How AI Strategy Consulting Should Work
A Case for Working with Builders
We are Stella and Amy. We share firsthand stories and perspectives that are either lost in translation or simply inaccessible to you. Together, we bridge cultural divides and bring the world a little closer—one post at a time.
In a recent chat with ZZ, co-founder and founding engineer at Kungfu AI, we explored what makes AI consulting effective—cutting through the hype to build real, impactful solutions.
The Cocoons
Stella: AI strategy is one of your company's key services. What does it do exactly? Is this role similar to a product manager for AI/ML projects?
ZZ: It's closer to traditional management consulting but specifically for AI. The key difference is that while engineers focus on technical aspects, strategists handle everything people-related. For example, in one project, we identified that measuring pure model accuracy wasn't the goal—it was about business value. A 70-80% accurate model that prioritizes problematic cases can significantly improve efficiency when a team can only review 10% of thousands of daily card uploads.
Stella: This resonates with my experience—I've been doing AI strategy without realizing there was a term for it.
ZZ: Exactly. Data scientists often make great strategists because they understand both technical and business aspects. The role involves:
Engineering context (pre- and post-implementation)
Cross-team coordination
Model governance
SME interviews (often revealing internal knowledge gaps)
ROI analysis for AI initiatives
Stella: True—many companies don’t have dedicated AI strategist roles. Instead, data science or ML team managers naturally bridge technical and business needs.
… (email us stellaxamy@gmail.com if you are interested in the full transcript of this podcast episode)
The Growing Disconnect in AI Consulting
Recent industry trends paint a concerning picture. Accenture announced $1.2 billion in new Generative AI bookings and plans to expand its AI workforce to 80,000 by 2026. Meanwhile, consulting giants like BCG and McKinsey report that AI-related work accounts for 20-40% of their revenue. (source)
Yet, a troubling gap is emerging—many AI consultants lack real-world, hands-on experience. Despite advising enterprises on AI strategy, they often have little direct exposure to building or deploying AI systems. This disconnect raises fundamental concerns about how organizations approach AI transformation.
Why AI Practitioners Make Effective Strategists
Our conversation with ZZ underscored why experienced data scientists—or AI practitioners—are well-suited to lead AI strategy. Their deep technical expertise, combined with business acumen, enables them to bridge the gap between cutting-edge AI and real-world impact.
Unlike traditional consultants, AI practitioners:
Align technical capabilities with business objectives, rather than fixate on pure model accuracy.
Understand how even "modest" models can drive significant operational improvements when properly integrated.
Anticipate real-world challenges and implementation hurdles before they arise.
“Always learning mentality” -- they follow the latest news on AI technologies and have good judgements on the pros and cons of new solutions
The Builder’s Advantage: Practical Experience Matters
ZZ highlighted how hands-on experience shapes better AI strategy, particularly in tool selection and implementation. Unlike consultants who recommend trending technologies without deep technical expertise, builders understand the real-world strengths and limitations of different tools.
For example, ZZ’s team might choose XGBoost—despite being a relatively old model (first released in 2014)—for its rapid training and adaptability, while leveraging LLMs in other scenarios where they provide a clear advantage.
This practical expertise extends to execution. Builder-led teams operate with small, highly skilled groups of 2-4 specialists who can both strategize and implement—unlike traditional consulting firms, which deploy large teams of business consultants with limited technical depth. The result? Faster execution, tighter alignment between strategy and implementation, and AI solutions that actually work in practice.
Why Traditional Consulting Falls Short
The current AI consulting boom has exposed critical weaknesses in traditional approaches. As Linas Beliūnas observed, CEOs and boards—under pressure to "do something with AI"—often turn to consulting firms that lack deep AI expertise. This leads to:
Overhyped AI roadmaps disconnected from execution realities.
Poorly scoped projects that overlook technical challenges.
A fixation on "cutting-edge" solutions rather than practical, high-impact implementations.
The Builder’s Alternative
Identify roadblocks early.
Design realistic project timelines.
Account for maintenance and scaling requirements.
Build strategies that are actually executable.
For AI strategy consulting to be truly effective, organizations need to rethink their approach. Instead of relying on traditional consulting firms, they should seek out AI practitioners who bring both technical depth and business acumen.
The ideal builder-strategists:
Have hands-on experience deploying AI across industries.
Know when simpler, traditional methods outperform trendy, complex models.
Prioritize business impact over hype.
Continuously learn and adapt to AI’s evolving landscape.
The goal isn’t to chase the latest technology—it’s to implement practical solutions that deliver real value.
The Rise of AI Practitioners in Strategy Consulting
We're witnessing the emergence of a new breed of AI consultants—practitioners who combine deep technical knowledge with business acumen. Firms like ZZ’s Kungfu AI exemplify this more effective approach to AI strategy consulting.
Their success comes from bridging the gap between technical possibilities and business realities. They understand implementation challenges, data infrastructure needs, and the importance of setting realistic timelines and expectations. Most importantly, they guide organizations through the entire journey, from strategy to execution.
As ZZ put it, "We care about practical AI, ensuring it delivers real value rather than just chasing novelty like academic research." This builder’s mindset, combined with strategic thinking, is what organizations need to successfully navigate their AI transformation journey.
The future of AI strategy consulting won’t be shaped by those who produce the most impressive reports but by those who can build, implement, and drive measurable business impact. As companies embrace AI, they should look beyond traditional consulting firms riding the AI wave—and seek out builder-strategists who can turn vision into reality.
Where to Find Builder-Strategists?
The best AI strategists aren’t just advisors—they’re practitioners who understand both the technical landscape and business realities.
If you’re looking for AI strategists that goes beyond the hype and delivers real impact, let’s talk.
Please subscribe The Cocoons for more exclusive conversation snippets and stories.
We are Stella and Amy. We share firsthand stories and perspectives that are either lost in translation or simply inaccessible to you.
