Ivan Batanov: The CTO role in the AI augmented organization (Scale Project – ep. #1)

 

CTO and SVP of Engineering, with a career spanning Microsoft, Yahoo, and leading scale-ups in AI, fintech, and data, Ivan Batanov shares his unique perspective on the evolving role of a technology leader in today’s world, and the critical intersection of AI, data, business strategy and people management.

 In this episode, you will learn:

1. Why hosting and training your AI models in-house can become a decisive competitive advantage.
➤ A strategy that protects your data, strengthens tech autonomy, and creates long-term strategic value.

2. How to avoid costly mistakes in a rapidly evolving AI ecosystem.
➤ A simple approach to experiment with AI without locking yourself into a vendor or technology dependency.

3. How to quickly identify the three areas where AI can deliver immediate impact in your organization.
➤ A clear framework: personal productivity, team efficiency, and product differentiation.

4. Why technical debt is now one of the biggest barriers to AI adoption – and what to do about it.
➤ A counterintuitive insight: sometimes, it’s smarter to pause for six months to harmonize your tech stack—and double your innovation speed afterward.

    If you’re a technology leader, entrepreneur, or AI enthusiast, this conversation will provide valuable insights into how to stay ahead of the curve in today’s fast-changing landscape.

    Links:

    Linkedin: https://www.linkedin.com/in/ivanb/ 

    Here are a few highlights from our conversation

    1. The Rising Complexity of the Technology Landscape

    • The number of available solutions has grown exponentially (e.g., from 2 databases 20 years ago to 20 today).
    • Businesses must deal with legacy systems while adapting to shorter innovation cycles.
    • Technology is evolving at an exponential rate, making agility and adaptability essential.

    2. The Expanding Role of the CTO

    • A modern CTO needs to be close to business, technology, and people simultaneously.
    • Historically, CTOs were either managers (running engineering teams) or visionaries (shaping architecture).
    • Today, CTOs must do both, balancing technical depth and strategic oversight.

    3. Mastering AI Adoption in Organizations

    • AI integration should be approached in three layers:
      • Personal productivity: How AI can help leaders and teams work smarter.
      • Company-wide efficiency: Using AI to optimize operations.
      • Product innovation: Enhancing products with AI capabilities.
    • Avoid premature adoption—AI is still in rapid development, and meaningful AI-driven products take time to build.

    4. Navigating the AI Technology Landscape

    • Maintain control over your AI stack by running models in your private cloud—this is an intellectual property asset.
    • Avoid vendor lock-in—keeping provider and model independence is crucial as the AI landscape evolves rapidly.
    • AI will likely follow a database-like market structure—companies will choose between open-source, self-hosted models and commercial AI services.

    5. AI’s Impact on Software Development

    • AI is accelerating the speed of building new software, reducing time-to-market.
    • Future software must provide insights—products without AI-driven intelligence will become obsolete.
    • Hybrid teams of human engineers and AI tools will drive development, but human expertise remains irreplaceable.

    6. The Startup Mindset: Lessons for Large Organizations

    • Startups have no legacy tech debt, allowing them to move faster.
    • Large organizations must assess the opportunity cost of maintaining outdated systems.
    • Some companies should pause and restructure their backend systems to enable high-velocity development.

    7. Eliminating Friction in Engineering Processes

    • Deploying new software often involves unclear and bureaucratic steps in large companies.
    • Organizations need to remove both organizational and technological friction to maintain agility.
    • The faster a company can adopt new technology, the greater its competitive advantage.

    8. The Regulatory Challenge: Balancing Innovation and Control

    • Global technology governance is becoming polarized, with the EU enforcing strict regulations while China accelerates innovation with fewer restrictions.
    • Heavy regulation (e.g., GDPR, AI Act) increases costs but doesn’t always benefit the consumer.
    • A regulatory framework must protect consumers without stifling innovation—otherwise, innovation will move elsewhere.

    9. The Future of Business in the AI Era

    • In 10 years, customer expectations will shift dramatically—software that doesn’t provide intelligent insightswill feel outdated.
    • The speed of software development will continue to increase, making adaptability a critical success factor.
    • Companies that fail to modernize their engineering foundations will struggle to compete.

    10. Advice for CTOs: How to Thrive in a Rapidly Changing World

    • Stop resisting AI—instead of fighting change, learn to surf the wave of innovation.
    • Stay on top of AI advancements—AI is already delivering real economic value, and companies that fail to adapt will fall behind.
    • Balance short-term pragmatism with long-term vision—leaders must think strategically while ensuring practical AI implementation.

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    Viorel Bucur     is the co-founder of Upscale Paris and The Scale Project podcast.

    Entrepreneur and Team Coach (ICF) with over a decade of experience in behavioral sciences, organizational systems, and tech entrepreneurship, he helps leaders and organizations navigate digital transformation, AI adoption, and organizational change.

    Passionate about human potential and leadership development, Viorel is dedicated to shaping the next generation of conscious and high-impact leaders, guiding them through transformational journeys that redefine the way they work, learn, and lead.