In May and June 2025, Huszár Consulting surveyed 143 senior professionals—mainly C-levels, founders, and team leads—across industries like technology, financial services, and professional services. The aim: to understand how AI is currently used in leadership and what holds back broader adoption.
Here’s what the data reveals.
In May and June 2025, Huszár Consulting surveyed 143 senior professionals—mainly C-levels, founders, and team leads—across industries like technology, financial services, and professional services. The aim: to understand how AI is currently used in leadership and what holds back broader adoption.
Here’s what the data reveals.
1. AI Usage Is Nearly Universal
A striking 97.6% of respondents report active use of AI in their work. This is not a hypothetical trend—it’s already happening.
Most common use cases include:
- Drafting or refining communication (e.g., emails, memos)
- Summarizing reports or documents
- Brainstorming and idea development
- Search and research tasks
Less common applications include coding (4.6%), image generation (4%), and video generation (1.5%). This suggests AI is primarily used for cognitive, communication-heavy tasks rather than technical development.
2. AI Is Already Impacting Leadership—But Not for Everyone
Over half (51.2%) of respondents say AI has already made them more effective leaders. Meanwhile, 36.6% believe it could help, but they haven’t seen the impact yet. Only 2.4% dismiss its relevance entirely.
This points to a key theme: belief in AI’s potential is high, but visible proof of impact varies. The strategic takeaway? The more it’s used in daily decision-making, the more tangible the value becomes.
3. Biggest Barrier? Lack of Time
When asked what’s holding them back from using AI more confidently, the top answer wasn’t ethics, trust, or compliance—it was lack of time (30.5%).
Other notable barriers include:
- Concerns about accuracy (23.2%)
- Legal or compliance risks (19.5%)
- Lack of integration into daily workflows (14.6%)
Interestingly, this marks a shift from earlier AI narratives focused on fear or ethics—today, practical adoption constraints are front and center.
4. Curiosity Runs Deep
The survey collected over 100 open responses on AI learning interests. Themes included:
- Prompt engineering
- Agentic workflows
- Tax and finance use cases
- Privacy and data security
Some responses even veered into AI’s societal and geopolitical impact—mentioning military regulation, quantum computing, and emotional development. A sign that leaders are thinking beyond just tools and toward long-term implications.
5. Strategic Insights for AI Adoption
The report outlines four practical recommendations for organizations:
- Start Where AI Is Already Used: Focus on augmenting communication and planning tasks rather than complex tech implementations.
- Create Time-Efficient Learning Paths: Short, targeted sessions could help busy executives gain hands-on confidence with AI.
- Coordinate Collective Reasoning: Since AI use often starts with individuals (“shadow AI”), companies should support and scale these grassroots experiments.
- Top-Down Engagement: C-levels must engage with AI tools themselves to lead by example and make informed strategic decisions.
Final Thought
This survey doesn’t aim to represent the entire market—it’s a directional signal from innovation-forward professionals already experimenting with AI. But it’s clear that the wave of adoption is underway, and the focus is shifting from why to how.
Board Reflections from Treasury Masterminds
We asked a few of our board members to react to the findings. Their comments will be added below. Want to share your own experience with AI in treasury? Join the conversation on Treasury Masterminds or drop your thoughts in the comments. Is this data reflective of your reality?
COMMENTS
Daniel Huszár, AI Strategist & Educator, comments:
The findings reflect something I’ve been seeing in conversations for months. Many people are using large language models daily. They rely on them to write, research, summarize, and think. But more importantly, many are beginning to ask a different kind of question, not just “what can this tool do,” but “how do we structure work around it?”
People are now thinking about agents, orchestration, and how to build systems around AI. A lot of these voices are coming from leaders, consultants, and managers. People who may not call themselves “technical” but are actively using AI to help them work.
It also means that if you’re waiting to “get more technical” before engaging with AI, you might be waiting too long. If you can write a clear sentence, you can prompt a model. If you understand your team’s needs, you can begin to design AI support.
One of the strongest themes I am seeing: those who use AI regularly are more confident in its potential, and more aware of its limitations. That confidence comes from trial and error.
So if there’s one thing I’d encourage, it’s this: use the tools. Start today. Build your own understanding by experimenting, especially before thinking about automating everything with AI agents.
Bojan Belejkovski, Treasury Masterminds Board Member, comments:
Across industries, I’m seeing (a rather slow) AI shift from abstract hype to a practical tool for speeding up decisions, refining communication, and surfacing strategic options faster. I believe the real value isn’t in technical complexity but how AI helps leaders analyze trade-offs, align teams, and drive action with more clarity.
That said, one barrier that I keep noticing, and is still holding people back, is fear of being replaced or becoming less relevant. At all levels. However, staying away from AI only delays the learning curve and limits your value. The leaders embracing AI aren’t trying to replace judgment because they’re using it to sharpen thinking and operationalize strategy more effectively.
Tanya Kohen, Treasury Masterminds Board Member, comments:
This is a great conversation. I’d offer you that one of the most valuable roles AI can play for leaders isn’t necessarily in decision-making itself, but in preparing for it. AI can help reduce bias by utilizing broader information sources, spotting patterns, and distinguishing correlation from causation. These are tasks that often distort judgment simply because leadership doesn’t have the time or access to relevant information. Used thoughtfully, AI can serve as a powerful partner in thinking, helping leaders ask better questions before rushing to answers.
The hesitation around AI adoption often gets framed as a time issue, but I think it’s more rooted in unfinished digital transformation. Many organizations are still working through messy data, siloed systems, and unclear process ownership. Without clean inputs and a shared understanding of “what’s true,” even the best AI tools won’t deliver meaningful results. Leaders may want to lean in, but the foundation isn’t quite solid yet.
That’s why the biggest opportunity lies in fixing the basics like streamlining access to data, creating clarity on ownership, and making sure teams at every level can trust and act on the same information.
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