How to embrace innovation in the age of AI

Minerva’s career exemplifies the belief that innovation is essential. Originally aspiring to be a brain surgeon, she pivoted to technology and became a chief AI officer, holding four patents along the way. Her early work in natural language processing laid the foundation for today’s large language models.

Throughout her career in city government, she led initiatives involving free Wi-Fi expansion, open data legislation, privacy laws and early artificial intelligence (AI) governance frameworks. She helped build Grasshopper Bank from the ground up, improving digital onboarding processes, compliance checks and fraud-detection workflows.

As she shared during the session, “I’ve invented every job I’ve had because that job didn’t exist before I had it.” Her journey reinforces the message that innovation is not optional; it’s essential.

Key actions for successful AI implementation

Minerva views AI adoption as a journey rather than a destination. Based on her experience leading large-scale innovation efforts in both the public and private sectors, Minerva suggested some practical guidelines that organizations might consider when working to implement AI successfully:

1. Develop a clear, modular roadmap

AI transformation cannot happen overnight. Break down the process into modular steps and set a realistic three-year plan. This approach helps maintain momentum without overwhelming resources.

2. Clarify capabilities and limitations

Understanding what technology can and cannot do builds trust and prevents overpromising. Designing systems with modularity allows organizations to enhance solutions as technology evolves.

3. Start with quick wins

Identify low-hanging fruit — projects that deliver immediate value — while planning for more complex long-term solutions. This builds momentum and stakeholder confidence.

4. Establish data integrity

Data is the fuel for AI. Use reconciliation agents to double-check data before official reporting to reduce errors and build trust in AI-driven insights.

5. Champion cross-departmental collaboration

Innovation requires strong leadership at every milestone. Whether aligning fire and police departments or coordinating 311 and 911 systems, seamless integration of new technologies requires collaboration.

6. Make smart build vs. buy decisions

Focus internal development on what is unique to your organization. Purchase what can be commoditized and avoid vendor lock-in so you can pivot as business needs evolve.

7. Approach risk management as a learning practice

Hold discussions to anticipate risks. When something fails, conduct a post-mortem to identify what can be improved. Intellectual honesty and a learning culture are essential for innovation.

Conclusion

As Minerva says, “The best way to predict the future is to invent it.” In an era where AI has moved from niche to mainstream, organizations that prioritize innovation may play a significant role in shaping the next chapter of progress. The challenge isn’t whether to innovate; it’s how quickly and effectively you can start.

Organizations that lead with vision, adaptability and a commitment to learning will not only survive but thrive in the age of AI.