The State of AI 2025:
What Leaders Really Think
Data Report by Mayven Studios
Based on in-depth conversations with 20+ senior executives across industries including SaaS, healthcare, construction, marketing, biotech, legal tech, and enterprise software.
Executive Summary
We spoke with 20+ senior executives, founders, and CEOs across diverse industries. The verdict: AI isn't just changing how businesses operate it's creating an entirely new landscape of opportunities and anxieties that most companies are struggling to navigate.
Our research reveals a striking paradox: while 92% of executives believe AI is critical to their future success, nearly 80% admit they're uncertain whether they're using it effectively or missing crucial opportunities.
Every executive expressed concern about being left behind.
Most companies have AI tools but lack strategic deployment.
Success demands fundamental mindset shifts, not just technology adoption.
Roles are transforming rather than disappearing.
Smaller, AI-enabled teams are outperforming larger traditional teams.
Human connection becoming more valuable, not less.
Methodology
Between March and August 2025, Mayven Studios conducted comprehensive interviews with C-level executives, founders, and senior leaders across multiple industries. Each conversation lasted 30-45 minutes and focused on real-world AI implementation experiences, challenges, and outcomes.
Industries Represented
- SaaS and Technology
- Marketing and Sales
- Healthcare and Biotech
- Construction and Infrastructure
- Media and Entertainment
- Legal Technology
- Manufacturing and Hardware
The Universal AI Anxiety
"Are We Missing Out?"AI anxiety is everywhere. Execs fear competitors are pulling ahead, current skills becoming obsolete, and money being wasted. Perhaps the most striking finding from our research was the universal nature of AI anxiety among business leaders. As one founder of The Vets, put it:
"There is tremendous amount of people that were very valuable two years ago and now it's a problem because the code is becoming irrelevant, the design is becoming irrelevant."
Michael Kravec, CSO & Co-Founder of Blue Yeti captured this sentiment perfectly:
"Is there some tool? Is there some functionality that if I was using it correctly, integrating into my business would be making massive impacts? If I'm not doing it today, what am I missing out on?"
- Competitive Disadvantage 86% fear competitors are getting ahead with AI
- Skills Obsolescence Concern that current capabilities will become irrelevant
- Investment Uncertainty Difficulty knowing where to allocate AI resources
- Competitive Disadvantage How to transform organizational culture and processes
Overwhelmed and Unsure
Our interviews revealed a consistent pattern: executives aren't just uncertain about AI, they're overwhelmed by the pace of change and the complexity of options available. KC Brothers, Director of Product Marketing at Canopy noted:
"AI wasted no time. It came straight for the jugular with marketing."
Yet even as a product marketing director, she admitted the challenge of keeping up:
"There's a lot of anxiety and uncertainty on are we using AI enough? I think everybody feels that way."
The Implementation Challenge: Tools vs. Strategy
Having AI vs. Using AI EffectivelyMost firms have AI tools. Few use them effectively. That’s the “implementation gap.”
A critical insight emerged from our research: most companies already have AI tools, but very few are using them strategically.
This creates what we call "The Implementation Gap", the space between having AI capabilities and actually transforming business outcomes.
The #1 blocker? Dirty, siloed data.
- Multiple AI subscriptions across teams
- Little coordination or strategy
- Unclear ROI measurement
- Individual experimentation without
- organizational alignment
- Pilot programs and limited testing
- Waiting for "best practices" to emerge
- Risk-averse approach to deployment
- Limited investment and commitment
- Systematic approach to AI adoption
- Clear business objectives tied to AI initiatives
- Cultural change management programs
- Measurable business outcomes
As Benu Agarwal, President and Founder of Milestone observed:
"AI is not about bouncing back, it's bouncing forward. Most companies are challenged with trying to understand this because it's not their job to understand it."
The Data Foundation Problem
Multiple executives highlighted a fundamental challenge: AI effectiveness depends on data quality, but most companies haven't invested in proper data infrastructure. Yar Salek, CTO and CoFounder of DeepCell, whose company has trained AI models on over 3 billion images, emphasized:
"Life science data has been residing in silos for too long... The industry is used to just behaving in silo. And now we're trying to change that."
Michael Corr, CEO at Duro Labs reinforced this point:
"If your internal data is not consolidated, it's not clean, then training your model...will fail"
The Cultural Transformation Imperative
Mindset Shifts RequiredTech isn’t the hurdle — culture is. Fast adopters lean into curiosity, change, and continuous learning.
