Most leaders are asking the wrong question about AI.
They ask: “How can AI help me work faster?”
But according to Maria Colacurcio, CEO of Syndio, ( as told to Fortune) the real question is:
“How can AI help me think better?”
After moving beyond basic ChatGPT use and learning to build custom AI agents, Colacurcio discovered that AI’s greatest value isn’t drafting emails or summarizing documents. It’s strengthening executive judgment, challenging assumptions, and improving decision quality.
Here are the key lessons leaders can take from her experience.
1. Stop Using AI as a Better Search Engine
Most executives use AI for:
- Drafting emails
- Creating meeting agendas
- Summarizing documents
- Organizing information
While useful, these are low-value applications.
Leadership insight:
The biggest opportunity is not automation. It is augmenting strategic thinking.
2. Build AI Around Your Thinking Process
Colacurcio found generic AI outputs polished but disconnected from her voice and decision-making style.
Instead, she built AI agents trained on:
- Her communication patterns
- Past decisions
- Company strategy
- Customer conversations
- Leadership principles
- Institutional knowledge
Leadership application:
Create AI systems that understand:
- How you make decisions
- How you communicate
- What matters most to your business
- Your organization’s history
The result is an AI partner that thinks with context rather than generating generic answers.
3. Use AI as a Strategic Challenger
One of her most valuable AI agents acts as a strategic advisor.
Before major decisions, the agent asks:
- What evidence supports this?
- What assumptions are you making?
- What could go wrong?
- What would investors challenge?
- What are the unintended consequences?
Leadership application:
Use AI as a “devil’s advocate” before:
- Board meetings
- Executive presentations
- Strategic planning sessions
- Major investments
- Organizational changes
This helps identify weak logic before it becomes an expensive mistake.
4. Create an AI Chief of Staff
Colacurcio built an AI assistant that:
- Prioritizes emails
- Prepares meeting briefings
- Retrieves historical context
- Drafts follow-up communications
- Surfaces important information buried across systems
Leadership application:
An AI chief of staff can:
- Reduce administrative workload
- Improve preparation quality
- Ensure important context is never lost
- Help leaders focus on high-value decisions
5. Context Is the New Competitive Advantage
One of her biggest discoveries:
AI is only as good as the context it receives.
She doesn’t just feed her agents data.
She also captures:
- Customer sentiment
- Meeting observations
- Stakeholder concerns
- Body language cues
- Informal reactions
- Strategic insights
Leadership application:
Leaders should build a “memory layer” for AI by documenting:
- Lessons learned
- Decision rationale
- Customer feedback
- Market observations
- Team dynamics
The richer the context, the smarter the AI becomes.
6. Simulate Important Conversations Before They Happen
For board preparation, Colacurcio created profiles of board members based on:
- Previous discussions
- Public statements
- Investment philosophies
- Historical questions
Before meetings, she tests ideas against likely objections.
Leadership application:
Use AI to simulate:
- Investor questions
- Customer objections
- Executive concerns
- Stakeholder reactions
- Competitive responses
You enter the room having already debated the issue.
7. Protect Thinking Time
One of the most powerful lessons from her journey:
In the age of AI, information is abundant. Deep thinking is scarce.
Learning AI required dedicated time away from meetings and daily operational demands.
Leadership application:
Schedule time specifically for:
- Experimentation
- Reflection
- Strategic thinking
- AI exploration
AI does not replace thinking. It amplifies it.
8. Leaders Must Build, Not Just Delegate
A striking observation came from an engineering candidate who told Colacurcio she was the first CEO he had met who actively built AI agents herself.
Many leaders discuss AI strategy.
Few understand how the technology actually works.
Leadership application:
Executives do not need to become engineers.
But they should:
- Build simple agents
- Experiment personally
- Understand limitations
- Learn where AI succeeds and fails
Hands-on experience creates better AI decisions than relying solely on consultants or vendors.
What Leaders Should Be Doing Right Now
Start Small
Build one AI assistant for:
- Email review
- Meeting preparation
- Strategic questioning
- Customer research
Capture Organizational Knowledge
Create systems that store:
- Decisions
- Customer insights
- Project lessons
- Strategic rationale
Use AI Before High-Stakes Decisions
Ask AI to:
- Challenge assumptions
- Identify blind spots
- Simulate stakeholder reactions
- Stress-test recommendations
Train Teams to Build
Encourage employees to create and share AI workflows instead of merely consuming AI tools.
The Bottom Line
The first wave of AI focused on productivity.
The next wave is about judgment augmentation.
The leaders who gain the greatest advantage won’t be those who automate the most tasks. They will be those who use AI to:
- Think more clearly
- Recognize patterns faster
- Challenge assumptions earlier
- Enter critical conversations with deeper context
In a world where everyone has access to the same AI models, the real differentiator will be how effectively leaders combine human judgment with machine intelligence.