Working Effectively With IT And Legal On AI Initiatives

Working Effectively With IT And Legal On AI Initiatives

Repeat with me: IT and Legal are friends, IT and Legal are friends, IT and Legal are friends. OK, we can start now! 😉

The common perception that "IT and Legal will never approve" can be a barrier to AI project success. However, there's potential for productive collaboration.

Key point: Early and strategic engagement with IT and Legal can significantly improve AI project outcomes.

Why it's important: Collaboration can lead to more efficient approvals, enhanced security measures, and better risk management.

A 7-Step Plan for Effective Collaboration

1. Start conversations early proactively: Discuss ideas before finalizing plans; gather initial feedback on potential concerns.

2. Find common objectives: Explain how AI aligns with company goals; identify shared interests and priorities.

3. Set up communication structures: Assign primary contacts for each team; schedule regular update meetings.

4. Make decisions together: Create a framework for key project decisions; acknowledge and utilize each team's expertise.

5. Work on policies and training as a team: Propose initial AI usage guidelines and training (if not available); revise based on IT and Legal input.

6. Evaluate risks collaboratively: Identify potential issues from all perspectives; develop strategies to mitigate identified risks.

7. Plan for ongoing oversight: Create a schedule for reviewing AI tool use; define relevant metrics for all teams involved.

Suggestion: Use a shared digital workspace for centralized project tracking and communication.

Four Key Areas to Address in AI Tool Adoption

When implementing new AI capabilities, consider these aspects in the terms and conditions documentation.

Pro tip: Show you did your homework and bring it to discuss with IT and Legal proactively.

1. Data Usage and Privacy

Potential issues:

• Use of personal data without clear consent

• Broad third-party data sharing allowances

• Unclear data retention timeframes

Possible measures:

• Create guidelines for handling sensitive data

• Select providers offering detailed data control options

• Implement clear data management processes

2. Intellectual Property Considerations

Potential issues:

• Broad content licensing terms

• Unclear ownership of AI-generated content

• User responsibility for all potential infringements

Possible measures:

• Seek specific, limited content licenses

• Clarify ownership of AI outputs in agreements

• Establish a process for content review and usage

3. Terms of Service Considerations

Potential issues:

• Unannounced changes to terms

• Extensive liability limitations

• Mandatory arbitration clauses

Possible measures:

• Monitor for terms of service updates

• Discuss liability terms for critical applications

• Consider implications of arbitration requirements

4. Security Protocols

Potential issues:

• Limited security assurances

• User-only security responsibility clauses

• Inadequate breach notification policies

Possible measures:

• Consider providers with recognized security certifications

• Develop internal AI tool security protocols

• Discuss prompt breach notification terms

Important note: Terms and conditions can change and may vary by service tier (e.g., free, individual, enterprise levels). Always review the most current legal documents from service providers' official websites to stay informed about data usage and your rights when using AI tools.

Disclaimer: This is a non-exhaustive list. This summary is based on personal experience and research for educational purposes only. Please seek formal IT and legal advice from qualified professionals at your company (or third party) before contracting any new AI tool. 😎