Verdict
"No, unless your LTV projections aren't just fantasy-based and you actually understand MEV beyond a buzzword."
GEO HIGHLIGHTS
- US market sees 3x VC funding in 'AI Transformation' in '23, 70% of it for vaporware.
- EU's AI Act creating compliance goldmine for lawyers, not necessarily innovation for consultants.
- APAC's 'AI-first' mandates driving massive, often ill-conceived, government contracts.
- Mid-tier consultancies rebranding overnight, chasing the 'AI premium' with zero actual expertise.
Every board now demands an 'AI strategy' from their C-suite. Consultants, seeing dollar signs, are happy to oblige, regardless of actual capability. It's the new 'digital transformation' gold rush, but with more hype, less tangible ROI, and far too many 'prompt engineers' selling glorified data labeling as cutting-edge AI.
Reality Check
The market's flooded with ex-Big-N grifters and 'AI ethicists' selling snake oil. Real value comes from deep domain expertise fused with actual ML engineering chops, not PowerPoint decks about 'synergistic AI ecosystems'. Most 'AI consulting' is just expensive data cleaning or basic automation rebadged. The few firms delivering measurable uplift in LTV, slashing operational MEV, or genuinely improving Retention are drowning in work. The rest are scrambling for scraps, peddling generic LLM wrappers that offer minimal actual TVL.💀 Critical Risks
- Over-promising and under-delivering: Clients burn cash, get nothing but a hefty invoice.
- Data privacy and ethical AI compliance nightmares for consultants who don't understand the tech or the law.
- Talent drain: Real AI engineers prefer building products, not endless client presentations for clueless execs.
- Scope creep turning into existential budget black holes with zero ROI.
FAQ: Is my legacy system 'AI-ready'?
Probably not. You'll spend more on data cleaning and integration than on actual AI, then blame the model for not performing. Just rip it out.