Our research revealed that successful AI adoption isn't primarily a technology challenge. It's a cultural one. Companies that achieve meaningful results from AI investments share common cultural characteristics.
The "Learn It All" vs. "Know It All" Culture
Benu Agarwal outlined what she calls an 8-step process for building an AI-first culture as shown below.
The Leadership Challenge
Dori Fussmann highlighted a crucial insight about organizational adaptation:
"The capabilities and skills and the ability to influence workflows is already here. Individuals that are focused on it can actually utilize it, but it takes organizations a lot of time to adapt."
This creates what we call "The Adoption Velocity Gap"—the difference between individual capability and organizational implementation speed.
Successful AI Leaders Share These Traits:
- Curiosity over Certainty: Embracing continuous learning
- Systems Thinking: Understanding AI as an enabler, not a solution
- Cultural Sensitivity: Managing change with empathy
- Strategic Patience: Balancing speed with sustainability
Skills Evolution: Transformation, Not Replacement
The Great ReconfigurationContrary to fears about AI eliminating jobs, our research suggests something more nuanced is happening: roles are being elevated and reconfigured rather than eliminated.
KC Brothers from Canopy explained:
"Your content writer today needs to become content strategist. Your coder today needs to not only code, but they need to be able to see if what they are coding aligns with workflows and aligns with impact they're trying to create."
Engineering and Product
- Individual contributors → AI orchestra conductors
- Feature builders → Workflow designers
- Problem solvers → Problem definers
Greg Bayer, CoFounder & CEO at Taylor AI described the shift:
"Instead of having like your quintessential BDR, SDR combo, cold emails, sequence, maximizer, marketing hybrid. We've specifically said in the world of enterprise SaaS, we want to go with relationship driven people."
The 90/10 Rule
A pattern emerged across interviews: AI can handle approximately 90% of routine tasks, but the human contribution becomes more valuable, not less.
The 90/10 Rule of AI Value
AI can handle approximately 90% of routine tasks, but the remaining 10% of human contribution becomes more valuable, not less.
Allyson Havener, CMO at TrustRadius noted:
"You can get maybe help you have one product marketer and then like, let's say like, you start to we verticalize some of our marketing and some of our AEs. Great, you don't need a product marketer for you to vertical, you need one product marketer that can use AI."
The Small Team Revolution
Doing More with LessOne of the most striking findings was how AI is enabling smaller teams to achieve results that previously required much larger organizations.
3-person marketing team generating demand equivalent to previous 10-person team
$2M budget achieving same results as previous $10M+ spends
50-person company generating $2M+ in revenue (previously required 100 people)
AI enabling 10x productivity improvements in marketing initiatives
Real Examples from Our Interviews:
TrustRadius (Allyson Havener, CMO)
- 3-person marketing team generating demand equivalent to previous 10-person team
- $2M budget achieving same results as previous $10M+ spends
- Focus shifted from team size to team leverage
Concord (Matt Lhoumeau, CEO)
- 50-person company generating $2M+ in revenue
- Previous 100-person team doing less with more resources
- AI enabling 10x productivity improvements in marketing initiatives
Taylor AI (Greg Bayer, Founder)
- Team of senior engineers outproducing previous 20-person junior/senior mix
- Focus on autonomous, high-level contributors
- AI handling routine tasks, humans focusing on architecture and strategy
The Talent Recalibration
Sean Lee, CEO at OpenDrive crystallized this shift:
"We hire people for their cognitive ability. Because the information with the advent of the internet, everybody can go get the information. And even now with AI, maybe even more so... So it's what do you do with that information? How can you be efficient? How can you think outside the box?"
Industry-Specific Insights
Contrary to fears about AI eliminating jobs, our research suggests something more nuanced is happening: roles are being elevated and reconfigured rather than eliminated.
Healthcare and Biotech: AI as Capability Enabler
The healthcare leaders we interviewed were uniquely positioned to discuss AI's transformative potential because they're building AI-first solutions.
"This is only doable to do right now, not even 10 years ago, because... the technology finally caught up."
