Legacy companies which have been around for more than 20 years have been always slow to embrace new technologies & the case is also very true with embracing AI technologies.
Companies relutcantly start few AI projects - only to abandon them.
Here are are the top 7 challenges AI projects face in legacy companies:
1. Management Reluctance
Fear of Exacerbating asymmetrical power of AI
Need to Protect their domains
Pressure to maintain statusquo
2. Ensuring Corporate Accountability
Internal Fissures
Legacy Processes hinder accountability on AI systems
3. Copyrights & Legal Compliance
4. Lack of Strategic Vision
5. Data Authenticity
6. Understanding Unstructured Data
7. Data Availability
Companies relutcantly start few AI projects - only to abandon them.
Here are are the top 7 challenges AI projects face in legacy companies:
1. Management Reluctance
Fear of Exacerbating asymmetrical power of AI
Need to Protect their domains
Pressure to maintain statusquo
2. Ensuring Corporate Accountability
Internal Fissures
Legacy Processes hinder accountability on AI systems
3. Copyrights & Legal Compliance
- Inability to agree on data copyrights
- Legacy Processes hinder compliance when new AI systems are implemented
4. Lack of Strategic Vision
- Top management lacksstrategic vision on AI
- Leaders are unaware of AI's potential
- AI projects are not fully funded
5. Data Authenticity
- Lack of tools to verify data Authenticity
- Multiple data sources
- Duplicate Data
- Incomplete Data
6. Understanding Unstructured Data
- Lack of tools to analyze Unstructured data
- Middle management does not understand value of information in unstructured data
- Incomplete data for AI tools
7. Data Availability
- Lack of tools to consolidate data
- Lack of knowledge on sources of data
- Legacy systems that prevent data sharing
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