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Why Your AI Consultant Is Taking 8 Months (And How to Ship in 3 Weeks)

 

You hired an AI consultant six months ago.

They’ve conducted 47 stakeholder interviews. They’ve built a comprehensive capability assessment. They’ve mapped your tech stack. They’ve created a strategic framework.

You have 94 PowerPoint slides and zero working systems.

The Billable Hours Problem

Here’s what nobody tells you axbout consulting economics:

Traditional consultants get paid by the hour. Or by the project phase. Or by “level of effort.”

Their incentive is to make the project take as long as possible while keeping you happy enough not to fire them.

That’s not evil. It’s just… how the model works.

The Standard AI Consulting Timeline:

Phase 1: Discovery (Months 1-2)

  • Stakeholder interviews
  • Current state assessment
  • Pain point identification
  • Opportunity mapping
  • Deliverable: 30-slide deck on what you already knew

Phase 2: Strategy Development (Months 3-4)

  • Capability assessment
  • Technology evaluation
  • Use case prioritization
  • ROI modeling
  • Deliverable: Strategic framework document

Phase 3: Implementation Planning (Months 5-6)

  • Detailed roadmap creation
  • Resource requirement analysis
  • Risk assessment
  • Change management planning
  • Deliverable: 94-page implementation plan

Phase 4: Pilot Planning (Months 7-8)

  • Pilot scope definition
  • Success metrics establishment
  • Stakeholder alignment sessions
  • Deliverable: Readiness to maybe start building something

Total cost: $200-300k

Total working systems: 0

What Actually Needs to Happen

Here’s what we do at Brainlink:

Week 1: Rapid Assessment

  • 3-hour workshop with key stakeholders
  • Identify top 3 highest-impact automation opportunities
  • Map current workflows
  • Done.

Week 2-3: Build

  • Implement first automation
  • Test with real data
  • Iterate based on actual usage
  • Done.

Week 4-6: Scale

  • Add 2-3 more automations
  • Train team on usage
  • Monitor and optimize
  • Done.

Total cost: $40-60k

Total working systems: 3-4

The Real Difference

A managing partner told us last month: “I don’t understand. Our last consultant said AI implementation requires extensive change management, stakeholder buy-in sessions, and a 6-month pilot program. You’re saying you’ll just… build it?”

Yes.

Here’s why:

Traditional consultants assume:

  • You need consensus before action
  • You need comprehensive planning before building
  • You need extensive documentation before implementation
  • You need to understand everything before starting anything

We assume:

  • You need working prototypes to build consensus
  • You need real results to inform planning
  • You need actual systems to generate useful documentation
  • You need to start somewhere and iterate

Different philosophy. Different timeline.

Why Fast Works Better Than Slow

There’s a dirty secret in the consulting world:

Long projects fail more often than short ones.

Why? Because:

  1. Momentum dies. Month 6 of planning, your team stops caring.
  2. Requirements change. Your business evolves while consultants are still mapping your current state.
  3. Stakeholders leave. The person who championed the project retires or takes another job.
  4. Budget gets reallocated. CFO sees 8 months of spending with zero output and pulls the plug.

Fast implementations avoid all of this:

  1. Momentum builds. Week 3, your team sees something working and gets excited.
  2. Requirements clarify. Real usage reveals what actually matters.
  3. Stakeholders stay engaged. 6 weeks from start to finish keeps everyone involved.
  4. ROI appears quickly. Working systems in month 1 make budget conversations easy.

The Incentive Structure Problem

Let me be blunt:

Traditional consulting firms don’t want to ship fast.

Fast means:

  • Fewer billable hours
  • Less “level of effort” to sell
  • Harder to justify large teams
  • More accountability for results

Slow means:

  • More engagement phases
  • More consultants on the project
  • More documentation to produce
  • More room to hide when results don’t materialize

We get paid when systems work. They get paid when projects continue.

Different incentives. Different outcomes.

What One CFO Told Us

“We spent $280k over 9 months with [major consulting firm]. We got beautiful documentation about our AI readiness. Zero working systems.

We spent $50k over 6 weeks with Brainlink. We got 4 working automations that saved us 30 hours/week. The documentation was an afterthought, written based on what actually got built.

The first approach felt professional. The second approach felt effective.

I’ll take effective.”

When Slow Makes Sense

This isn’t “consulting bad, fast good.”

Sometimes you need extensive planning:

  • Highly regulated industries with strict compliance requirements
  • Firm-wide transformations affecting 200+ employees
  • Mission-critical systems where failure has catastrophic consequences
  • Complex integrations across 50+ legacy systems

But most firms aren’t in these situations.

Most firms just need someone to build the thing instead of planning how to plan to build the thing.

The Question to Ask Your Consultant

Next time you’re talking to an AI consultant, ask:

“How many weeks until we have our first working system?”

If the answer is:

  • “We need to assess before we can answer that” 🚩
  • “Typically after the strategy phase completes” 🚩
  • “Implementation timelines vary based on readiness” 🚩
  • “Let’s discuss the discovery process first” 🚩

If the answer is:

  • “Week 3” ✓
  • “Depends on your specific workflows, but usually 2-4 weeks” ✓
  • “We’ll have a prototype running by end of week 2” ✓

Different answers. Different billing models.

Brainlink commits to working systems in weeks, not roadmaps in months. See what we can ship in 6 weeks

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