Key Healthcare AI Themes
- Data Integration: Breaking down silos between research institutions
- Precision Medicine: AI enabling personalized treatment approaches
- Diagnostic Speed: Real-time analysis of complex biological data
- Regulatory Navigation: AI helping manage complex compliance requirements
Construction and Infrastructure: Digital Transformation Acceleration
Kevin Kane (Ascent OS CEO) highlighted how AI is changing risk assessment in traditionally conservative industries:
"People are kind of scared, I know about AI and how that might get involved and start minimizing jobs... I tend to be a little more optimistic. You look at the Internet, right, people thought the Internet was going to blow up the world and it didn't."
Construction Industry AI Applications:
- Project Management: AI-powered scheduling and resource allocation
- Risk Assessment: Predictive analytics for project delays and cost overruns
- Safety Monitoring: Real-time hazard detection and prevention
- Supply Chain: Automated procurement and inventory management
Marketing and Sales: The Creative-Efficiency Balance
Our marketing executives revealed a fascinating tension between AI's efficiency gains and concerns about creative authenticity.
"AI is honestly about tools or it's about, yes, absolutely. You can bring in lot of efficiency in your workflows and in your throughput, but AI in my mind is all about creating that culture of curiosity. And it is hard because a lot of senior execs, the mindset is always, I've done this for 30 years."
Marketing AI Success Patterns
- Custom GPTs: Using proprietary data for competitive intelligence
- Content Strategy: AI for research and ideation, humans for creativity and strategy
- Customer Intelligence: AI analyzing customer conversations and feedback
- Attribution: AI helping solve the persistent attribution problem
Legal Technology: The Post-Law Firm World
Matt Lhoumeau from Concord presented perhaps the most radical transformation vision:
"We see they don't have legal teams anymore. I really see it a lot. I think it's going to be more and more common. And so we're building a tool that's going to help them just accelerate."
This "post-legal world" concept suggests entire professional service categories may be reimagined rather than simply automated.
The Relationship Renaissance
Why Human Connection Matters More, Not LessParadoxically, as AI handles more routine interactions, the value of genuine human relationships is increasing dramatically.
"In a world of commoditized tech, in a world of AI, it's the customer relationship that matters. And so how can you value, how can you create customer relationships? If you were a B-minus door-to-door salesman 10 years ago, you're going to be best in class."
The Trust Imperative
Jon Hunter (CEO at HunterX ), an enterprise sales expert with decades of experience, emphasized:
"A lot of these folks have been oversold and under delivered for 25 years. So no matter that they'd never met you, they don't trust you... The way you come out of that is just have super empathetic attention to detail, getting to know them."
Information Commodity
AI gives everyone access to the same information
Decision Fatigue
Too many options require trusted advisors
Change Anxiety
People need reassurance during transformation
Systematic Approach
They build systematic approaches to AI adoption
The Quality vs. Quantity Paradigm
The Flight to ExcellenceA consistent theme across interviews was the shift from volume-based to quality-based approaches across all business functions.
"I think what happens is people really focus on, like right now, everyone's in this hype phase where they're just regurgitating content and just throwing stuff out there... that's not the content that's going to be used because AI actually has its own way of detecting AI generated content."
Measurable Quality Improvements
Review Rejection Rate
TrustRadius rejects over 60% of all reviews for fraud, misinformation, or AI generation
AI-Written Content
Less than 10% AI-written content (lowest among review platforms)
This quality focus isn't limited to content—it extends to:
- Team Composition Hiring senior talent over junior + AI supervision
- Customer Service Deeper relationships with fewer clients
- Product Development Fewer features, better execution
- Market Positioning Niche expertise over broad capabilities
TrustRadius Quality Standards
- Reject 60%+ of all reviews for fraud, misinformation, or AI generation
- Less than 10% AI-written content (lowest among review platforms)
- Focus on authentic, hard-to-replicate customer experiences
Common Implementation Mistakes
What We Learned from FailuresOur interviews revealed several patterns of AI implementation failures that companies can avoid:
Buying tools before defining problems
The Pattern: Companies buy AI tools and then look for problems to solve.
"I'm not sure if excited would be the right word. Something I'm a little, I would say, worried about because it's still so new that I'm not sure how it will affect Google Ads... as people rely less and less on Google search and switch to different LLMs."
- Gabriel from Userlytics
Ignoring Culture + Training
The Pattern: Expecting teams to adopt AI naturally without training or cultural preparation.
