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Artificial Intelligence in the Public Sector: A Maturity Model

The IBM Center for the Business of Government released my new report today.

Artificial Intelligence in the Public Sector: A Maturity Model

The technology is revolutionizing the way we derive value and insights from data in order to improve our daily lives. In addition, governments gather a treasure trove of pertinent data that can be used to execute important missions and improve services to the citizen. An effective AI program can greatly enhance the ability of the public sector to deliver on that promise.

The challenge has always been to design and implement an AI program that has all the critical elements in place to successfully achieve the goal of improved mission delivery and citizen services. An initial report commissioned by the IBM Center for The Business of Government, Delivering Artificial Intelligence in Government: Challenges and Opportunities, proposed an initial maturity model that gave public agencies a starting point for developing an AI capability. Subsequently, we have had the opportunity to fine tune the model, based on extensive research on how the public sector was deploying AI, documenting successful use cases and highlighting pitfalls and lessons learned.

The revised maturity model was shared with experienced public sector practitioners and feedback from these discussions led to a further revision. The revised model was then shared with a final group of reviewers that included public sector executives (both within and beyond the information systems domain), academics, and consultants.

We hope that this report provides public sector leaders a view into the “art of the possible” by emphasizing how AI programs can accelerate the transformation of government programs to better serve the public and by providing them a framework for establishing a successful AI program. We will continue to explore this topic and will provide further updates as the use of AI in the public sector continues to evolve.

To access the report, please click [Report]

A blog post on the report by Margie Graves (Visiting Fellow, IBM Center for the Business of Government, former Deputy Federal CIO for the Office of Management and Budget) is available here: [Post]

What are the key factors affecting smart city transformation readiness? Evidence from Australian cities

New paper co-authored with Tan Yigitcanlar, Kenan Degirmenci, and Luke Butler published in Cities.

Transformation into a prosperous smart city has become an aspiration for many local governments across the globe. Despite its growing importance, smart city transformation readiness is still an understudied area of research. In order to bridge this knowledge gap, this paper identifies the key factors affecting smart city transformation readiness in the context of Australian cities. The empirical investigation conducted in this study places Australian local government areas (n = 180) under the smart city microscope to quantitatively evaluate, through a multiple regression analysis, the key factors affecting their urban smartness levels—a proxy used for smart city transformation readiness. The findings disclose that the following factors determine about two-thirds (65%) of the smart city transformation readiness: (a) Close distance to domestic airport; (b) Low remoteness value; (c) High population density; (d) Low unemployment level, and; (e) High labour productivity. The study findings and generated insights inform urban policymakers, managers and planners on their policy, planning and practice decisions concerning smart cities.

To access the paper, please click [LINK]

Will AI ever sit at the C-suite table? The future of senior leadership

Graeme J. Watson, Vincent M. Ribiere, JakaLindi? and I have an article accepted in Business Horizons.

As the sophistication of artificial intelligence (AI) systems develop and AI becomes a key element of organizational strategy across a wide spectrum of industries, new demands are being placed on senior leaders. To understand the growing challenges leaders will face in the age of AI, we conducted interviews with 33 senior leaders in several countries across a wide range of industries. Our research highlights key capabilities and skills that leaders will require. Underlying these capabilities is a mindset oriented toward continuous learning and self-development, which will enable ongoing and rapid adaptation to change. Our findings identified the following key capabilities: digital know-how, data-driven focus, networking, ethics, and agility. To successfully navigate the coming era, senior leaders will need to focus on reskilling the workforce, recruiting and retaining highly skilled talent, building an intrapreneurial culture, and managing unprecedented changes in technologies and the nature of work.

To access the article [LINK]

Demystifying Analytical Information Processing Capability: Cybersecurity Incident Response

New paper published in Decision Support Systems

Little is known about how organizations leverage business analytics (BA) to develop, process, and exploit analytical information in cybersecurity incident response (CSIR). Drawing on information processing theory (IPT), we conducted a field study using a multiple case study design to answer the following research question: How do organizations exploit analytical information in the process of cybersecurity incident response by using business analytics? We developed a theoretical framework that explains how organizations respond to the dynamic cyber threat environment by exploiting analytical information processing capability in the CSIR process. This, in turn, leads to positive outcomes in enterprise security performance, delivering both strategic and financial benefits. Our findings contribute to the BA and cybersecurity literature by providing useful insights into BA applications and the facilitation of analytics-driven decision making in CSIR. Further, they contribute to IPT by providing new insights about analytical information needs, mechanisms to seek analytical information, and analytical information use in the process of CSIR.

To access the paper, please click here.