THE SIALIA CONSULTING GROUP SIALIA GROUP

What Big Consulting's AI Projects Don't Tell You

Here’s what actually happens 6–12 months after the consultants leave — and why your team is still using spreadsheets.

Big consulting firms love to publish glossy case studies showing 40% efficiency gains and ‘company-wide adoption.’ What they don’t show you is what happens 6–12 months after they leave—when the AI sits unused because nobody trained the warehouse manager how to actually use it.

What Big Consulting Pitched

THE PROMISE

40% reduction in manual processes through AI-powered workflow automation. Company-wide adoption across 2 facilities. $50k investment.

WHAT THEY DIDN'T TELL YOU

  • ✗ "Company-wide adoption" meant 3 people actually used it
  • ✗ The warehouse manager retired 4 months in—taking all the tribal knowledge with her
  • ✗ No change management process for floor staff, resulting in shadow workflows
WHAT $50k COULD HAVE BOUGHT
  • • Human in the loop automation of top 3 high-impact bottlenecks with internal buy-in
  • • 6 months of dedicated staff training and upskilling
  • • A customized ops dashboard that staff actually use daily

"If your warehouse manager hasn't been consulted on the AI roadmap, your $50K investment is actually a $50K donation to Big Consulting’s annual partner retreat."

What Big Consulting Pitched

THE PROMISE

$75K customer service overhaul. 60% improvement in first-touch resolution using LLM-based support agents. ROI achieved in 9 months.

WHAT THEY DIDN'T TELL YOU

  • ✗ "Resolution" counted every time the AI closed a ticket—even if the user was still angry
  • ✗ API costs ballooned to $11K/month because the prompt logic was inefficient
  • ✗ Customer churn hit a record high 3 months post-launch due to "AI hallucinations"
  • ✗ Nobody cleaned the training data before deploying the LLM—garbage in, garbage out at scale
WHAT $75K COULD HAVE BOUGHT
  • • A data cleaning and validation layer before a single LLM was deployed
  • • Targeted AI integration for the top 3 query types only—not everything at once
  • • A self-sustaining support infrastructure built on clean, reliable data your team actually trusts

"If your AI chatbot is hallucinating on your customers, it's not a feature—it's a brand suicide note funded by your shareholders."

What Big Consulting Pitched

THE PROMISE

$60K predictive maintenance project for a mid-size manufacturer. 25% reduction in downtime. Real-time sensor integration across 2 facilities.

WHAT THEY DIDN'T TELL YOU

  • ✗ The "real-time" data had a 24-hour lag because the legacy ERP couldn't sync faster
  • ✗ Maintenance teams ignored the AI alerts because they were 80% false positives
  • ✗ Sensor hardware was low-grade and failed in industrial heat within 6 months
WHAT $60K COULD HAVE BOUGHT
  • • Modern sensor infrastructure that actually survives the floor
  • • Clean, reliable data pipes before layering on the AI
  • • Predictive models built on real physics, not just statistical noise

"AI is not a band-aid for bad engineering. If your data is garbage, your AI will just produce garbage at industrial scale."

See the Pattern?

01

Big Consulting sells to C-suite with impressive decks and benchmark data

02

Implementation ignores the people who actually do the work

03

No real change management—just "here's the new tool"

04

System gets deployed without cultural readiness

05

Employees find workarounds to avoid using it

06

Consultants leave with their success fee

07

AI initiative fails 6-12 months later

"This isn’t a technology problem. It’s a people problem. And Big Consulting doesn’t solve people problems—they solve ‘how do we bill more’ problems."

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