"We interview and I use the, say that cautiously because we don't like calling it interviews because we feel like interviews are broken processes... we hire people for their cognitive ability."
- Sean Lee (OpenDrive)
Waiting for Perfect Solutions
The Pattern: Waiting for perfect solutions or complete certainty before acting.
"People that are feeling paralyzed are the ones that are going to be left behind, and that analysis paralysis is gonna get you."
Expecting results from bad data
The Pattern: Expecting AI to work magic with poor-quality, siloed data.
Multiple executives emphasized data foundation importance, with Michael from Duro noting:
"If your data, your internal data is not consolidated, it's not clean, then training your model... Only challenge is that if your data, your internal data is not consolidated, it's not clean, then training your model doesn't work."
Success Framework: What Works
The AI Maturity ModelBased on our interviews, we identified five stages of AI organizational maturity:
Stage 1: AI Curious (Most Companies)
- Individual experimentation
- Scattered tool adoption
- No coordinated strategy
- Limited business impact
Stage 2: AI Aware (35% of Companies)
- Leadership acknowledges AI importance
- Some budget allocated to AI initiatives
- Pilot projects launched
- Mixed results and learning
Stage 3: AI Strategic (20% of Companies)
- Clear AI strategy aligned with business objectives
- Cultural change management programs
- Systematic approach to implementation
- Measurable ROI improvements
Stage 4: AI Native (10% of Companies)
- AI integrated into core business processes
- Culture of continuous AI innovation
- Competitive advantage through AI capabilities
- Exponential productivity improvements
Stage 5: AI Transformative (5% of Companies)
- Business model fundamentally enabled by AI
- Industry leadership through AI innovation
- Ecosystem effects and network advantages
- AI as primary competitive moat
The Implementation Playbook
Phase 1: Foundation Setting
(Months 1-3)
- Clear AI strategy aligned with business objectives
- Cultural change management programs
- Systematic approach to implementation
- Measurable ROI improvements
Phase 2: Strategic Piloting
(Months 4-9)
- High-impact, low-risk pilot projects
- Cross-functional team formation
- Success metrics definition
- Learning and iteration cycles
Phase 3: Systematic Scaling
(Months 10- 18)
- Successful pilot expansion
- Process standardization
- Advanced team capability development
- Competitive advantage emergence
Phase 4: Transformation Acceleration
(18+ Months)
- High-impact, low-risk pilot projects
- Cross-functional team formation
- Success metrics definition
- Learning and iteration cycles
Looking Ahead: 2025/26 Predictions
What Executives ExpectBased on our conversations, here's what business leaders anticipate for 2025/2026:
Near-Term Certainties (Next 6-12 Months)
- Further consolidation of AI tool landscape
- Increased focus on AI ROI measurement
- More sophisticated AI literacy across organizations
- Regulatory clarity and compliance frameworks
Likely Developments
- Industry-specific AI solutions gaining traction
- AI-human collaboration models becoming standard
- Data governance becoming competitive advantage
- Smaller, more capable teams becoming the norm
Potential Disruptions
- Entire professional service categories being reimagined
- Traditional competitive moats being eroded
- New forms of business model innovation
- Generational shifts in workforce expectations
The Adaptation Imperative
"In a couple of years, will be tremendous amount of people that were very valuable two years ago and now it's a problem... You will be left with the top 5%, top 10% people that can actually manage a team instead of... or manage a team of like AIs, agents, instead of managing a team of people."
- Dori Fussmann (abs)
Job Elevation, Not Replacement
This isn't about job replacement, it's about job elevation. The professionals who thrive will be those who learn to orchestrate AI capabilities rather than compete with them.
