Talent: AI talent is in short supply. A lack of talent and internal advocacy remain a major roadblock.

Modern IT Infrastructure: Implementing AI technologies requires modern and effective infrastructures.

Change Management Champions: Change is difficult when it requires from any organization to transform itself and change its processes, services, business models while integrating risk and change management efforts. 

 Succeeding in this effort requires a robust, healthy, transparent ecosystem of robust data, human and infrastructure resources, and AI capabilities to support the entire business process from the genesis of the data to the experience of the end user. They include the creation of value at scale, reduction of time to market, optimization of procedures and processes, enhancement of data-driven decision making, improvement of the quality of services, and catalyzing economic growth and prosperity.

However, there are several risk factors such as effectively managing change and disruption, readying the workforce, efficiently developing and deploying AI-based complex products and services, leveraging an ethical and compliance framework, and ensuring data privacy and quality. 

The AI Golden Hexagon

While the United States Federal Data Strategy is a central component in promoting the adoption of Artificial Intelligence (AI) within the federal public sector, there is a need for a roadmap for success. I propose here an AI framework that includes six pillars/components that I coined the AI Golden Hexagon to empower effective data-driven digital transformation.

Figure 1. The AI Golden Hexagon

The six pillars include:

1. Data: The most value comes from being able to collect, aggregate, and correlate information from different kinds of systems.
2.  Data Strategy and Policies:  Capabilities and governance policies to support the ingestion, discovery, curation, and quality of data, as well as to ensure data security, privacy, and compliance.
3.  Analytics platform: Hardware, software and tools framework that enable and accelerate enterprise-grade AI projects. It should support the full Machine Learning/AI lifecycle from data genesis to model production, deployment, and monitoring.
4.  Modern IT infrastructure: A flexible, secure, powerful infrastructure where agencies are able to maximize secure use of cloud computing and effectively support the agency applications.
5.  Talent: A diverse mix of talent to translate mission needs into solution requirements, including the structure, skills, and processes required to execute AI projects at scale.
6.  Data-Driven Culture: Agencies must establish the organizational capability, including the support for a data-driven culture, responsible and ethical data-driven decisions, a system of governance and change management, all aligned with the agency mission and priorities.

? Chakib Chraibi, Ph.D., 2020