The Real AI Debate

Are You Building Tools or Reinventing Work?

Hey there! I’m Eric Feddal, the Head of Growth at Ingedata. I I work on the frontline of enterprise GenAI transformation, and a troubling pattern is emerging. Too many organizations are limiting their AI ambitions, focusing on making small, often obsolete models perform basic, isolated tasks. This approach isn’t transformation; it’s incrementalism.

At Ingedata, we understand the risks and architectural complexities of scaling agentic AI, which means autonomous systems capable of making decisions independently. But we also see the huge potential for companies ready to move boldly, quickly, and deeply into AI transformation.

Eric Feddal

Head of Growth

The real challenge is not the technology. It is the imagination behind how AI is applied. Most leaders still struggle to picture how their core processes would change if autonomous agents handled 60 percent of the work. This is not about copilots or improved search tools; it is about Real, end-to-end transformation.

The Hidden Engine of AI Transformation

To understand the gap between small tools and true reinvention, we need to look at how AI is actually built. In a recent discussion, Wharton Professor Ethan Mollick highlighted a critical, often-overlooked truth: AI is not magic. It’s built on a foundation of massive human labor dedicated to creating and annotating high-quality data.

This “human-in-the-loop” approach is the engine of AI transformation. But the quality of that engine determines everything. Before an AI agent can autonomously reason across legal contracts or dynamically create sales proposals, the data it learns from must be flawless.

This is where the tool-making approach falls short. It often relies on disconnected, low-context data work. At Ingedata, we see things differently. Our foundation is built on providing the expert human teams necessary to ensure data quality from the start. We don’t just process data; we create the reliable foundation for transformative AI.

This is proven in our work in the most demanding sectors:

For Defense & Intelligence clients like Safran, we use expert photo analysts in a “Human in the loop” process to achieve 99.81% accuracy in detecting strategic objects from satellite imagery. This isn’t just labeling; it’s mission-critical analysis that trains sophisticated AI.
In advanced recycling for partners like Pellenc ST, our specialized teams perform complex contaminant classification across various waste streams, annotating over 50,000 images to power revolutionary optical sorting AI that’s transforming recycling efficiency.
For energy leaders, we enable AI systems to detect subtle faults in high-voltage pylons and solar panels, ensuring grid reliability and maximizing asset longevity.

What sets Ingedata apart? Our stable, highly skilled workforce maintains a staff turnover rate of less than 3%—ensuring consistency and expertise that volatile gig-worker models simply cannot match. This stability translates directly into superior data quality and client outcomes.

From Assistant to Orchestrator: Reimagining Core Processes

Once you have this foundation of data quality, you can start asking the bigger questions that drive real transformation:

While teams go back and forth on a single NDA, what happens when your legal workflow can reason across thousands of case laws and contracts without direct human input?
What does sales become when pricing, targeting, and proposal writing are handled by agents that learn and adapt in real time?
What is the new role of the human when GenAI moves from assistant to co-worker to orchestrator?

That’s the paradigm shift we’re enabling today at Ingedata—with real agents in real processes, not just pilots or proof-of-concepts.

The real debate is not small versus large AI models. It is about moving beyond tool-based thinking to reinvent how work happens.

So, what’s your take? Are you building AI tools just to save time? Or are you ready to rethink the very shape of work?

This conversation is critical for transformation leaders. If you’re thinking about making 2025 the year you go beyond copilots and build a truly intelligent operation, let’s connect.

Why Ingedata? The Transformation Partner You Need

The debate shouldn’t be small models vs. big models. It’s tool thinking vs. operating model reinvention.

At Ingedata, we believe true transformation requires three critical elements:

Expert Human Intelligence: Our specialized teams bring domain expertise that ensures AI learns from the highest quality, most contextually rich data
Scalable Infrastructure: We’ve built the reliable, consistent workforce and processes needed to support enterprise-scale AI initiatives
Transformation Vision: We partner with leaders who are ready to reimagine their core processes, not just optimize existing ones

Ready to Lead the AI Revolution?

So, what’s your take? Are you building AI tools just to save time? Or are you ready to rethink the very shape of work itself?

This conversation is critical for transformation leaders. If you’re thinking about making 2025 the year you go beyond copilots and build a truly intelligent operation, the foundation starts with data quality, expert human insight, and the vision to reimagine your core processes.

The question isn’t whether AI will transform business—it’s whether you’ll lead that transformation or be left behind by it.

At Ingedata, we’re not just service providers—we’re transformation partners. We bring the expertise, stability, and vision needed to turn AI potential into business reality.

Ready to transform your business with AI that actually works?

Connect with our team to explore how Ingedata’s expert human-in-the-loop processes can power your next-generation AI initiatives.

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