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Talent, Teams, and ROI: Where 250 AI Leaders Are Placing Their Bets in 2025 [New Research]

250 tech leaders reveal how they’re bridging the AI talent gap, measuring ROI, and investing their budget in 2025.

Only 36% of organizations have deployed AI to production; those using blended teams (combining freelancers with full-time employees) are twice as likely to succeed in AI implementation.

94% of tech leaders cite talent shortages as their primary barrier to AI innovation, with 92% planning to increase freelance engagements over the next 24 months.

Despite the "AI Trough of Disillusionment," 96% of leaders plan to increase AI investments in 2025, with 67% expecting ROI within a year and a notable shift toward revenue generation over cost reduction.

While 67% of business leaders predict AI will transform their organizations in 2025, only 36% have a well-defined vision for implementation. As generative AI enters Gartner's Trough of Disillusionment, we wanted to understand what separates successful AI innovators from those stuck in endless pilots.

We partnered with Riviera Partners to survey 250 senior product and engineering leaders responsible for AI initiatives across 27 industries to uncover the talent strategies, team structures, and technical investments that drive real results, and revealed the findings in our free 20-page State of AI Innovation Report (get it here).

Trapped in Prototype Purgatory

Despite predictions that AI will add $9 trillion to the annual GDP, only 36% of organizations have successfully deployed AI innovations to production. The majority remain trapped in what we call "prototype purgatory"—endlessly creating demos that never reach customers.

This bottleneck between development and production deployment represents the true challenge of AI innovation — moving beyond impressive demos to systems that deliver real business value.

The Talent Crisis Is Real

Talent constraints are overwhelmingly slowing AI progress. A staggering 94% of tech leaders identify talent shortages as their primary barrier to AI innovation, with 85% reporting delayed initiatives as a direct result.

Traditional hiring simply isn't working—67% of leaders say it takes 4+ months to hire top engineering talent, while 88% struggle to attract talent through conventional channels. As a result, 89% of leaders say that the traditional recruitment process is broken and needs an overhaul.

This bottleneck is forcing a fundamental rethinking of team structures.

Blended Teams: The Secret Weapon of AI Leaders

Our most surprising finding? Organizations using blended teams—combining specialized freelance talent with full-time employees—are twice as likely to reach advanced stages of AI innovation.

Among the 77% of organizations using blended teams, 40% have successfully deployed AI to production or achieved scaled usage—double the success rate of companies relying solely on traditional structures. These organizations report overwhelming benefits:

This shift toward flexible talent is accelerating rapidly. A remarkable 92% of tech leaders expect to increase their engagements with freelance or fractional talent in the next 24 months.

Build vs. Buy: The Path to Production

For companies that successfully deploy AI to production, 93% say building custom solutions delivers more value than off-the-shelf tools. This conviction grows stronger with experience—organizations with multiple production deployments are 1.67× more likely to strongly agree.

The leading technical investments for 2025 reflect this production mindset: 50% are prioritizing AI safety & monitoring tools; 49% are investing in AI development platforms and 41% are upgrading data infrastructure and AI Model Training Infrastructure.

ROI Expectations: Are We Coming Out the Other Side of the Trough of Disillusionment?

Despite Gartner placing Generative AI in the Trough of Disillusionment in 2024, our data suggests technical leaders remain bullish. An overwhelming 96% expect to increase GenAI investment in 2025, with 52% planning increases exceeding 50%.

ven more telling are ROI expectations: 32% of leaders expect to see returns from custom AI product development in less than 6 months, while 67% expect ROI within the next year. This optimism suggests the much-discussed disillusionment may be more media narrative than technical reality.

The focus is shifting from cost reduction to revenue generation, with 46% of organizations prioritizing AI's growth potential versus 30% focused primarily on efficiency gains. This signals a maturing perspective that views AI as a business transformer rather than just a cost-cutting tool.

Where AI Leaders Are Placing Their Bets

What separates successful AI innovators from those stuck in pilot purgatory? Our research reveals four clear strategies:

1) They're adopting blended teams that combine specialized freelance builders with full-time technical leadership

2) They're building custom solutions rather than relying solely on off-the-shelf tools

3) They're investing in foundational capabilities: development platforms, data infrastructure, and monitoring tools

4) They're focused on revenue-generating applications rather than just cost reduction

As AI capability gaps widen between organizations in 2025, technical leaders who can successfully bridge the talent gap while building production-grade systems will create lasting competitive advantages.


What You'll Find in the Full Report

The insights above are just the beginning. When you download the complete 2025 State of AI Innovation Report, you'll get in-depth analysis of:

  • Technical investment priorities: Detailed breakdowns of the AI platforms, tools, and infrastructure investments delivering the highest ROI across 27 different industries
  • AI talent strategy playbook: How leading organizations are designing blended teams, including optimal ratios of freelance to full-time staff and key roles to prioritize
  • GenAI skills gap analysis: The 10 most in-demand technical skills with detailed data on which roles are hardest to fill (48% struggle most with Data Scientists)
  • Build vs. buy decision framework: Criteria that successful AI innovators use to determine when to build custom vs. use off-the-shelf solutions
  • Capabilities Benchmarking: Where leaders benchmark their capabilities across key AI features, and how they're prioritizing investment for each in 2025.

Download the full State of AI Innovation Report to see all the data and discover how leading organizations are structuring their teams, measuring ROI, and making technical investments in 2025.

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