Infusing AI Technologies Into the Intelligence Analysis Process

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Table of Contents

Discussion
Challenges and Management Approaches
Concluding Points
References

Discussion

It is worth noting that many experts in the field believe that artificial intelligence (AI) can significantly transform the work of the Intelligence Community (IC). However, AI is not able to learn without human intervention, and specialists will have to make efforts to obtain and clean up data, compile classifications, and train machines and employees (Weisgerber, 2018). The purpose of this paper is to discuss what management challenges may be anticipated in infusing new technologies into the Intelligence analysis process and recommend management approaches for integrating technologies into the ICs work.

Challenges and Management Approaches

The main difficulties in applying such technologies lie in their expediency. In its turn, the feasibility of introducing new technologies is determined by the effect of the final results and the costs of developing and testing AI technologies as applied to the Intelligence analysis process. The rationale for the resources spent during these processes is another challenge (Jarmon, 2020). When developing innovative solutions, mistakes and forced repetitions accompanying such a process are also considered as spent resources, since they divert the ICs cognitive resource (the workforce), which is used less productively.

Moreover, project management is inseparable from the active investment of financial resources since only the merger of these two processes ensures the achievement of the target effect from the development of a new technological solution. Also, resistance to change is a challenge to overcome when incorporating AI into analysis processes (Jarmon, 2020). In particular, the staff operating the tools will need to undergo intensive training, which might cause objections from the side of the ICs workforce.

It is impossible to determine which specific approaches will be most effective since it depends on the type and form of artificial intelligence being introduced. Before applying the new system, management needs to understand how it works, what operational tasks it will perform, and in which operating environments it will be used. In particular, it is essential to make sure that the program provides an understandable decision-making procedure, which specialists of the departments will be able to verify (Scharre & Horowitz, 2018).

With the support of a trained workforce, management needs to consider how the desired results of the software used will be achieved, especially in the case of machine learning. To gain confidence in the results, management needs to ensure the transparency of the applied approaches and procedures. However, to accomplish this task, it will have to find a compromise between transparency in the decision-making process, system performance, and functionality.

Apart from that, management should make sure the goals of infusing new AI technologies into the Intelligence analysis process are in line with the ICs strategy. Insights should then be passed to technology designers and teams managers to make sure they are incorporated into the tools and processes (Allen & Chan, 2017). With the right tools and a clear strategy in place, it will be easier to educate the workforce on new approaches and minimize resistance to change.

Concluding Points

Thus, it can be concluded that the success of introducing new technologies depends not only on the usability of the selected tools but also on strategically correct management approaches. With consistent integration, artificial intelligence can become a constructive force that will resolve operational problems associated with the underdevelopment of technological processes in IC. For this reason, it is necessary to properly prepare the workforce for this infusion and offer a clear vision and action plan so that the introduction of artificial intelligence is not inhibited.

References

Allen, G., & Chan, T. (2017). Artificial intelligence and national security. Retrieved from Belfer Center for Science and International Affairs.

Jarmon, J. A. (2020). The new era in U.S. national security: Challenges of the information age (2nd ed.). New York, NY: Rowman & Littlefield.

Scharre, P., & Horowitz, M. C. (2018). Artificial intelligence: What every policymaker needs to know. Washington, DC: Center for a New American Security.

Weisgerber, M. (2018). General: Project Maven is just the beginning of the militarys use of AI. Defense One. Web.

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Infusing AI Technologies Into the Intelligence Analysis Process

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