As AI adoption continues to grow, businesses are asking fundamental questions: What is value? How do we measure it? And when can we expect to see results? In a 2024 Everyday AI Berlin session, we explored these pressing issues through real-world insights, interactive discussions, and industry data.
This session led by Stephanie Griffiths, field chief data officer at Dataiku, revealed five myths that often prevent businesses from unlocking the true potential of AI and provided actionable tips on overcoming these challenges.
Myth 1: Value Is a Fixed Concept
One of the biggest misconceptions in AI adoption is having a narrow definition of value.
Don’t limit AI value to specific data team’s KPIs:
If I have to prove the value of my data lake, I know I lost the game.
— Stephanie Griffiths, field chief data officer at Dataiku
Think beyond efficiency. How can AI advance your mission, not just optimize tasks?
Value first, tech second. What impact do you want — economic, social, cultural? AI is a tool, not the goal.
A retailer needs to shift products off the shelves. But is there something else they could think about? For example, Decathlon now measures success based on CO2 reduction rather than just sales. This leads to new KPIs such as longer product life and transformative business models: renting versus selling certain types of goods.
— Stephanie Griffiths, field chief data officer at Dataiku
Key Takeaways:
- Brainstorm different value types with your team, and don't limit yourself to the data field.
- Broaden your definition of value beyond immediate ROI and focus on economic, social, cultural, and geopolitical impact.
- Experiment and be curious.
Myth 2: The Chief Data Officer Has a Magic Wand
Hiring a Chief Data Officer is not a one-stop solution for making data work perfectly. AI success requires collaboration across departments, not just data teams. A CDO isn’t enough. The real power comes from collaboration, especially with the CFO, who understands value from a business perspective.
Key Takeaways:
- AI is not just about data and models — it’s about business impact.
- Partner with finance, operations, and leadership teams to define and communicate value.
- Build trust in data across the organization by ensuring transparency and reliability.
Myth 3: AI Always Delivers Rapid ROI
There’s a common belief that AI leads to immediate value creation. However, real-world AI adoption takes time, especially when factoring in readiness, talent acquisition, and integration costs.
Key Takeaways:
- AI requires investment in talent, infrastructure, and process changes.
- Companies must consider the cost of being wrong and the impact of inaccurate models.
- Focus on operationalizing AI rather than just building models.
Myth 4: More AI Tools = Better Performance
Many businesses assume that adopting more AI tools will automatically lead to better outcomes. However, the real challenge lies in collaboration, knowledge sharing, and implementation. Note that over-reliance on AI tools also weakens the ability of teams to think, iterate, and create!
Success isn’t about having the most tools; it’s about teamwork. AI and data culture must be nurtured to drive real business impact.
— Stephanie Griffiths, field chief data officer at Dataiku
Key Takeaways:
- Foster a collaborative AI culture within your organization.
- Encourage experimentation and learning through small AI projects.
- Ensure AI tools are well-documented and easily accessible for all teams.
Myth 5: More AI Users = Higher ROI
While increasing AI adoption is crucial, it does not guarantee success unless businesses establish a clear strategy and best practices.
The more users we have for GenAI doesn’t mean better ROI. The key is refining prompts and ensuring AI adoption is efficient.
— Stephanie Griffiths, field chief data officer at Dataiku
Key Takeaways:
- Train employees on how to effectively use AI tools — get tips in this AI literacy bundle!
- Store and optimize AI-generated knowledge to prevent redundancy.
- Use AI monitoring systems to track effectiveness and iterate on improvements.
The Path to AI Success
The true value of AI extends far beyond mere speed and productivity. It lies in its ability to drive smarter business decisions, fuel innovation, and generate lasting impact. Organizations that successfully implement AI recognize that its benefits go beyond immediate financial returns.
They cultivate a culture of collaboration and continuous learning, ensuring that AI tools are not only accessible but seamlessly integrated into existing workflows. Rather than limiting AI to isolated experiments, they focus on fully operationalizing its capabilities, embedding it into their core strategies to maximize long-term success.
As Stephanie said, "We don’t have doubts that AI will generate value — the question is when and how. Companies that start strategizing now will be ahead of the game."