Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
September 10, 2025European Modern Studies JournalOpen Access

Ethical AI in Business Intelligence: Balancing Innovation with Responsible Data Use

View Full Paper
Ask AI
Bookmark
Share

Authors

PPPranitha PotturiFilm Independent

Discussion

Loading...

Member takes

Implication

The article explores ethical challenges like algorithmic bias and data privacy in AI-driven analytics, highlighting strategic approaches for businesses.

Key Points

  • The implementation of AI in business analytics presents significant ethical challenges, including algorithmic bias and transparency issues.
  • Evidence shows that organizations addressing ethical AI strategically, through measures like ethics committees, gain competitive advantages.
  • Practical approaches such as comprehensive bias testing and clear data usage policies can help navigate ethical dilemmas in AI.
  • A case study in financial services illustrates how improved oversight and accountability led to better customer relationships and regulatory standing.

Cite This Study

Pranitha Potturi (2025) studied this question.

synapsesocial.com/papers/68c183f89b7b07f3a060fc64https://doi.org/10.59573/emsj.9(4).2025.98
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Ethical Artificial Intelligence in Business: Frameworks, Challenges, and Responsible Implementation2026
  2. 2AI integration in business development: Ethical considerations and practical solutions2024 · 1 citations
  3. 3Ethics of Artificial Intelligence: Balancing Innovation with Privacy, Fairness, and Accountability2025 · 1 citations
  4. 4TOWARDS ETHICAL AND SUSTAINABLE DEVELOPMENT IN BUSINESS MANAGEMENT WITH AI2024
  5. 5Rethinking corporate responsibility in the age of Artificial Intelligence2026