Key Recommendations
For CEOs and Senior Leaders
- Develop AI Literacy Fast: You can't lead what you don't understand
- Invest in Culture Change: Technology adoption without culture change fails
- Start with High-Impact Pilots: Build confidence through early wins
- Focus on Data Foundation: AI effectiveness depends on data quality
- Embrace the Learning Mindset: "Know it all" cultures will struggle
For Technology Leaders
- Think Platform, Not Point Solutions: Build integrated AI capabilities
- Prioritize Interoperability: Avoid AI tool silos
- Plan for Scale: Architecture decisions made today will matter for years
- Security by Design: AI introduces new security considerations
- Measure What Matters: Track business outcomes, not just technical metrics
For Marketing and Sales Leaders
- Quality Over Quantity: Focus on authentic, valuablecontent
- Embrace Relationship Renaissance: Human connection is becoming more valuable
- Build Custom Intelligence: Proprietary data creates AI competitive advantage
- Prepare for Attribution Changes: Traditional tracking methods are evolving
- Invest in Creative Strategy: AI handles execution, humans drive vision
For HR and People Leaders
- Rethink Role Definitions: Focus on cognitive abilities over specific skills
- Create Upskilling Programs: Help people transition to AI augmented roles
- Hire for Adaptability: Learning ability matters more than current knowledge
- Design for Collaboration: Humans and AI working together, not competing
- Culture Eats Strategy: The best AI strategies fail without cultural support
Conclusion
Our research with 20+ senior executives across industries reveals a crucial inflection point: the companies that master AI integration in the next 18-24 months will build sustainable competitive advantages, while those that don't will find themselves increasingly disadvantaged.
But this isn't primarily a technology challenge, it's a leadership and cultural transformation challenge.
Embrace Uncertainty
They embrace uncertainty and continuous learning
Cultural Investment
They invest in cultural change alongside technology
Human Augmentation
They focus on augmenting human capabilities rather than replacing them
Systematic Approach
They build systematic approaches to AI adoption
Outcome Focus
They measure business outcomes, not just technical capabilities
The executives who are succeeding with AI share common characteristics
"The path forward isn't about having the most advanced AI tools it's about building organizations that can effectively integrate AI into their core business processes while maintaining the human elements that create lasting value."
As Benu Agarwal summarized:
"AI is not about bouncing back, it's bouncing forward."
The question isn't whether your organization will be affected by AI, it's whether you'll be leading the transformation or scrambling to catch up.
The executives we spoke with are at various stages of this journey, but they all share one thing: they're actively experimenting, learning, and adapting. The window for passive observation is closing rapidly.
What's Next?
If the insights in this report resonate with your experience, if you recognize your organization in these stories of uncertainty, opportunity, and transformation you're not alone.
The executives we interviewed didn't have all the answers when they started their AI journeys.
What they had was curiosity, commitment to learning, and willingness to experiment systematically rather than hope for perfect solutions.
Let's Connect
If you found this research helpful and think a conversation about your specific situation would be valuable, let's schedule a brief 15-minute call where we can dive into these topics more deeply and share some practical insights about how you can leverage AI within your organization today.
About This Research
This report was compiled by Mayven Studios based on comprehensive interviews conducted as part of the "Top Engineering Cultures" podcast series. All insights and quotes are used with permission from interview participants.
Research Team:
- Nate McGuire, Founder & Host
- Mayven Studios Research Team
Podcast Episodes Guests Referenced:
- Dori Fussmann: The Vets (Israeli Veterinary Services)
- Kevin Kane: Ascent OS (Construction Management Platform)
- Michael Corr: Duro (Hardware Development Tools)
- Yar Salek: DeepCell (Biotech AI Solutions)
- Matt Lhoumeau: Concord (Legal Contract Management)
- KC Brothers: Canopy (Product Marketing, Accounting Software)
- Gabriel Rivas-Micoud: Userlytics (User Experience Research Platform)
- Allyson Havener: TrustRadius (B2B Review Platform)
- Benu Agarwal: Milestone (Digital Platform Solutions)
- Bubba Smitham: Acquire ROI (HR Technology)
- Michael Kravik: Blue Yeti (Modern Data Stack Consulting)
- Greg Bayer: Taylor AI (Marketing Technology)
- Sean Lee: OpenDrive (Media Storage Solutions)
- Jon Hunter: Enterprise Sales Consultant
Full podcast episodes are available at our YouTube channel for deeper insights into each conversation.
© 2025 Mayven Studios. All rights reserved. This research may be shared and referenced with attribution to Mayven Studios.- Executive Summary
- Methodology
- The Universal AI Anxiety
- The Implementation Challenge: Tools vs. Strategy
- The Cultural Transformation Imperative
- Skills Evolution: Transformation, Not Replacement
- The Small Team Revolution
- Industry-Specific Insights
- The Relationship Renaissance
- The Quality vs. Quantity Paradigm
- Common Implementation Mistakes
- Success Framework: What Works
- Looking Ahead: 2025/26 Predictions
- Key Recommendations
- Conclusion
- What's Next?
- About This Research