Enterprises face one common problem: the hidden costs of AI-based technical debt. “There’s a lot of hype around AI, but many initiatives aren’t founded in a business value proposition,” says Paul Brownell, CTO, Growth Acceleration Partners (GAP). “People wander in without an intentional path for ROI.”
In this episode of the Don’t Panic, It’s Just Data podcast, host Douglas Laney — BARC Research and Advisory Fellow, and author of Infonomics and Data Juice — speaks with Paul Brownell from GAP and Frank Lavigne — Advisory Board Member of CloudArmy. The speakers ultimately agree that AI promises greater returns on investment (ROI). However, it’s imperative to note that without a strong data foundation and strategy, AI can quickly turn into a financial nightmare.
Meet the Speakers:
- Paul Brownell
CTO, Growth Acceleration Partners (GAP) - Frank Lavigne
Advisory Board Member, CloudArmy
Host:
- Douglas Laney
BARC Research and Advisory Fellow, author of Infonomics and Data Juice
Key Takeaways:
- AI investments can create hidden financial burdens.
- Data readiness is crucial for successful AI initiatives.
- A hypothesis-driven approach can guide AI projects.
- Iterative experimentation leads to better outcomes.
- Data engineering is essential but often overlooked.
- Generative AI can assist in data pipeline management.
- Selecting AI tools requires flexibility and speed.
- Purpose-built AI models may outperform generative models.
- Organisations must foster a culture of continuous learning.
- Understanding the total cost of ownership for AI is vital.
If you’d like to discuss how to apply these strategies in your own environment, our team is ready to help — find more information at www.WeAreGAP.com
Enjoy!