Drawing on Sol Rashidi’s insights

6 Lessons on AI and Data From Sol Rashidi

As adoption cycles for emerging technologies accelerate, leveraging AI and data wisely is crucial for driving real transformation. Sol Rashidi—a seasoned AI, data, and analytics leader—offers grounded, human-centric wisdom. Drawing from her experience across Fortune 500 firms and her book Your AI Survival Guide, here are the six standout lessons she shares:

1. Deployment Is Just the Starting Line

Launching an AI system into production isn’t scaling—it’s the beginning. True success depends on two equally critical non-technical pillars:

• Data protection and governance, to ensure AI systems don’t become liabilities.

• Workforce readiness, ensuring teams understand, trust, and adopt AI. LinkedIn

2. Check Your Data Reality, Honestly

Before chasing shiny AI use cases, ask:

• Is your data accessible, well-classified, and of decent quality?

• Are systems integrated—or are you hoarding data across silos?
  Rashidi has encountered organizations with dozens of data systems, only a fraction actually valuable. Strategy without execution—or data maturity—is just hallucination. LinkedIn

3. AI Amps, Doesn’t Replace

AI isn’t about cutting headcount—it’s about reimagining workflows. According to Rashidi:

• “Freed up” people often tackle backlogs.

• AI enables growth-focused work.

• Redundancies become reassignments.
  She urges: design for augmentation over automation, emphasize empathy, and invest in upskilling. LinkedIn

4. Align AI Strategy with a Parallel Data Strategy

AI’s power is limited by the strength of its data foundation. Whether it's fine-tuning or Retrieval-Augmented Generation (RAG), both require accessible, hygienic data. Rashidi’s admonition: “Don’t develop an AI Strategy without parallel pathing your Data Strategy.” LinkedIn

5. Stop Chasing Technobabble—Focus on Problem & People

Many AI failures boil down to thinking, not technology. Hiring brilliant data scientists and deploying buzzword-laden models doesn’t guarantee success. The fix lies in:

• Teaching business leaders AI fundamentals.

• Building cross-functional teams from day one.

• Letting strategy—not hype—drive deployment.
  And above all, match sophistication to real business maturity. LinkedIn

6. Don’t Ignore the People Side of AI

The toughest barriers to successful AI deployments are cultural, not technical:

• Resistance, fear, and inertia can derail projects.

• Change management is often underfunded or overlooked.

• Leaders must proactively reshape workflows, incentives, and structures—and do the heavy lifting post-deployment, not just pre-launch. siliconvalleytime.comGreg Walters Ai

Sol Rashidi’s approach is refreshing—and profoundly needed. AI success isn’t about cutting-edge models or data volume—it’s about:

• Alignment: matching aspirations with data maturity.

• Empowerment: lifting people to work with AI.

• Governance and culture: balancing trust, safety, readiness, and ethics.

Start small, solve real business pain, and grow AI fluency across the organization. Because the biggest wins come from the human-AI partnership—not AI solo.