• IEEE.org
  • IEEE CS Standards
  • Career Center
  • About Us
  • Subscribe to Newsletter

0

IEEE
CS Logo
  • MEMBERSHIP
  • CONFERENCES
  • PUBLICATIONS
  • EDUCATION & CAREER
  • VOLUNTEER
  • ABOUT
  • Join Us
CS Logo

0

IEEE Computer Society Logo
Sign up for our newsletter
IEEE COMPUTER SOCIETY
About UsBoard of GovernorsNewslettersPress RoomIEEE Support CenterContact Us
COMPUTING RESOURCES
Career CenterCourses & CertificationsWebinarsPodcastsTech NewsMembership
BUSINESS SOLUTIONS
Corporate PartnershipsConference Sponsorships & ExhibitsAdvertisingRecruitingDigital Library Institutional Subscriptions
DIGITAL LIBRARY
MagazinesJournalsConference ProceedingsVideo LibraryLibrarian Resources
COMMUNITY RESOURCES
GovernanceConference OrganizersAuthorsChaptersCommunities
POLICIES
PrivacyAccessibility StatementIEEE Nondiscrimination PolicyIEEE Ethics ReportingXML Sitemap

Copyright 2025 IEEE - All rights reserved. A public charity, IEEE is the world’s largest technical professional organization dedicated to advancing technology for the benefit of humanity.

  • Home
  • /Publications
  • /Tech News
  • /Research
  • Home
  • / ...
  • /Tech News
  • /Research

Strategies to Tackle Uncertainty With AI Deployment

By IEEE Computer Society Team on
December 19, 2022
LATEST NEWS
From Isolation to Innovation: Establishing a Computer Training Center to Empower Hinterland Communities
From Isolation to Innovation: Establishing a Computer Training Center to Empower Hinterland Communities
IEEE Uganda Section: Tackling Climate Change and Food Security Through AI and IoT
IEEE Uganda Section: Tackling Climate Change and Food Security Through AI and IoT
Blockchain Service Capability Evaluation (IEEE Std 3230.03-2025)
Blockchain Service Capability Evaluation (IEEE Std 3230.03-2025)
Autonomous Observability: AI Agents That Debug AI
Autonomous Observability: AI Agents That Debug AI
Disaggregating LLM Infrastructure: Solving the Hidden Bottleneck in AI Inference
Disaggregating LLM Infrastructure: Solving the Hidden Bottleneck in AI Inference
Read Next

From Isolation to Innovation: Establishing a Computer Training Center to Empower Hinterland Communities

IEEE Uganda Section: Tackling Climate Change and Food Security Through AI and IoT

Blockchain Service Capability Evaluation (IEEE Std 3230.03-2025)

Autonomous Observability: AI Agents That Debug AI

Disaggregating LLM Infrastructure: Solving the Hidden Bottleneck in AI Inference

Copilot Ergonomics: UI Patterns that Reduce Cognitive Load

The Myth of AI Neutrality in Search Algorithms

Gen AI and LLMs: Rebuilding Trust in a Synthetic Information Age

FacebookTwitterLinkedInInstagramYoutube
Get the latest news and technology trends for computing professionals with ComputingEdge
Sign up for our newsletter

Strategies for artificial intelligence deploymentStrategies for artificial intelligence deploymentThe power of AI comes with a lot of responsibilities. It has changed a lot about our world, but the change has been a double-edged sword. It is responsible for a lot of progress, but some risks and unknowns are involved in its use. Because of this duality, most business leaders are unsure how to use and deploy AI systems. Still, they can look to public agencies that have already experienced these uncertainties in AI initiatives for some answers.

The 5 Major Areas of AI Uncertainty


Since 2014, Queensland University of Technology has engaged in around 40 projects that deal with AI efforts in the public, private, and nonprofit sectors in Australasia and the United States. However, most of the recommendations were drawn from the public sector. This experience allowed them to observe managers’ use of AI firsthand, and they found five major areas of uncertainty.

1. Communicating Realistic Expectations

From these projects, the team found that managers weren’t sure about the outcome of AI initiatives, and there were four main ways they thought about AI:

  • AI is overhyped
  • AI can fully automate tasks
  • No opinion
  • AI isn’t perfect, but it is getting better every day

The last group has the right idea. Skill training and accountability were the best way to gain support from the first three groups. This education needs to begin with communicating what AI can accomplish and what it can’t.


Want More Tech News? Subscribe to ComputingEdge Newsletter Today!


2. Assessing How AI Fits Tasks

Managers struggled with evaluating how AI fits into their business. It is the degree of discretion that determines how to fit AI into a task. Repetitive, low-level tasks like data entry or facilities operation are examples of a low-discretion take suitable for total automation. For tasks that require medium discretion, like developing a hiring process, AI can augment human decision-making. But AI should not make highly sensitive and complex decisions.

3. Clarifying a Path for Deployment